API Endpoint for journals.

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            "pk": 21448,
            "title": "Predicting NCAA Men's Basketball Rankings: How Context Effects Shape Beliefs",
            "subtitle": null,
            "abstract": "We test whether the support one holds about an event is influenced by other hypotheses. We addressed this by examining context effects in subjective probabilities (SPs) when forecasting NCAA men's basketball team rankings. A challenge in investigating context effects with naturalistic stimuli is the need to model the different representations of the options. To do so, we adapted the Spatial Arrangement method to capture individual representations and developed an algorithm to select stimuli. We asked participants steeped in basketball knowledge to create spatial maps for 50 teams. They were then presented with customized triplets of teams and asked to estimate their SP that one team would outrank the others. The study uncovered context effects in SPs, and moderators of the effects. Our findings suggest that similar cognitive processes may govern the construction of belief and preference and highlight the importance of modeling mental representations to understand forecasting scenarios.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Representation; Bayesian modeling; Knowledge representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3999t0vj",
            "frozenauthors": [
                {
                    "first_name": "Jun",
                    "middle_name": "",
                    "last_name": "Fang",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Xiaohong",
                    "middle_name": "",
                    "last_name": "Cai",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Adaryukov",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Tim",
                    "middle_name": "",
                    "last_name": "Pleskac",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21448/galley/11047/download/"
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21448/galley/21893/download/"
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        },
        {
            "pk": 21495,
            "title": "Predicting the Unexpected - Analysis and Modeling of the Denial of Expectation",
            "subtitle": null,
            "abstract": "This paper explores the use of linguistic strategies, specifically discourse markers like 'but', to express contrasts between expectations and reality when faced with unexpected events. The study concentrates on Denial of Expectation (DofE), the\nmost powerful form of contrast, which arises when the expected value based on background assumptions is not met. The main focus of this paper is to model DofE as a weighted homogeneous relationship between object properties. The aim is to predict DofE for numerical properties in specific contexts. I aim to address a gap in previous models by considering the role of context. This is achieved by analyzing contrastive sentences from German car and motorcycle reviews. The research presents the concept of expectation intervals for scalar properties. These intervals align with expectations and exceeding them triggers a potential contrast. The study incorporates causality, expected behavior, and a shift function in selecting contrastive pairs, transforming the conditions into an algorithm.\n\nKeywords: contrast; computational and cognitive modeling; discourse analysis",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Linguistics; Concepts and categories; Decision making; Discourse; Perception; Pragmatics; Semantics; Computational Modeling; Discourse Analysis; Mathematical modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7gx68315",
            "frozenauthors": [
                {
                    "first_name": "Marie Christin",
                    "middle_name": "",
                    "last_name": "Walch",
                    "name_suffix": "",
                    "institution": "Leibniz Universität Hannover",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21495/galley/21940/download/"
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        {
            "pk": 24045,
            "title": "Prediction of Users Perceptional State for Human-Centric Decision Support Systems in Complex Domains through Implicit Cognitive State Modeling",
            "subtitle": null,
            "abstract": "This paper presents an approach to model the internal cognitive state of decision-makers when interacting with AI to understand exchanges between agents and improve future interactions. We focus on understanding how AI suggestions are perceived by a human agent using an approach based on the technology acceptance model. The variation in the user's state is investigated when perceiving the interaction with AI by considering it as a hidden (latent) state. Using human evaluation data collected from two cases of clinical decision-making and software development scenarios, we analyse and explore the user's perceptional state during interaction. The experiment conducted employs the Bayesian belief network to represent the human perceptional model and provide a prediction of the usefulness of AI model's suggestions in the considered case. Upon introduction of cognitive states in the model, we observed an increase in predictive performance by 76–77%. Our investigation can be concluded as an attempt to identify implicit static and dynamic cognitive characteristics of users to provide personalized assistance in human-AI interaction (HAI) and collaboration in complex domains of decision-making",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive architectures; Human-computer interaction; Agent-based Modeling; Bayesian modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/02t0z53n",
            "frozenauthors": [
                {
                    "first_name": "Sergey",
                    "middle_name": "",
                    "last_name": "Kovalchuk",
                    "name_suffix": "",
                    "institution": "Huawei",
                    "department": ""
                },
                {
                    "first_name": "Ashish",
                    "middle_name": "Tara Shivakumar",
                    "last_name": "Ireddy",
                    "name_suffix": "",
                    "institution": "ITMO University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24045/galley/21462/download/"
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            ]
        },
        {
            "pk": 24291,
            "title": "Predictive processing suppresses form-related words with overlapping onsets",
            "subtitle": null,
            "abstract": "Do language users predict word forms as readily as they predict semantic features? Previous studies are conflicting, possibly because they did not differentiate between two types of word form relationship: Head and rhyme relationships, sharing onset or offset features with predictable words. Here, we investigated prediction of form and meaning by means of a priming lexical decision task. People read constraining sentences that disconfirmed their expectations, and indicated, at sentence offset, whether a letter string was a word. Targets were predictable but not presented nouns, semantically related nouns, as well as head- and rhyme-related nouns. Unrelated control nouns were also presented. Results showed facilitation for predictable and semantically related words, with no difference between the two. While no effects emerged for rhymes, head-related words showed slowing, indicating suppression of lexical neighbors following prediction of word forms. Our findings align with word recognition models and prediction-by-production models of predictive processing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language understanding; Predictive Processing; Reading"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/95w210ck",
            "frozenauthors": [
                {
                    "first_name": "Katja",
                    "middle_name": "",
                    "last_name": "Haeuser",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Arielle",
                    "middle_name": "",
                    "last_name": "Borovsky",
                    "name_suffix": "",
                    "institution": "Purdue University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24291/galley/13887/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24291/galley/21463/download/"
                }
            ]
        },
        {
            "pk": 24072,
            "title": "Predisposed Mood and Music in Perceptual Judgement Task",
            "subtitle": null,
            "abstract": "The current study examines the interaction between predisposed mood, perceptual processing, and induced mood using music. We conducted an experiment in which participants were asked to identify stimuli at global or local (G/L) perceptual levels with four different background music conditions, which had different valence and arousal ratings. We used BMIS to assess current mood and PHQ-9 and GAD-7 to assess depression and anxiety, and divided the participants into two groups: distress and no distress (encompassing both disorders). We found a main effect of background music on mood. However, the distress group showed an overall low mood. Further, we observed an overarching effect of predisposed mood, encompassing depression and anxiety, on individuals' transient mood experience and perceptual task performance. Individuals in the non-distress group showed a larger global-precedence effect. The results are discussed in light of emotional reactivity theories and the theory of positive emotion.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Mood; Music; Perception; Comparative Analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4920c3h3",
            "frozenauthors": [
                {
                    "first_name": "Manas",
                    "middle_name": "",
                    "last_name": "Kabre",
                    "name_suffix": "",
                    "institution": "International Institute of information technology, Hyderabad",
                    "department": ""
                },
                {
                    "first_name": "Priyanka",
                    "middle_name": "",
                    "last_name": "Srivastava",
                    "name_suffix": "",
                    "institution": "International Institute of Information Technology, Hyd",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24072/galley/13666/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24072/galley/21464/download/"
                }
            ]
        },
        {
            "pk": 24563,
            "title": "Preliminary insights into the effects of ChatGPT on children's creativity",
            "subtitle": null,
            "abstract": "Creative thinking is associated with improved academic performance, social proficiency, problem-solving skills, and emotional wellbeing in children. Here, we explore the potential of ChatGPT, a language model developed by OpenAI, as an avenue for fostering creativity in children through prompting new ideas and ways of thinking. Six- to 11-year-old children's (N=140) performance on the Alternative Uses Test (AUT) was measured before and after completing one of three possible activities: (i) hearing single-word AI-generated uses for three objects, (ii) hearing sentence-long AI-generated uses for the three objects, or (iii) drawing a picture containing the three objects. Blind coding of children's own AUT responses (for different objects) before and after these activities suggested that children showed greater improvements in creativity in the two AI conditions (M=.55, SE=.14) than in the drawing condition (M=.04, SE=.15), F=4.17, p=.018. Our results provide initial support for ChatGPT as a useful tool for promoting children's creative thinking.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Cognitive development; Creativity; Human-computer interaction"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6x3981pf",
            "frozenauthors": [
                {
                    "first_name": "Kristy",
                    "middle_name": "L",
                    "last_name": "Armitage",
                    "name_suffix": "",
                    "institution": "The University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Jessica",
                    "middle_name": "",
                    "last_name": "Crimston",
                    "name_suffix": "",
                    "institution": "The University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Redshaw",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24563/galley/21465/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24563/galley/14160/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24563/galley/21465/download/"
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            ]
        },
        {
            "pk": 24843,
            "title": "Preparing Teacher Candidates with Pedagogical Approaches for ELLs in Hybrid/Virtual Learning Spaces",
            "subtitle": null,
            "abstract": "The purpose of this study is to empower preservice teachers (PSTs) to leverage relevant technology-based practices and be equipped with various tools and strategies appropriate for English Language Learners (ELLs) in PreK–12 grade settings. Now, more than ever, teacher candidates need to be prepared to understand the challenges faced by ELLs and provide various pedagogies for online platforms. This qualitative investigation explored 57 educators’ perspectives from PreK–12 schools, districts, and preparation programs in higher education in an effort to obtain relevant approaches in technology strategies and pedagogical frameworks that support ELLs’ remote learning. The study also draws on the knowledge needed to implement Social and Emotional Learning. Based on the findings, the study revealed (a) there are gaps between what teachers gain from the districts and what they have previously learned from their teacher preparation programs; (b) some teachers were not completely aware of the Social and Emotional Learning approach; (c) participants identified three pedagogical frameworks as most commonly used and they interchangeably used frameworks, programs, some online platforms, and resources in one section; and (d) educators’ insights highlighted what teachers should take into consideration (e.g., scaffolding/differentiated strategies) when planning, creating, and delivering instruction for ELLs in an online platform. Overall, participants emphasized the much-needed dedication to explore technology tools for various pedagogical approaches in hybrid/virtual learning spaces.",
            "language": "eng",
            "license": null,
            "keywords": [
                {
                    "word": "English learners"
                },
                {
                    "word": "COVID-19 pandemic"
                },
                {
                    "word": "preservice teachers"
                },
                {
                    "word": "hybrid/virtual learning"
                },
                {
                    "word": "pedagogical approaches"
                }
            ],
            "section": "Theme Section - Developing Strong Educators",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3fm0x68h",
            "frozenauthors": [
                {
                    "first_name": "Elsie",
                    "middle_name": "N.",
                    "last_name": "Solis",
                    "name_suffix": "",
                    "institution": "California State University",
                    "department": ""
                },
                {
                    "first_name": "Nirmla",
                    "middle_name": "G.",
                    "last_name": "Flores-Chang",
                    "name_suffix": "",
                    "institution": "Cal Poly Pomona",
                    "department": "Education"
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/24843/galley/14437/download/"
                }
            ]
        },
        {
            "pk": 21403,
            "title": "Preschoolers' Neophobia Influences Category-based Abilities Beyond the Food Domain",
            "subtitle": null,
            "abstract": "Food neophobia – the reluctance to eat novel food – has been associated with poorer performance in category-based tasks within the food domain among preschoolers. This research aims to unravel this negative relationship and determine if this association is specific to food items or reflects general cognitive rigidity in considering alternative ways to represent entities. In study 1, 123 children between 3 and 6 years were tested on an inductive reasoning task, comparing food and animals. In study 2, 112 children aged 4 to 6 engaged in a cross-categorization task comparing food, animals and artifacts. Results indicated that neophobic children exhibited poorer induction and cross-categorization performance in all domains compared to their neophilic counterparts. These findings highlight the importance of child characteristics in shaping the general development of category-based abilities and suggest that food neophobia, rather than a fear of novelty, reflects instead difficulties in changing perspectives once items have been classified.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Concepts and categories; Knowledge representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2rq7f936",
            "frozenauthors": [
                {
                    "first_name": "Foinant",
                    "middle_name": "",
                    "last_name": "Damien",
                    "name_suffix": "",
                    "institution": "Université de Bourgogne",
                    "department": ""
                },
                {
                    "first_name": "Lafraire",
                    "middle_name": "",
                    "last_name": "Jérémie",
                    "name_suffix": "",
                    "institution": "Institut Lyfe Research and Innovation Center",
                    "department": ""
                },
                {
                    "first_name": "Jean-Pierre",
                    "middle_name": "",
                    "last_name": "Thibaut",
                    "name_suffix": "",
                    "institution": "Université de Bourgogne",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21403/galley/11002/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21403/galley/21848/download/"
                }
            ]
        },
        {
            "pk": 24368,
            "title": "Preservice teachers' understanding of mathematical equivalence",
            "subtitle": null,
            "abstract": "Prior research has shown that many elementary school students hold misconceptions about mathematical equivalence, interpreting the equal sign operationally as an indicator to give an answer or the total. They often fail to correctly solve missing operand problems such as 1+5=  ___  + 2. The present study extends the research on mathematical equivalence to examine pre-service teachers' performance on equivalence tasks.  Results show that some participants failed to correctly solve missing operand problems and chose an operational definition of the equal sign over the correct relational definition.  Many participants failed to recognize statements that violate equality and failed to correctly identify equations and operations. These findings suggest that misconceptions of mathematical equivalence can involve confusion about the definition of equation and the meaning of mathematical operation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Learning; Other; Statistics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0bn3d6n9",
            "frozenauthors": [
                {
                    "first_name": "Jennifer",
                    "middle_name": "",
                    "last_name": "Kaminski",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24368/galley/13965/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24368/galley/21466/download/"
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            ]
        },
        {
            "pk": 24672,
            "title": "Prestimulus Periodic and Aperiodic Neural Activity Shapes McGurk Perception",
            "subtitle": null,
            "abstract": "Studies have reported that prestimulus brain oscillations guide perceptual experiences during AV speech perception. However, 'what' features in such oscillations drive perception remains unknown. In this EEG study (n=18), we investigated how prestimulus periodic oscillations and aperiodic components influence the perception of the McGurk illusion on a trial-by-trial basis. Using logistic mixed-effect models, we determined the topology of spectral markers that predict the brain response to illusory perception. We found lower levels of alpha (8-12 Hz) and beta (15-30 Hz) band oscillations over parieto-occipital sensors, lower aperiodic offset values over parietal-temporal sensors, and a lower global effect of exponent over the scalp that predicted the response to McGurk illusion. We conclude that the predominant source of variations in the prestimulus oscillatory state is manifested by aperiodic background activity and that variations in these oscillations and aperiodic activity, account for inter-trial and inter-individual variability in perception of the McGurk illusion.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neuroscience; Perception; Predictive Processing; Sensory Processing; Electroencephalography (EEG)"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1dm5c4zc",
            "frozenauthors": [
                {
                    "first_name": "Vinsea A V",
                    "middle_name": "",
                    "last_name": "Singh",
                    "name_suffix": "",
                    "institution": "National Brain Research Centre",
                    "department": ""
                },
                {
                    "first_name": "Vinodh G.",
                    "middle_name": "",
                    "last_name": "Kumar",
                    "name_suffix": "",
                    "institution": "Penn State College of Medicine",
                    "department": ""
                },
                {
                    "first_name": "Dr. Arpan",
                    "middle_name": "",
                    "last_name": "Banerjee",
                    "name_suffix": "",
                    "institution": "National Brain Research Centre (NBRC)",
                    "department": ""
                },
                {
                    "first_name": "Dr. Dipanjan",
                    "middle_name": "",
                    "last_name": "Roy",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Jodhpur",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24672/galley/18081/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24672/galley/21467/download/"
                }
            ]
        },
        {
            "pk": 24083,
            "title": "Priming Abstract Modal Representations in Modals with Causatives",
            "subtitle": null,
            "abstract": "Semanticists have debated the extent to which modality and causation are related in natural language. This paper aims to promote a theory in which overt causatives share core components of meaning with deontic modals. We report a sentence recall experiment that suggests that priming can be used to target the high-level semantic representations shared between two syntactically distinct linguistic expressions. Our results show that it's possible to prime the production of the deontic modal 'had to' (e.g., ``George 'had to' go to the store\"), with causative 'made' (e.g., ``Jane 'made' George go to the store''), suggesting that the two expressions share a component of their meaning. Our results contribute to the methodological development in experimental semantics by establishing the utility of the priming effect to target meaning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language Production; Memory; Representation; Semantics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7wv8j75t",
            "frozenauthors": [
                {
                    "first_name": "Angelica",
                    "middle_name": "",
                    "last_name": "Hill",
                    "name_suffix": "",
                    "institution": "University of Massachusetts Amherst",
                    "department": ""
                },
                {
                    "first_name": "Shota",
                    "middle_name": "",
                    "last_name": "Momma",
                    "name_suffix": "",
                    "institution": "University of Massachusetts Amherst",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24083/galley/13677/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24083/galley/21468/download/"
                }
            ]
        },
        {
            "pk": 24510,
            "title": "Prior Knowledge Adaptation Through Item-Removal in Adaptive Learning Increases Short- and Long-Term Learning Benefits",
            "subtitle": null,
            "abstract": "In personalized-schedule learning, previous research has shown the benefit of initial attempted retrieval of study-items on short-term retention and later test performance. As a way of prior-knowledge identification, initial attempted retrieval may help to optimize learning and long-term performance further, through the removal (or ‘drop') of items from the learning set that are answered correctly on the first attempt. This study sought to support this hypothesis through a real-world, within-subjects experiment, comparing vocabulary test performance of Dutch middle school students after the use of a drop- and non-drop adaptive learning algorithm. The results show that short- and long-term item retention was higher for material studied using the drop-algorithm, while dropping items did not lead to worse retention compared to items that were kept upon initial correct responses. This suggests that initially-known items are correctly identified as ‘mastered', and that their removal from the learning material allows students to focus their efforts on unknown items, leading to increased learning gains.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Skill acquisition and learning; Classroom studies; Knowledge representation"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1jh7z8tp",
            "frozenauthors": [
                {
                    "first_name": "Malte",
                    "middle_name": "",
                    "last_name": "Krambeer",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Maarten",
                    "middle_name": "",
                    "last_name": "van der Velde",
                    "name_suffix": "",
                    "institution": "MemoryLab",
                    "department": ""
                },
                {
                    "first_name": "Hedderik",
                    "middle_name": "",
                    "last_name": "van Rijn",
                    "name_suffix": "",
                    "institution": "SlimStampen BV",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24510/galley/21469/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24510/galley/14107/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24510/galley/21469/download/"
                }
            ]
        },
        {
            "pk": 24218,
            "title": "Probabilistic and Selectional Biases in Ambiguity Resolution during Real-time Sentence Processing",
            "subtitle": null,
            "abstract": "This study examines the influence of lexical frequency bias and\nselectional constraints on the resolution of complement\nambiguity during sentence processing. Some argue that in\ncomplement ambiguity resolution, lexical frequency bias and\nselectional constraints lead to the clausal complement before\ndisambiguation, while others claim that the nominal\ncomplement is maintained until the disambiguating verb\nappears. The present study investigates this issue in two\nreading experiments using a temporal adjunct. The results\nsuggested the rapid influence of lexical frequency bias and\nselectional constraints. However, the temporal adjunct\nintroduces a bias towards the nominal complement, and\nultimately overrides the influence of the lexical frequency bias\nand selectional constraints. These results suggest that\nprocessing preferences dynamically change, influenced by\nmultiple biases.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language understanding; Reading"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/96v0p8ns",
            "frozenauthors": [
                {
                    "first_name": "Hiroki",
                    "middle_name": "",
                    "last_name": "Fujita",
                    "name_suffix": "",
                    "institution": "University of Potsdam",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24218/galley/13814/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24218/galley/21470/download/"
                }
            ]
        },
        {
            "pk": 21605,
            "title": "Probabilistic simulation supports generalizable intuitive physics",
            "subtitle": null,
            "abstract": "How do people perform general-purpose physical reasoning across a variety of scenarios in everyday life? Across two studies with seven different physical scenarios, we asked participants to predict whether or where two objects will make contact. People achieved high accuracy and were highly consistent with each other in their predictions. We hypothesize that this robust generalization is a consequence of mental simulations of noisy physics. We designed an \"intuitive physics engine'' model to capture this generalizable simulation. We find that this model generalized in human-like ways to unseen stimuli and to a different query of predictions. We evaluated several state-of-the-art deep learning and scene feature models on the same task and found that they could not explain human predictions as well. This study provides evidence that human's robust generalization in physics predictions are supported by a probabilistic simulation model, and suggests the need for structure in learned dynamics models.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Reasoning; Representation; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/93j3f86q",
            "frozenauthors": [
                {
                    "first_name": "Haoliang",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Khaled",
                    "middle_name": "",
                    "last_name": "Jedoui",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Rahul",
                    "middle_name": "",
                    "last_name": "Venkatesh",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Felix",
                    "middle_name": "Jedidja",
                    "last_name": "Binder",
                    "name_suffix": "",
                    "institution": "UC San Diego",
                    "department": ""
                },
                {
                    "first_name": "Josh",
                    "middle_name": "",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Judith",
                    "middle_name": "E.",
                    "last_name": "Fan",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Yamins",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "A",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21605/galley/11204/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21605/galley/21998/download/"
                }
            ]
        },
        {
            "pk": 21589,
            "title": "Probability, but not utility, influences repeated mental simulations of risky events",
            "subtitle": null,
            "abstract": "There has been considerable interest exploring how the utility of an outcome impacts the probability with which it is mentally simulated. Earlier studies using varying methodologies have yielded divergent conclusions with different directions of the influence. To directly examine such mental process, we employed a random generation paradigm in which all the outcomes were either equally (i.e., followed a uniform distribution) or unequally (i.e., a binomial distribution) probable. While our results revealed individual differences in how the utility influenced responses, the overall findings suggested that it is the outcomes' probabilities, not their utilities, that guide this process. Notably, an initial utility-independent bias emerged, with individuals displaying a tendency to start with smaller values when all outcomes are equally likely. Our findings offer insights into the benefits of studying the mental sampling processes and provide empirical support for particular sampling models in this domain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Verbal protocol studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2ps2t4sz",
            "frozenauthors": [
                {
                    "first_name": "Yun-Xiao",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Johanna",
                    "middle_name": "",
                    "last_name": "Falben",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Lucas",
                    "middle_name": "",
                    "last_name": "Castillo",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Jake",
                    "middle_name": "",
                    "last_name": "Spicer",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Jian-Qiao",
                    "middle_name": "",
                    "last_name": "Zhu",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Nick",
                    "middle_name": "",
                    "last_name": "Chater",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Sanborn",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21589/galley/11188/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21589/galley/21982/download/"
                }
            ]
        },
        {
            "pk": 24806,
            "title": "Probability Learning and Repeated Choice in Childhood: A Longitudinal Study",
            "subtitle": null,
            "abstract": "What is the developmental trajectory of probability learning in early childhood, and how do changes in choice behavior relate to changes in executive functions? We conducted a two-year longitudinal study with children between the ages of 3.5 and 6.5 years and complemented behavioral analyses with computational modeling to illuminate underlying cognitive processes. On average, children became more likely to choose the high-probability option as they grew older and increasingly diversified choices in line with probability matching by T3. Moreover, younger children in the cohort were more likely to maximize probability than older children. Our analyses suggest that increasing choice diversification across childhood may relate to improving executive functions and value-based learning, whereas probability maximizing may serve as an easily implementable satisficing strategy. Finally, our findings emphasize how children's variability in choice behavior may affect the estimated direction of change and highlight the need for longitudinal research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Decision making; Development; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5m64f14w",
            "frozenauthors": [
                {
                    "first_name": "Anna",
                    "middle_name": "Isabel",
                    "last_name": "Thoma",
                    "name_suffix": "",
                    "institution": "Max-Planck-Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Christin",
                    "middle_name": "",
                    "last_name": "Schulze",
                    "name_suffix": "",
                    "institution": "UNSW",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24806/galley/21471/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24806/galley/14404/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24806/galley/18261/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24806/galley/21471/download/"
                }
            ]
        },
        {
            "pk": 21554,
            "title": "Probing Nonhuman Primate Errors on False Belief Tasks to Explore the Evolutionary Roots of Theory of Mind",
            "subtitle": null,
            "abstract": "Theory of Mind (ToM) is central to human social cognition, yet the roots of this capacity remain poorly understood. Both infants and nonhuman primates perform inconsistently on false belief tasks, limiting our understanding of the representations that characterize their ToM. Here, we seek to better understand this often-contradictory literature by dissecting these failures. Specifically, we focus on primates' characteristic null performance on false belief tasks. Across three studies, we find that—despite succeeding on a closely-matched control—rhesus monkeys fail to predict how agents with false beliefs will behave even when the agents perform highly unexpected, unlikely actions. We interpret this pattern of performance as evidence that monkeys have no representation of another agent's past awareness once the scene changes outside of that agent's view. This work moves beyond the success/failure dichotomy typically used to assess ToM, and instead gives a more precise characterization of primates' signature limits in ToM.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Animal cognition; Theory of Mind; Comparative Studies"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/43h3z261",
            "frozenauthors": [
                {
                    "first_name": "Amanda",
                    "middle_name": "L",
                    "last_name": "Royka",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "J.",
                    "last_name": "Horschler",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Walker",
                    "middle_name": "",
                    "last_name": "Bargmann",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Laurie",
                    "middle_name": "",
                    "last_name": "Santos",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21554/galley/11153/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21554/galley/14630/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21554/galley/21472/download/"
                }
            ]
        },
        {
            "pk": 24236,
            "title": "Procedural and Declarative Category Learning Simultaneously Contribute to Downstream Processes",
            "subtitle": null,
            "abstract": "Studies on interactions between procedural and declarative learning have focused on largely on competition during encoding, consolidation, or use (retrieval). Less attention has been paid to interactions between the representations created by each system. In a behavioral study, we demonstrated that information from both declarative and procedural learning can contribute to response selection. Participants were instructed to use a completely diagnostic, verbalizable, shape-based rule to categorize exemplars and received feedback after each trial. However, the categories also differed probabilistically in their color distributions. Participants used both color (learned procedurally) and shape (learned declaratively) to categorize exemplars, making faster responses when both sources indicated the same category judgement, and slower when they conflicted. Debriefing confirmed that most participants were unaware of the color distributions (aware participants were analyzed separately). This result suggests that both the color (procedural) and shape (declarative) information contributed to response selection.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Education; Learning; Memory; Skill acquisition and learning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8766k211",
            "frozenauthors": [
                {
                    "first_name": "Priya",
                    "middle_name": "B.",
                    "last_name": "Kalra",
                    "name_suffix": "",
                    "institution": "University of Western Ontario",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Batterink",
                    "name_suffix": "",
                    "institution": "University of Western Ontario",
                    "department": ""
                },
                {
                    "first_name": "John Paul",
                    "middle_name": "",
                    "last_name": "Minda",
                    "name_suffix": "",
                    "institution": "University of Western Ontario",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24236/galley/13832/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24236/galley/21473/download/"
                }
            ]
        },
        {
            "pk": 21363,
            "title": "Procedural Dilemma Generation for Moral Reasoning in Humans and Language Models",
            "subtitle": null,
            "abstract": "As AI systems like language models are increasingly integrated into decision-making processes affecting people's lives, it's critical to ensure that these systems have sound moral reasoning. To test whether they do, we need to develop systematic evaluations. We provide a framework that uses a language model to translate causal graphs that capture key aspects of moral dilemmas into prompt templates. With this framework, we procedurally generated a large and diverse set of moral dilemmas---the OffTheRails benchmark---consisting of 50 scenarios and 400 unique test items. We collected moral permissibility and intention judgments from human participants for a subset of our items and compared these judgments to those from two language models (GPT-4 and Claude-2) across eight conditions. We find that moral dilemmas in which the harm is a necessary means (as compared to a side effect) resulted in lower permissibility and higher intention ratings for both participants and language models. The same pattern was observed for evitable versus inevitable harmful outcomes. However, there was no clear effect of whether the harm resulted from an agent's action versus from having omitted to act. We discuss limitations of our prompt generation pipeline and opportunities for improving scenarios to increase the strength of experimental effects.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Psychology; Causal reasoning; Reasoning; Large Language Models"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/77r459kj",
            "frozenauthors": [
                {
                    "first_name": "Jan-Philipp",
                    "middle_name": "",
                    "last_name": "Fränken",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Kanishk",
                    "middle_name": "",
                    "last_name": "Gandhi",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Tori",
                    "middle_name": "",
                    "last_name": "Qiu",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Ayesha",
                    "middle_name": "",
                    "last_name": "Khawaja",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Noah",
                    "middle_name": "",
                    "last_name": "Goodman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Tobias",
                    "middle_name": "",
                    "last_name": "Gerstenberg",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21363/galley/10962/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21363/galley/21808/download/"
                }
            ]
        },
        {
            "pk": 24053,
            "title": "Processing non-culminating accomplishments across languages",
            "subtitle": null,
            "abstract": "We investigated the processing and interpretation of aspectual coercion in the case of non-culminating accomplishments in English and German. Two offline experiments employing an inference rating task showed that non-culminating accomplishments in both languages actually involve a shift in interpretation. Four self-paced reading experiments furthermore show that this type of coercion isn't costly - neither in German, a language lacking grammatical aspect, nor in English with an aspectual opposition between progressive and perfective forms. This lack of effect in processing coercion was obtained in a first pair of experiments using adverbial modification (sentence-internally) within the verb phrase and in a second pair of experiments in which aspectual coercion was triggered in a subsequent discourse unit. A final stops-making-sense experiment replicates the lack of effect for English and furthermore shows that the processing of non-culminating accomplishments does not incur a processing effect even in a task calling for immediate full interpretation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language understanding; Pragmatics; Reading; Reasoning; Semantics; Cross-linguistic analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1mb5x4cc",
            "frozenauthors": [
                {
                    "first_name": "Oliver",
                    "middle_name": "",
                    "last_name": "Bott",
                    "name_suffix": "",
                    "institution": "Bielefeld University",
                    "department": ""
                },
                {
                    "first_name": "Torgrim",
                    "middle_name": "",
                    "last_name": "Solstad",
                    "name_suffix": "",
                    "institution": "Bielefeld University",
                    "department": ""
                },
                {
                    "first_name": "Jens",
                    "middle_name": "",
                    "last_name": "Michaelis",
                    "name_suffix": "",
                    "institution": "Bielefeld University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24053/galley/13647/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24053/galley/21475/download/"
                }
            ]
        },
        {
            "pk": 24422,
            "title": "Processing of Relative Clause Structural Ambiguity by Iranians' Japanese Learners - From the Perspective of the Effect of L1 and the Animacy of the Head Nouns on L2 Sentence Processing -",
            "subtitle": null,
            "abstract": "This study investigates the processing of structurally ambiguous relative clause (RC) constructions in Japanese by Persian-Japanese learners, examining the influence of their native language (L1) on second language (L2) processing. It challenges the universality of parsing strategies through a self-paced reading (SPR) task. The results indicate a preference for High Attachment (HA) and a stronger tendency towards NP-high when it's an animate noun, in both Persian and Japanese. Descriptive analyses further revealed a shift from Low Attachment (LA) to HA among native Japanese speakers, suggesting unforced revision. However, there was an absence of a clear animacy effect on their preference. These findings suggest parallel interactive mechanisms in sentence processing and the transfer of syntax and semantic information from L1 to L2. Moreover, the study underscores language-specific differences in sentence processing, emphasizing the impact of language dominance in cross-linguistic transfer and contributing to our understanding of bilingual sentence processing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language understanding; Natural Language Processing; Computer-based experiment; Cross-linguistic analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3nt3m9pm",
            "frozenauthors": [
                {
                    "first_name": "Faezeh",
                    "middle_name": "",
                    "last_name": "Zare",
                    "name_suffix": "",
                    "institution": "University of the Ryukyus",
                    "department": ""
                },
                {
                    "first_name": "Hideki",
                    "middle_name": "",
                    "last_name": "Goya",
                    "name_suffix": "",
                    "institution": "University of the Ryukyus",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24422/galley/14019/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24422/galley/21476/download/"
                }
            ]
        },
        {
            "pk": 24664,
            "title": "Processing of scene intrinsics in the ventral visual stream for object recognition",
            "subtitle": null,
            "abstract": "A hallmark of human vision is the ability to rapidly recognize objects in a complex naturalistic scene. However, the exact mechanisms behind the computational invariance of object recognition remain unknown. In this study, we investigate object constancy by estimating how the ventral visual stream processes shading, shadows, textures, and specularities. To accomplish this, we use object meshes from the Objaverse dataset to create distinct multiclass classification tasks. For every task, we render a dataset by excluding exactly one of the previously stated features at a time. Subsequently, we train a ResNet50 model on each dataset. The trained model is evaluated on Brain-Score; deviations in these metrics indicate the importance of a brain region in achieving invariance to a specific feature. A reduced score for a removed feature in a particular region implies its crucial role in processing that feature since the model classifies objects based on remaining scene intrinsics.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Computer Science; Behavioral Science; Decision making; Machine learning; Perception; Vision; Neural Networks"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9nj174x3",
            "frozenauthors": [
                {
                    "first_name": "Shreya",
                    "middle_name": "",
                    "last_name": "Kapoor",
                    "name_suffix": "",
                    "institution": "Friedrich-Alexander-Universität Erlangen-Nürnberg",
                    "department": ""
                },
                {
                    "first_name": "Bernhard",
                    "middle_name": "",
                    "last_name": "Egger",
                    "name_suffix": "",
                    "institution": "Friedrich-Alexander-Universität Erlangen-Nürnberg",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24664/galley/21477/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24664/galley/14262/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24664/galley/18063/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24664/galley/21477/download/"
                }
            ]
        },
        {
            "pk": 24571,
            "title": "Process Modelling for Digit Span Tasks: Attention, Working Memory, and Executive Functioning in Cancer Survivors",
            "subtitle": null,
            "abstract": "A considerable number of non-central nervous system (non-CNS) cancer survivors face long-term cognitive impairments after successful treatment, which affects various domains of cognition. Two tests used to measure working memory and attention are the digit span forward and digit span backwards, which were computerized to assess cognitive deficits in cancer survivors. \nWe aim to investigate which cognitive processes are impaired in cancer survivors, by separating the various processes measured in the digit span tests. To this end, we formulate a hierarchical Bayesian cognitive process model which uses raw input data from the digit span and identifies metrics of working memory capacity, attentional control, and executive control. \nWe compare these outcomes between non-CNS cancer survivors and healthy controls, to better localize which processes are affected by cancer and its treatment. Formal modeling allows for the extraction of more precise information in describing the cognitive deficits faced by patients.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Attention; Memory; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5b71f2sz",
            "frozenauthors": [
                {
                    "first_name": "Ruben",
                    "middle_name": "",
                    "last_name": "Potthoff",
                    "name_suffix": "",
                    "institution": "Netherlands Cancer Institute",
                    "department": ""
                },
                {
                    "first_name": "Sanne",
                    "middle_name": "",
                    "last_name": "Schagen",
                    "name_suffix": "",
                    "institution": "Netherlands Cancer Institute",
                    "department": ""
                },
                {
                    "first_name": "Joost",
                    "middle_name": "",
                    "last_name": "Agelink van Rentergem",
                    "name_suffix": "",
                    "institution": "Netherlands Cancer Institute",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24571/galley/21474/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24571/galley/14168/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24571/galley/21474/download/"
                }
            ]
        },
        {
            "pk": 24169,
            "title": "Production of Syntactic Alternations Displays Accessibility But Not Informativity Effects",
            "subtitle": null,
            "abstract": "This paper explores how speakers choose between two utterance alternatives with similar syntactic properties and distinct yet related meanings. We consider the interaction of two speaker pressures: to mention accessible lexical items early in the utterance and to mention informative content early in the utterance, the latter of which is explicitly predicted by an incremental Rational Speech Act (IRSA) model. In Exp. 1, we observed a significant effect of accessibility on utterance choice in an online spoken production task, which elicited descriptions of the relationship between two entities using a provided verb. We found that making entities more accessible via foregrounding led speakers to mention them earlier. In Exp. 2, an interactive production task, both informativity and foregrounding were manipulated. While IRSA predicts more informative content to be mentioned earlier in the sentence, we observed neither significant effects of informativity nor of accessibility. Consistent with recent work on Good-Enough theories of production, we conclude that even when two sentences are not entirely meaning-equivalent, production choices can be affected by lexical accessibility; the pressure to mention informative material early, however, should be investigated further",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language Production"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8vw801s0",
            "frozenauthors": [
                {
                    "first_name": "Emily",
                    "middle_name": "",
                    "last_name": "Goodwin",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Judith",
                    "middle_name": "",
                    "last_name": "Degen",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24169/galley/13765/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24169/galley/21478/download/"
                }
            ]
        },
        {
            "pk": 24180,
            "title": "Productivity and Creative Use of Compounds in Reduced Registers: Implications for Grammar Architecture",
            "subtitle": null,
            "abstract": "Reduced registers – search queries, print and TV ads, and navy messages – are characterized by an unusually high number of novel compounds. Results of a production study reported here reveal combinatorial patterns not attested in the standard language and allow us to establish the range of possibilities. We argue that productivity and creative use of compounds in reduced registers is not coincidental but follows directly from the grammar that generates expressions in these registers. We adopt an analysis couched in the Parallel Architecture framework (Jackendoff, 1997; Jackendoff & Audring, 2016) and demonstrate how productivity and idiosyncrasy of compounds in reduced registers can be explained.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Morphology; Semantics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1c39n81t",
            "frozenauthors": [
                {
                    "first_name": "Anastasia",
                    "middle_name": "",
                    "last_name": "Smirnova",
                    "name_suffix": "",
                    "institution": "San Francisco State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24180/galley/13776/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24180/galley/21479/download/"
                }
            ]
        },
        {
            "pk": 21661,
            "title": "Professional Jazz Musicians Explore and Exploit a Space of Sounds",
            "subtitle": null,
            "abstract": "Collective improvisation is remarkable. When people\nimprovise—whether dancing, making music, or conversing—\nthey coordinate their behavior while exploring abstract spaces\nof movements, sounds, and ideas. How do improvisers navigate\nthese abstract spaces? One possibility is that improvisation\nbuilds on foraging strategies used to search the physical\nworld. Here, we investigate the dynamics of an especially\ncomplex and abstract form of collective improvisation: free\njazz. We quantify how professional jazz ensembles navigate\na space of sounds and show that it resembles a foraging strategy\nknown as Area Restricted Search. In particular, ensembles\nchange their playing dynamics in response to encounters with\nnovel ‘soundworlds.' Before encountering a new soundworld,\nensembles engage in widespread exploration; immediately after,\nthey shift to focused exploitation of the new sound. While\ncollective improvisation pushes at our cognitive limits and is a\nparadigm of human creativity, it may build on evolutionarilyancient\nstrategies for searching space.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; Creativity; Group Behaviour; Music; Corpus studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/72b6c674",
            "frozenauthors": [
                {
                    "first_name": "Tevin",
                    "middle_name": "",
                    "last_name": "Williams",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                },
                {
                    "first_name": "Matthew",
                    "middle_name": "",
                    "last_name": "Setzler",
                    "name_suffix": "",
                    "institution": "Meta",
                    "department": ""
                },
                {
                    "first_name": "Minje",
                    "middle_name": "",
                    "last_name": "Kim",
                    "name_suffix": "",
                    "institution": "University of Illinois Urbana-Champaign",
                    "department": ""
                },
                {
                    "first_name": "Rachel",
                    "middle_name": "",
                    "last_name": "Ryskin",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Spivey",
                    "name_suffix": "",
                    "institution": "UC Merced",
                    "department": ""
                },
                {
                    "first_name": "Tyler",
                    "middle_name": "",
                    "last_name": "Marghetis",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21661/galley/11260/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21661/galley/14569/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21661/galley/22037/download/"
                }
            ]
        },
        {
            "pk": 21439,
            "title": "Program-Based Strategy Induction for Reinforcement Learning",
            "subtitle": null,
            "abstract": "Typical models of learning assume incremental estimation of continuously-varying decision variables like expected rewards.  However, this class of models fails to capture more idiosyncratic, discrete heuristics and strategies that people and animals appear to exhibit.  Despite recent advances in strategy discovery using tools like recurrent networks that generalize the classic models, the resulting strategies are often onerous to interpret, making connections to cognition difficult to establish.  We use Bayesian program induction to discover strategies implemented by programs, letting the simplicity of strategies trade off against their effectiveness.  Focusing on bandit tasks, we find strategies that are difficult or unexpected with classical incremental learning, like asymmetric learning from rewarded and unrewarded trials, adaptive horizon-dependent random exploration, and discrete state switching.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Learning; Bayesian modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6qh3f4fn",
            "frozenauthors": [
                {
                    "first_name": "Carlos",
                    "middle_name": "G.",
                    "last_name": "Correa",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Nathaniel",
                    "middle_name": "",
                    "last_name": "Daw",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21439/galley/11038/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21439/galley/21884/download/"
                }
            ]
        },
        {
            "pk": 24230,
            "title": "Prompting invokes expert-like downward shifts in GPT-4V's conceptual hierarchies",
            "subtitle": null,
            "abstract": "Humans tend to privilege an intermediate level of categorization, known as the basic level, when categorizing objects that exist in a conceptual hierarchy (e.g. choosing to call a Labrador a dog instead of Labrador or animal). Domain experts demonstrate a downward shift in their object categorization behaviour, recruiting subordinate levels in a conceptual hierarchy as readily as conventionally basic categories (Tanaka & Philibert, 2022; Tanaka & Taylor, 1991). Do multimodal large language models show similar behavioural changes when prompted to behave in an expert-like way? We test whether GPT-4 with Vision (GPT-4V, OpenAI, 2023a) and LLaVA (Liu, Li, Wu, & Lee, 2023; Liu, Li, Li, & Lee, 2023) demonstrate downward shifts using an object naming task and eliciting expert-like personas by altering the model's system prompt. We find evidence of downward shifts in GPT-4V when expert system prompts are used, suggesting that human expert-like behaviour can be elicited from GPT-4V using prompting, but find no evidence of downward shift in LLaVA. We also find that there is an unpredicted upward shift in areas of non-expertise in some cases. These findings suggest that in the default case, GPT-4V is not a novice: instead, it behaves at default with a median level of expertise, while further expertise can be primed or forgotten through textual prompts. These results open the door for GPT-4V and similar models to be used as tools for studying differences in the behaviour of experts and novices, and even comparing contrasting levels of expertise within the same large language model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Linguistics; Psychology; Concepts and categories; Large Language Models"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5b132892",
            "frozenauthors": [
                {
                    "first_name": "Cara Su-Yi",
                    "middle_name": "",
                    "last_name": "Leong",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24230/galley/13826/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24230/galley/21480/download/"
                }
            ]
        },
        {
            "pk": 24808,
            "title": "Properties and predictiveness of affective prediction errors",
            "subtitle": null,
            "abstract": "Do verbally reported feelings follow reinforcement learning principles? Prediction errors—differences between expectations and outcomes—are key in models of learning across humans, animals, and machines. Historically, the emphasis has been on outcomes in the environment (e.g., money or food), focusing relatively less on the fact that humans can also report correspondingly expected and experienced affect (i.e., feelings). Recent research suggests that expected and experienced affect, including prediction errors, can explain behavior beyond outcomes in the environment alone. However, the properties of affective prediction errors underlying this explanatory power are unknown. We address this gap across two studies. We show that affective prediction errors can decrease over time, but that the decrease depends on introspection (Study 1). We then replicate this finding while additionally documenting transfer effects across tasks (Study 2). Crucially, decreases in affective prediction errors generally occurred independent of changes in behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Decision making; Emotion; Learning; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6zs3b38h",
            "frozenauthors": [
                {
                    "first_name": "Marius",
                    "middle_name": "C",
                    "last_name": "Vollberg",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24808/galley/14406/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24808/galley/18263/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24808/galley/21481/download/"
                }
            ]
        },
        {
            "pk": 21647,
            "title": "Prosocial Acts Towards AI Shaped By Reciprocation And Awareness",
            "subtitle": null,
            "abstract": "The proliferation of artificial intelligence (AI) agents has introduced a new dynamic into the human social environment. This study investigates prosocial behavior in a hybrid human-AI setting, particularly within a gaming environment. Many existing studies on prosocial behavior are conducted in economic game settings in which the agents' intentions, and whether or not prosocial actions offer benefits, are explicit. This project explores prosocial interactions in spatial environments where the need for help by another agent might not be immediately obvious, and where cognitive processes such as attention, and decision-making processes about the cost of helping are thus likely to play a role. In a baseline study (N = 177), we investigated the likelihood of human agents reciprocating prosocial behavior initiated by an AI player. Results indicated that the low saliency of the AI player's actions was a primary reason for non-reciprocation. A follow-up study (N = 164) tested whether increasing the salience of the AI's actions would enhance human prosocial responses. We found support for our hypothesis from analysis of the time-series data and participants' self-reported post-game questionnaires. This research contributes to the growing field of human-AI cooperation, outlining a vision for a future where technology actively contributes to our collective well-being, and opening up new possibilities for positive transformation in a world increasingly populated by intelligent machines.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision making; Human-computer interaction; Intelligent agents; Interactive behavior; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/14q5z5bv",
            "frozenauthors": [
                {
                    "first_name": "Xinyue",
                    "middle_name": "",
                    "last_name": "Hu",
                    "name_suffix": "",
                    "institution": "University of California, Irvine",
                    "department": ""
                },
                {
                    "first_name": "Kumar",
                    "middle_name": "",
                    "last_name": "Akash",
                    "name_suffix": "",
                    "institution": "Honda Research Institute USA, Inc.",
                    "department": ""
                },
                {
                    "first_name": "Shashank",
                    "middle_name": "",
                    "last_name": "Mehrotra",
                    "name_suffix": "",
                    "institution": "Honda Research Institute USA, Inc.",
                    "department": ""
                },
                {
                    "first_name": "Teruhisa",
                    "middle_name": "",
                    "last_name": "Misu",
                    "name_suffix": "",
                    "institution": "Honda Research Institute USA, Inc.",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Steyvers",
                    "name_suffix": "",
                    "institution": "University of California, Irvine",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21647/galley/11246/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21647/galley/14555/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21647/galley/22038/download/"
                }
            ]
        },
        {
            "pk": 21460,
            "title": "Publish or Perish: Simulating the Impact of Publication Policies on Science",
            "subtitle": null,
            "abstract": "Science can be viewed as a collective, epistemic endeavor. However, a variety of factors- such as the publish-or-perish culture, institutional incentives, and publishers who favor novel and positive findings- may challenge the ability of science to accurately aggregate information about the world. Evidence of the shortcomings in the current structure of science can be seen in the replication crisis that faces psychology and other disciplines. We analyze scientific publishing through the lens of cultural evolution, framing the scientific process as a multi-generational interplay between scientists and publishers in a multi-armed bandit setting. We examine the dynamics of this model through simulations, exploring the effect that different publication policies have on the accuracy of the published scientific record. Our findings highlight the need for replications and caution against behaviors that prioritize factors uncorrelated with result accuracy.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Interactive behavior; Agent-based Modeling; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9cb0b1pw",
            "frozenauthors": [
                {
                    "first_name": "Marina",
                    "middle_name": "",
                    "last_name": "Mancoridis",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Ted",
                    "middle_name": "",
                    "last_name": "Sumers",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21460/galley/11059/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21460/galley/21905/download/"
                }
            ]
        },
        {
            "pk": 24770,
            "title": "Pupil dynamics open eyes to links between word learning and interest",
            "subtitle": null,
            "abstract": "Infant word learning is a crucial process that is of great importance to early development. Indeed, delays in early word learning are linked to poor language and educational outcomes, including Developmental Language Disorder (DLD). However infant word learning is highly variable, and the correlates of successful and delayed early word learning are not well understood. Here, we examine the role of individual temperament in word learning, examining the dynamic interplay between category interest, general curiosity, willingness to engage, and motivated word learning in a novel word learning task, using changes in infant pupil diameter as the measurement. Preliminary data suggests category interest to be of key import to early word learning, supporting previous findings from Ackermann et al (2020). We also find differences in personality contribute to word learning, suggesting that the variability in infant word learning might be related to individual differences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Language development; Language learning; Eye tracking"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1p0576nx",
            "frozenauthors": [
                {
                    "first_name": "Samuel",
                    "middle_name": "",
                    "last_name": "Forbes",
                    "name_suffix": "",
                    "institution": "Durham University",
                    "department": ""
                },
                {
                    "first_name": "Lucy",
                    "middle_name": "Elizabeth",
                    "last_name": "Edgar",
                    "name_suffix": "",
                    "institution": "Durham University",
                    "department": ""
                },
                {
                    "first_name": "Shuai",
                    "middle_name": "",
                    "last_name": "Shao",
                    "name_suffix": "",
                    "institution": "Bard College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24770/galley/21482/download/"
            },
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24770/galley/14368/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24770/galley/18225/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24770/galley/21482/download/"
                }
            ]
        },
        {
            "pk": 24748,
            "title": "Pupil dynamics preceding switches in task engagement",
            "subtitle": null,
            "abstract": "When completing a task for a prolonged period, our ability to sustain attention fluctuates over time. Accordingly, in mice, disengaged behaviour has temporal autocorrelation (i.e., ‘disengagement states'), with lapses clustering in time, rather than occurring randomly. In this disengaged state, mice make more errors and provide responses biased towards one side. What neural and physiological processes trigger the transition into, and out of, disengagement states? Here, we investigated the role of pupil-linked arousal. We used a public dataset of 140 mice performing a perceptual decision-making task, including extracellular recordings alongside behavioural and pupil responses. We applied hidden Markov models to identify engagement states based on response times. Preliminary results show that disengaged trials are associated with larger and more variable baseline pupil, and suggest that pupil size changes precede state transitions. These findings will provide a starting point for exploring the cortical, subcortical and neuromodulatory processes preceding task (dis)engagement.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neuroscience; Animal cognition; Decision making; Computational Modeling; Eye tracking"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5658c14m",
            "frozenauthors": [
                {
                    "first_name": "Philippa",
                    "middle_name": "A",
                    "last_name": "Johnson",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                },
                {
                    "first_name": "Sander",
                    "middle_name": "",
                    "last_name": "Nieuwenhuis",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                },
                {
                    "first_name": "Anne",
                    "middle_name": "",
                    "last_name": "Urai",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24748/galley/21483/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24748/galley/14346/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24748/galley/18204/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24748/galley/21483/download/"
                }
            ]
        },
        {
            "pk": 21541,
            "title": "Pupil size reflects the relevance of reward prediction error and estimation uncertainty in upcoming choice",
            "subtitle": null,
            "abstract": "How humans process and utilize experienced outcomes and actions to adapt to a constantly evolving and noisy world is an important area of research. We investigate the role of the pupil-linked arousal system in adaptive value-based decision-making in an uncertain and changing environment using a two-armed bandit task with occasional changes in reward contingencies. We find that pupil size fluctuation encodes reward- and uncertainty-related values across trials; moreover, pupil size reflects future-choice-dependent contributions of these variables to learning and decision-making: larger pupil encoding of reward prediction error (RPE) promotes reward-driven switches in choice, while larger pupil encodings of estimation uncertainty (EU) promotes uncertainty-driven switches in choice. Furthermore, individual differences in pupil's encoding of RPE and EU correlate with individual variabilities in choice bias and task performance. Given the relationship of pupil size to noradrenergic and cholinergic modulations, these results provide insights into the computational and neural process underlying adaptive decision-making.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Decision making; Learning; Bayesian modeling; Eye tracking"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9cr3j67v",
            "frozenauthors": [
                {
                    "first_name": "Zoe",
                    "middle_name": "W",
                    "last_name": "He",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Maëva",
                    "middle_name": "",
                    "last_name": "L'Hôtellier",
                    "name_suffix": "",
                    "institution": "CEA Paris-Saclay, Gif-sur-Yvette, France Université de Paris",
                    "department": ""
                },
                {
                    "first_name": "Alexander",
                    "middle_name": "",
                    "last_name": "Paunov",
                    "name_suffix": "",
                    "institution": "CEA Paris-Saclay, Gif-sur-Yvette, France Université de Paris",
                    "department": ""
                },
                {
                    "first_name": "Dalin",
                    "middle_name": "",
                    "last_name": "Guo",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Florent",
                    "middle_name": "",
                    "last_name": "Meyniel",
                    "name_suffix": "",
                    "institution": "CEA Paris-Saclay, Gif-sur-Yvette, France Université de Paris",
                    "department": ""
                },
                {
                    "first_name": "Angela J",
                    "middle_name": "",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "Technical University of Darmstadt",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21541/galley/11140/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21541/galley/14617/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21541/galley/21484/download/"
                }
            ]
        },
        {
            "pk": 24644,
            "title": "Quantifying Culture: an Information-Theoretic Measure of how Memes Flow Through Minds",
            "subtitle": null,
            "abstract": "Cultural evolution is changing humanity much faster than genetic evolution, but at present we lack a way to empirically ground models of cultural evolution in a quantitative, content-agnostic way analogous to counting alleles in models of genetic evolution. A way to measure what information ends up in which minds would permit quantitative models of the many different processes that govern the flow of memes through minds. We offer a method for estimating the amount of information retained based on previous exposure to a cultural artifact. Entropy estimates that are generated based on a test set from e.g. Harry Potter will differ between a treatment group (Readers, people who have read Harry Potter), and a control group (Non-Readers). This difference is an expression, in bits, of how much information from the book stored in Readers' minds and therefore capable of influencing behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Anthropology; Linguistics; Psychology; Behavioral Science; Culture; Evolution; Language and thought; Memory; Computer-based experiment"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/20r0h350",
            "frozenauthors": [
                {
                    "first_name": "Matthew",
                    "middle_name": "",
                    "last_name": "Cashman",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Damian",
                    "middle_name": "E",
                    "last_name": "Blasi",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24644/galley/21485/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24644/galley/14241/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24644/galley/18028/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24644/galley/21485/download/"
                }
            ]
        },
        {
            "pk": 24321,
            "title": "Questioning Two Common Assumptions concerning Group Agency and Group Cognition",
            "subtitle": null,
            "abstract": "In this paper, we identify two common assumptions underlying popular accounts of group agency. The first assumption is that paradigmatic cases of agency are to be identified with individual organisms, typically human beings. The second assumption is that cognition requires the manipulation of mental representations. Combining these two assumptions generates the status quo account of group agency, namely that a group's agency ontologically depends upon the mental representations of the individuals that constitute the group. We provide a taxonomy of views about group agency along two axes, each corresponding to the extent to which the view endorses (or rejects) one of these two common assumptions. We believe that none of the standard conceptions of group cognition and agency reject both of these two assumptions. After developing brief arguments against both assumptions, we provide a brief sketch of what an account of group agency that rejects both assumptions might look like.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Distributed cognition; Group Behaviour; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7gp5895b",
            "frozenauthors": [
                {
                    "first_name": "Zachary",
                    "middle_name": "",
                    "last_name": "Peck",
                    "name_suffix": "",
                    "institution": "University of Cincinnati",
                    "department": ""
                },
                {
                    "first_name": "Anthony",
                    "middle_name": "",
                    "last_name": "Chemero",
                    "name_suffix": "",
                    "institution": "University of Cincinnati",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24321/galley/13917/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24321/galley/21486/download/"
                }
            ]
        },
        {
            "pk": 21617,
            "title": "Quick and Accurate Affordance Learning",
            "subtitle": null,
            "abstract": "Infants learn actively in their environments, shaping their own learning curricula. They learn about their environments' affordances, that is, how local circumstances determine how their behavior can affect the environment. Here we model this type of behavior by means of a deep learning architecture. The architecture mediates between global cognitive map exploration and local affordance learning. Inference processes actively move the simulated agent towards regions where they expect affordance-related knowledge gain. We contrast three measures of uncertainty to guide this exploration: predicted uncertainty of a model, standard deviation between the means of several models (SD), and the Jensen-Shannon Divergence (JSD) between several models. We show that the first measure gets fooled by aleatoric uncertainty inherent in the envi- ronment, while the two other measures focus learning on epistemic uncertainty. JSD exhibits the most balanced exploration strategy. From a computational perspective, our model suggests three key ingredients for coordinating the active generation of learning curricula: (1) Navigation behavior needs to be coordinated with local motor behavior for enabling active affordance learning. (2) Affordances need to be encoded locally for acquiring generalized knowledge. (3) Effective active affordance learning mechanisms should use density comparison techniques for estimating expected knowledge gain. Future work may seek collaborations with developmental psychology to model active play in children in more realistic scenarios.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Learning; Motor control; Spatial cognition; Computational Modeling; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/21b6p6tt",
            "frozenauthors": [
                {
                    "first_name": "Fedor",
                    "middle_name": "",
                    "last_name": "Scholz",
                    "name_suffix": "",
                    "institution": "University of Tübingen",
                    "department": ""
                },
                {
                    "first_name": "Erik",
                    "middle_name": "",
                    "last_name": "Ayari",
                    "name_suffix": "",
                    "institution": "University of Tübingen",
                    "department": ""
                },
                {
                    "first_name": "Johannes",
                    "middle_name": "",
                    "last_name": "Bertram",
                    "name_suffix": "",
                    "institution": "University of Tübingen",
                    "department": ""
                },
                {
                    "first_name": "Martin",
                    "middle_name": "V.",
                    "last_name": "Butz",
                    "name_suffix": "",
                    "institution": "University of Tübingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21617/galley/11216/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21617/galley/14525/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21617/galley/22039/download/"
                }
            ]
        },
        {
            "pk": 24374,
            "title": "Quicker, extremer: a computational modeling of reaction time and rating in social evaluation of faces",
            "subtitle": null,
            "abstract": "When individuals are pressed to make decisions quickly, their accuracy tends to decline, which is termed as speed-accuracy trade-off. But does this phenomenon extend to perceptual rating? In other words, do rapid judgments result in more extreme outcomes? To address this question, the study analyzed a global dataset covering 11,481 adult participants' ratings of 120 targets across 45 countries. The hypothesis posited that the rating became more extreme if it took less time. The study firstly identified response time as a significant predictor in extremity of social judgments through a machine learning algorithm, XGBoost, with cultural variables emerging as the second most important predictor. Given the importance of response time, the study employed hierarchical general linear models to investigate whether faster decision-making correlates with more extreme ratings and how this effect varies across diverse cultural contexts. The findings revealed a significant global level effect, also showing considerable variance across eleven regions. This observed phenomenon is termed as the “speed-extremity trade-off,” and is strongest in the Middle East and weakest in East Southeast Asia and Scandinavia.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Face Processing; Perception; Big data"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6j03d5rd",
            "frozenauthors": [
                {
                    "first_name": "Nan",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "the Chinese University of Hong Kong",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24374/galley/13971/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24374/galley/21487/download/"
                }
            ]
        },
        {
            "pk": 24711,
            "title": "Randomly Generating Stereotypes: Can We Understand Implicit Attitudes with Random Generation?",
            "subtitle": null,
            "abstract": "Societal expectations have been found to determine which social roles (e.g., jobs) people should occupy. Previously, however, these beliefs have been mainly explored using implicit measures such as sequential priming tasks where responding to expected (vs. conflicting) information is facilitated. We applied a random generation paradigm where participants said aloud the first names of hypothetical people working in various professions. This revealed that more female (male) first names were uttered for the female-typical (male-typical) occupations reflecting the societal gender stereotypes and the environmental statistics. Furthermore, the proportion of female and male names generated for each profession predicted participants' performance in a sequential priming task (prime = professions from random generation task, target = female vs. male face) better than the environmental statistics or participants' explicit gender ratio estimates of these jobs. Collectively, these findings offer a new method for exploring the internal representations elicited by cultural expectations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Social cognition"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3pp5k07f",
            "frozenauthors": [
                {
                    "first_name": "Johanna",
                    "middle_name": "",
                    "last_name": "Falben",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Lucas",
                    "middle_name": "",
                    "last_name": "Castillo",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Pablo",
                    "middle_name": "",
                    "last_name": "Leon Villagra",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Nick",
                    "middle_name": "",
                    "last_name": "Chater",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Sanborn",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24711/galley/21488/download/"
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24711/galley/14309/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24711/galley/18156/download/"
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24711/galley/21488/download/"
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            ]
        },
        {
            "pk": 21580,
            "title": "Random Replaying Consolidated Knowledge in the Continual Learning Model",
            "subtitle": null,
            "abstract": "A continual learning (CL) model is designed to solve the catastrophic forgetting problem, which damages the performance of neural networks by overwriting previous knowledge with new knowledge. The fundamental cause of this problem is that previous data is not available when training new data in the CL setting. The memory-based CL methods leverage a memory buffer to address this problem by storing a limited subset of previous data for replay, and most methods of this type adopt random storage and replay strategies. In the human brain, the hippocampus replays consolidated knowledge from the neocortex in a random manner, e.g., random dreaming. Inspired by this memory mechanism, we propose a memory-based method, which replays more consolidated memory data while maintaining the randomness. Our work highlights that random replaying is important for the CL model, which confirms the effectiveness of random dreaming in the human brain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Machine learning; Memory; Experience sampling; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4959j9q6",
            "frozenauthors": [
                {
                    "first_name": "Guanglu",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "Dalian University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Xinyue",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "Dalian University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Wenxin",
                    "middle_name": "",
                    "last_name": "Liang",
                    "name_suffix": "",
                    "institution": "Dalian University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Linlin",
                    "middle_name": "",
                    "last_name": "Zong",
                    "name_suffix": "",
                    "institution": "Dalian University of Technology",
                    "department": ""
                },
                {
                    "first_name": "XianChao",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Dalian University of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21580/galley/11179/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21580/galley/21973/download/"
                }
            ]
        },
        {
            "pk": 24191,
            "title": "Rapid parallel processing dynamics during hierarchical category decisions",
            "subtitle": null,
            "abstract": "Objects in the world are represented at multiple hierarchical levels of abstraction. For example, you can identify a four-legged creature as an animal, or a dog, or specifically as a Cocker Spaniel. While there has been extensive work examining the relationships between hierarchical category levels, it is unclear how such representations interact during categorization. That is, do individuals process category levels serially or are category levels processed in parallel during categorization? Here, we had participants learn categorization rules for four categories of novel creatures. We examined patterns of errors that participants made in a forced response task, where we manipulated the amount of time participants had to make responses on a trial-by-trial basis. Our results indicate that participants process category levels in parallel, rather than serially resolving superordinate levels before subordinate levels. Parallel processing of category levels could underpin the remarkable flexibility with which we access and deploy category information.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Decision making; Representation"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4qg1g2g4",
            "frozenauthors": [
                {
                    "first_name": "Juliana",
                    "middle_name": "E.",
                    "last_name": "Trach",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Samuel",
                    "middle_name": "David",
                    "last_name": "McDougle",
                    "name_suffix": "",
                    "institution": "Yale Univeristy",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24191/galley/13787/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24191/galley/21489/download/"
                }
            ]
        },
        {
            "pk": 21322,
            "title": "Rapprochement, not Detente: How Cognitive Science and Industry can get back to getting along, and make each other better along the way",
            "subtitle": null,
            "abstract": "We have a simple thesis: the relationship between academic and industry-based cognitive science is broken, but can be fixed. Over the last few decades, there has been a huge increase in the representation of cognitive science in industry. Beyond just machine learning, businesses are increasingly interested in human behavior and cognitive processes. Large proportions of our Ph.D. students, post-docs, and even faculty choose to go through a largely one-way door to corporate jobs in data science, behavioral experimentation, machine learning, user experience, and elsewhere. Currently, people who choose industry careers often lose their social and intellectual networks and their ability to return to tenure-track positions. Valuable insights from industry about memory, decision-making, learning, emotion, distributed cognition, and much more never return to the academic community. We believe that deep, theory driven, theory building work is being done in industry settings–and that the rift between communities makes all our work less effective",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; UX; Big data; Computational Modeling"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6734m2sg",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Landy",
                    "name_suffix": "",
                    "institution": "Netflix",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "",
                    "last_name": "Glushko",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21322/galley/10921/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21322/galley/15686/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21322/galley/21767/download/"
                }
            ]
        },
        {
            "pk": 24235,
            "title": "Rates of Spiritual Presence Events",
            "subtitle": null,
            "abstract": "In this paper, we catalog the rates at which people report spiritual presence events: phenomenal experiences understood by the perceiver to imply the presence of a spiritual being. We draw on four large datasets (total N=3150) collected in the US, Ghana, Thailand, China, and Vanuatu, including participants from a range of religious backgrounds. This yields what is, to our knowledge, an unprecedented “epidemiology” of spiritual presence events across diverse cultural settings. While some events vary dramatically in their rates of endorsement across cultural settings, other events are relatively common across all five settings, and still others are relatively rare across settings. In general, the most common events center on ordinary experiences of one's own inner life, while events that hinge on near-tangible perceptions of presence and hallucination-like events involving outer sensory experiences are relatively rare. In sum, local culture shapes but does not fully determine the architecture of spiritual experience.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Anthropology; Psychology; Culture; Perception; Cross-cultural analysis; Survey"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4wt510nb",
            "frozenauthors": [
                {
                    "first_name": "Eleanor",
                    "middle_name": "Brower",
                    "last_name": "Schille-Hudson",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Kara",
                    "middle_name": "",
                    "last_name": "Weisman",
                    "name_suffix": "",
                    "institution": "University of California, Riverside",
                    "department": ""
                },
                {
                    "first_name": "Tanya",
                    "middle_name": "",
                    "last_name": "Luhrmann",
                    "name_suffix": "",
                    "institution": "Stanford",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24235/galley/13831/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24235/galley/21490/download/"
                }
            ]
        },
        {
            "pk": 24095,
            "title": "Rationality Meets Facts",
            "subtitle": null,
            "abstract": "In this paper, we confront two prevailing views of rationality—reason- and coherence-based theories—with empirical facts. While the experimental resolution of the debate between both theories is challenging, we examine two cases in which these theories make distinct predictions regarding whether an agent is deemed rational or not. By directly pitting reason-based against coherence-based theories, our findings indicate that reasons play a more influential role in shaping people's attributions of rationality than coherence.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Psychology; Cognitive Humanities; Concepts and categories; Reasoning; Semantics; Case studies; Survey"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/09j1s4jd",
            "frozenauthors": [
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "Reuter",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Messerli",
                    "name_suffix": "",
                    "institution": "University if Zurich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24095/galley/13689/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24095/galley/21492/download/"
                }
            ]
        },
        {
            "pk": 24070,
            "title": "Rationally uncertain: investigating deviations from Explaining Away and Screening Off in causal reasoning",
            "subtitle": null,
            "abstract": "This work provides an alternative account for deviations in human causal reasoning from normative predictions based on Causal Bayesian Networks (CBNs). We highlight violations of the Markov condition (Screening Off) and insufficient Explaining Away. Different from other accounts, our model does not assume that people fail to honor normative predictions due to reliance on heuristics, hidden nodes and links or cognitive limitations. Instead, we propose that people are rationally uncertain about the received causal model they are asked to reason with. We fitted the model to published data from two experiments where people were asked to make probability estimates on inferences of interest within a causal model. We find that the model is able to i) reproduce deviations from normative predictions, and ii) predict changes in the magnitude of these deviations across contexts. We conclude that assuming that people, in order to be rational, will always fully believe in the information they receive about a causal model may be too strong an assumption.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Concepts and categories; Reasoning; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/31r8z1h8",
            "frozenauthors": [
                {
                    "first_name": "Nicolas",
                    "middle_name": "",
                    "last_name": "Marchant",
                    "name_suffix": "",
                    "institution": "Universidad Adolfo Ibàñez",
                    "department": ""
                },
                {
                    "first_name": "Guillermo",
                    "middle_name": "",
                    "last_name": "Puebla",
                    "name_suffix": "",
                    "institution": "Universidad de Tarapacà",
                    "department": ""
                },
                {
                    "first_name": "Tadeg",
                    "middle_name": "",
                    "last_name": "Quillien",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Sergio",
                    "middle_name": "E.",
                    "last_name": "Chaigneau",
                    "name_suffix": "",
                    "institution": "Adolfo Ibanez University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24070/galley/13664/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24070/galley/21493/download/"
                }
            ]
        },
        {
            "pk": 21523,
            "title": "Rational Polarization: Sharing Only One's Best Evidence Can Lead to Group Polarization",
            "subtitle": null,
            "abstract": "Contemporary formal models aim to capture group polarization as the result of deliberation between rational agents. Paradigmatic models do, however, rely on rather limited agents, casting doubt on the conclusion that group polarization can be rationally reconstructed. In this paper, we use a recently developed Bayesian agent-based model of deliberation to investigate this conclusion. This model avoids problems we identify in a group of influential Bayesian polarization models. Our case study shows that a simple mechanism produces realistic patterns of group polarization: limited exchange of evidence across a sparse social network.  We reflect on what our results mean for our formal understanding of rational group polarization.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Psychology; Agent-based Modeling; Bayesian modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6x80n8v4",
            "frozenauthors": [
                {
                    "first_name": "Leon",
                    "middle_name": "",
                    "last_name": "Assaad",
                    "name_suffix": "",
                    "institution": "Ludwig-Maximilians-Universität München",
                    "department": ""
                },
                {
                    "first_name": "Ulrike",
                    "middle_name": "",
                    "last_name": "Hahn",
                    "name_suffix": "",
                    "institution": "Birkbeck, University of London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21523/galley/11122/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21523/galley/14599/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21523/galley/21491/download/"
                }
            ]
        },
        {
            "pk": 24046,
            "title": "Reaching Consensus through Theory of Mind in Social Networks with Locally Distributed Interactions",
            "subtitle": null,
            "abstract": "How people reach consensus in social networks with locally distributed interactions is relevant to understanding collective group decision-making and problem-solving. However, while the importance of theory of mind in consensus problems has been hypothesized, little work has been done to test it systematically. We present both computational modeling and behavioral experiments designed to test the impact of theory of mind on individual choices within such consensus networks. We test 2,108 computational models informed by theoretical work on a graph-coloring consensus task to compare models using theory of mind to other behavioral parameters. We then use behavioral responses from 107 participants in a similar task to evaluate support for theory of mind in consensus formation. We find that the computational model that best accounts for prior behavioral data uses theory of mind, and our behavioral results likewise support use of theory of mind over other potential decision-making models.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Group Behaviour; Theory of Mind; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9qw9361h",
            "frozenauthors": [
                {
                    "first_name": "Daphne",
                    "middle_name": "",
                    "last_name": "Barretto",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Raja",
                    "middle_name": "",
                    "last_name": "Marjieh",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24046/galley/13640/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24046/galley/21496/download/"
                }
            ]
        },
        {
            "pk": 24469,
            "title": "Reach Tracking Reveals Distinct Inhibitory Control Processes in Adults' False Belief Inferences",
            "subtitle": null,
            "abstract": "The present study examines distinct inhibitory processes as adults make inferences about others' true and false beliefs while the movement of their finger is tracked in 3D space over time. This reach tracking method allows us to isolate distinct inhibitory control processes while participants make an inference. Adult participants were asked to make inferences about others' true and false belief states, as well as two control trials that differed in the use of inhibitory control. Adults showed a difference in accuracy in responding to others' true and false beliefs, suggesting that even though young children can recognize others' belief states, such performance is not at ceiling in adulthood. Moreover, adults showed a difference in the inhibitory resources necessary to make a response selection processes to accurately infer a false belief as opposed to a true one. Such differences were not present for other inferences that required different inhibitory control. This suggests that adults need specific inhibitory systems to infer others' false (as opposed to true) beliefs, and those systems are not involved in other inferences that require inhibition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Action; Embodied Cognition; Other; Theory of Mind"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9wx4k3h6",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "M.",
                    "last_name": "Sobel",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "G.",
                    "last_name": "Kamper",
                    "name_suffix": "",
                    "institution": "UCLA",
                    "department": ""
                },
                {
                    "first_name": "Joo-Hyun",
                    "middle_name": "",
                    "last_name": "Song",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24469/galley/14066/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24469/galley/21495/download/"
                }
            ]
        },
        {
            "pk": 21568,
            "title": "Readily grasping 'who' and 'whom': child-directed speech facilitates semantic role learning",
            "subtitle": null,
            "abstract": "A key aspect in child language development involves inducing\nthe rules that determine the relations of the arguments to\ntheir verbal predicate, i.e., semantic roles. Here, we investigate\nwhether child-directed speech facilitates learning ‘who\ndoes what to whom' in English and Russian, two languages\nthat strongly differ in their amount of case-marking and word\norder variation. We ask whether a contextual, distributional\nlearner can more easily learn to assign semantic roles to arguments\nbased on child-directed speech versus adult-directed\nspeech. To this end, we represent the arguments of a verb\nwith contextualised word embeddings extracted from neural\nlanguage models. We compare the classification accuracy\nof semantic roles based on these representations between utterances\nextracted from corpora of child-directed speech and\nadult-directed speech. We further study to what extent semantic\nroles can be predicted based on arguments represented\nby different levels of information, such as non-contextualised\nrepresentations, the position in the sentence, and case marking.\nWe find that child-directed speech facilitates the learning\nof semantic roles, an important cornerstone for learning the\nmorphosyntactic features of a language. However, the effect\nof child-directed speech is more pronounced in Russian than\nin English, indicating that child-directed speech may be optimised\nmore strongly in a language where arguments are expressed\nin more varied forms and positions, as is the case in\nRussian.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7k03n2gb",
            "frozenauthors": [
                {
                    "first_name": "Eva",
                    "middle_name": "",
                    "last_name": "Huber",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Sabine",
                    "middle_name": "",
                    "last_name": "Stoll",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Balthasar",
                    "middle_name": "",
                    "last_name": "Bickel",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21568/galley/11167/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21568/galley/21961/download/"
                }
            ]
        },
        {
            "pk": 24444,
            "title": "Reading in conditions of low contrast; the adaptability of binocular fixation behaviours",
            "subtitle": null,
            "abstract": "How does the visual system adapt to reduced contrast? Participants read a row of white numbers against a static background that changed from black to white, from left to right. There was pervasive binocular disparity between the fixation points of the left and right eye as legibility decreased. Overall, the lines of sight crossed more frequently in front of the stimulus plane (“crossed fixation disparities”) than behind (“uncrossed fixation disparities”). The proportion of crossed fixation disparities increased systematically with reading difficulty. Absolute size of fixation disparity changed differentially in the two disparity types when contrast reduced, implicating different subsystems. We claim that hemisphericity provides the most insightful understanding of these behaviours. The viewer has flexible control of (a) advantaged contralateral projections from retina to cortex, (b) the size of the perceptual window, and (c) binocular fusion. Thus, an apparent failure of the eyes to fixate precisely conjointly is revealed as an adaptation of embodied cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Perception; Reading; Eye tracking; Psychophysics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8843c0gk",
            "frozenauthors": [
                {
                    "first_name": "Ruomeng",
                    "middle_name": "",
                    "last_name": "Zhu",
                    "name_suffix": "",
                    "institution": "University of Amsterdam",
                    "department": ""
                },
                {
                    "first_name": "Mateo",
                    "middle_name": "",
                    "last_name": "Obregón",
                    "name_suffix": "",
                    "institution": "The University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Richard",
                    "middle_name": "",
                    "last_name": "Shillcock",
                    "name_suffix": "",
                    "institution": "The University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24444/galley/14041/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24444/galley/21497/download/"
                }
            ]
        },
        {
            "pk": 24798,
            "title": "Real-time processing of symmetrical predicates: Semantic categorization over time",
            "subtitle": null,
            "abstract": "Symmetry, a fundamental concept in perception and language, poses an interpretative challenge due to the disparity between its formal definition and linguistic expression. Formal symmetry is often distorted when expressed linguistically, such that e.g., 'North Korea is similar to Red China' is interpreted differently from 'Red China is similar to North Korea' despite their logical equivalence (Tversky, 1977). Gleitman et al. (1996) found this interpretive asymmetry stems from the syntactic positions of arguments, such that symmetry is restored when both arguments are on equal syntactic footing (e.g., a Conjoined NP Intransitive, “North Korea and China are similar”). Here a novel eye-tracking method tested how syntax and lexical semantics contribute to symmetrical interpretations. Participants were asked to rapidly sort spoken utterances by clicking on visible folders marked with a symmetrical or asymmetrical icon. Commitments to symmetry based on syntactic evidence emerged rapidly as the sentence unfolded over time.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language understanding; Eye tracking"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1pn4k173",
            "frozenauthors": [
                {
                    "first_name": "Ugurcan",
                    "middle_name": "",
                    "last_name": "Vurgun",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Heesu",
                    "middle_name": "",
                    "last_name": "Yun",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Barbara",
                    "middle_name": "",
                    "last_name": "Landau",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                },
                {
                    "first_name": "John",
                    "middle_name": "",
                    "last_name": "Trueswell",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24798/galley/21499/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24798/galley/14396/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24798/galley/18253/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24798/galley/21499/download/"
                }
            ]
        },
        {
            "pk": 24803,
            "title": "Real world event schemas offer modality-independent conceptual bases for verb argument structures",
            "subtitle": null,
            "abstract": "Gonering & Corina (2023) argued that abstractions over visual scenes (i.e. schemas or situation models) provide a semantic scaffold for acquiring verb argument structures. We provide a systematic meta-analysis of 158 fMRI studies of verb processing (from NeuroSynth) and 208 fMRI studies of visual event processing (from NeuroQuery) suggestive of their hypothesis. Functional maps produced using Activation Likelihood Estimation via the Neuroimaging Meta-Analysis Research Environment package (Salo et al., 2022) (cluster-level family-wise error corrected using Monte Carlo method) showed overlapping regions of activation in the left inferior parietal lobule and Brodmann's area 47 bilaterally, suggesting shared neural resources for processing verbs and visual scenes. Meta-analyses on additional visual scene and verb processing studies from NeuroSynth and NeuroQuery, respectively, are also underway. We further intend to show that a hierarchical Bayesian model can learn verb argument structures from input statistics, even when they deviate from strong prior event semantic knowledge.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language learning; Spatial cognition; Syntax; Bayesian modeling; fMRI"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6zz2q6tb",
            "frozenauthors": [
                {
                    "first_name": "Brennan",
                    "middle_name": "T",
                    "last_name": "Gonering",
                    "name_suffix": "",
                    "institution": "University of California, Davis",
                    "department": ""
                },
                {
                    "first_name": "Zoey",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "University of Florida",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24803/galley/21498/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24803/galley/14401/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24803/galley/18258/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24803/galley/21498/download/"
                }
            ]
        },
        {
            "pk": 24013,
            "title": "Real-World Visual Search in Autistic Individuals",
            "subtitle": null,
            "abstract": "Recent research has found that autistic individuals have poorer performance and lower eye movement consistency in face recognition, which may be related to less face processing experience due to lack of social interests. Here we showed that this phenomenon was not observed in visual search tasks, as autistic individuals and matched neurotypicals had similar hit rate and precision as well as eye movement behavior when searching for either social (human) or non-social (vehicle) stimuli. However, autistic individuals had longer search time and made more and longer fixations, suggesting difficulties in identifying potential targets. This difficulty was not limited to social stimuli, supporting a domain-general view of deficits in autism spectrum disorder (ASD). Our findings have important implications for understanding the core mechanisms underlying social-cognitive impairment in ASD.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Attention; Perception; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2kv7d88x",
            "frozenauthors": [
                {
                    "first_name": "Alice",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Janet",
                    "middle_name": "",
                    "last_name": "Hsiao",
                    "name_suffix": "",
                    "institution": "Hong Kong University of Science & Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24013/galley/13607/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24013/galley/21500/download/"
                }
            ]
        },
        {
            "pk": 21456,
            "title": "Reasoning about (In)Dependent Evidence: A Mismatch between Perceiving and Incorporating Dependencies?",
            "subtitle": null,
            "abstract": "Independent pieces of corroborating evidence should provide stronger support to a hypothesis than dependent pieces of evidence. Overlooking the inferiority of dependent relative to independent items of evidence can lead to a chain reaction of double-counting evidence, over-estimating the probability that the fact under consideration is true, and making wrongful decisions. Within fictitious scenarios, we investigate people's sensitivity to the independency advantage. We assess their ability to integrate multiple items of evidence that come from (in)dependent sources who differ in reliability. We find that participants properly perceive dependencies when explicitly asked but fail to distinguish the probative value of dependent versus independent evidence in their belief updating. Still, individuals who perceive a strong dependence between sources treat the evidence as being more redundant. We find no dependency-related effects on participants' individual Bayesian network model predictions. Potential reasons why participants perceive (in)dependencies and yet (mostly) fail to discount for them are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Decision making; Reasoning; Bayesian modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7jt638nj",
            "frozenauthors": [
                {
                    "first_name": "Laura Elaine",
                    "middle_name": "",
                    "last_name": "Strittmatter",
                    "name_suffix": "",
                    "institution": "ETH Zurich",
                    "department": ""
                },
                {
                    "first_name": "Toby",
                    "middle_name": "D",
                    "last_name": "Pilditch",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Lagnado",
                    "name_suffix": "",
                    "institution": "UCL",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21456/galley/11055/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21456/galley/21901/download/"
                }
            ]
        },
        {
            "pk": 21560,
            "title": "Reasoning about knowledge in lie production",
            "subtitle": null,
            "abstract": "Theory of Mind enables us to represent and reason about other people's mental states like beliefs and knowledge. By considering what other people know, this allows us to strategically construct believable lies. Previous work has shown that people construct lies to be consistent with others' beliefs even when those beliefs differ from their own. However, in most real world cases, we don't know everything that the other person knows. We propose that to produce believable lies, the sender considers what private information the receiver may have. Here, we develop our theory into a computational model and test it in a novel paradigm that allows us to distinguish between knowledge shared between the lie sender and receiver and knowledge private to the receiver. Our main model successfully captures how people lie in this paradigm over alternative models. Overall, our work furthers our understanding of human social cognition in adversarial situations.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Social cognition; Theory of Mind; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1528q2pr",
            "frozenauthors": [
                {
                    "first_name": "Zhi Yi",
                    "middle_name": "",
                    "last_name": "Tan",
                    "name_suffix": "",
                    "institution": "Yale NUS College",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Marlene",
                    "middle_name": "",
                    "last_name": "Berke",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21560/galley/11159/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21560/galley/14636/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21560/galley/21501/download/"
                }
            ]
        },
        {
            "pk": 23998,
            "title": "Reasoning with Polysemes: When Default Inferences Beat Contextual Information",
            "subtitle": null,
            "abstract": "How, and how strongly, do default comprehension inferences shape verbal reasoning? When do they lead to fallacies? We address these questions for reasoning with polysemous verbs (verbs with distinct, but related senses) and ask when their use leads to fallacies of equivocation. The ‘linguistic salience bias hypothesis' specifies conditions where subordinate uses of unbalanced polysemes trigger defeasible default inferences that are supported only by the dominant sense but influence further cognition, regardless. But does this happen even where the verb is preceded by disambiguating context that invites subordinate interpretations from the start? We present three experimental-philosophy studies that address this question: We use the psycholinguistic cancellation paradigm and fixation time measurements to examine inferences from polysemous appearance verbs. We find that default inferences can beat even preceding contextual information. Beyond their psycho-linguistic interest, findings have important philosophical consequences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Psychology; Language and thought; Language understanding; Reading; Reasoning; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/44d2d054",
            "frozenauthors": [
                {
                    "first_name": "Eugen",
                    "middle_name": "",
                    "last_name": "Fischer",
                    "name_suffix": "",
                    "institution": "University of East Anglia",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Engelhardt",
                    "name_suffix": "",
                    "institution": "University of East Anglia",
                    "department": ""
                },
                {
                    "first_name": "Dimitra",
                    "middle_name": "",
                    "last_name": "Lazaridou-Chatzigoga",
                    "name_suffix": "",
                    "institution": "University of East Anglia",
                    "department": ""
                },
                {
                    "first_name": "Kate",
                    "middle_name": "",
                    "last_name": "Stanton",
                    "name_suffix": "",
                    "institution": "University of Pittsburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23998/galley/13592/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/23998/galley/21502/download/"
                }
            ]
        },
        {
            "pk": 24023,
            "title": "Recognising prosodically degraded lexical material - Can word length help?",
            "subtitle": null,
            "abstract": "This study investigates the role of low-level acoustic cues in relation to increasing number of syllables in two word recognition experiments conducted in a remote field site. Participants are bilingual speakers of French and Drehu (Oceanic), two edge-marking languages. The two languages use grammatical gender, but differ in the number of function words used for it. In two experiments, prosodic cues were manipulated at the edges of Accentual Phrases (AP) of increasing length. APs consisted of an article and a following content word. Results show that the acoustic manipulations had a greater impact on short APs with three syllables while words in APs with more syllables could be retrieved faster in French. In Drehu, results indicate that words in longer APs are recognised later. This shows that despite similarities in the intonational phonology, listeners rely on different strategies during word recognition influenced by the grammatical make up of the language.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language understanding; Multilingualism; Cross-linguistic analysis; Field studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2zg7b9dm",
            "frozenauthors": [
                {
                    "first_name": "Catalina",
                    "middle_name": "",
                    "last_name": "Torres",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24023/galley/13617/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24023/galley/21503/download/"
                }
            ]
        },
        {
            "pk": 24720,
            "title": "Recognising the future utility of a solution: When do children choose to retain and share an object to solve a future problem?",
            "subtitle": null,
            "abstract": "Recognising the future utility of a solution is fundamental to our capacity for innovation. However, developmental research has thus far focused on children's capacity to create solutions, rather than recognise existing solutions with ongoing utility. We examined children's capacity to retain and share a solution that would be useful again in the future. Across two rooms, 4- to 9-year-olds (N=83) were given a series of time-based tasks which could be solved by building and using a tool. When given the opportunity to transport a tool between the first and second rooms, children from age 6 onwards retained the tool that would be useful again above chance levels. When subsequently asked to secure a solution for another child, only 8- to 9-year-olds chose this tool above chance. Positive age-partialled correlations between children's retaining and sharing behaviours suggest that these behaviours may reflect a common underlying capacity for recognising future utility.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/284829dn",
            "frozenauthors": [
                {
                    "first_name": "Zoe",
                    "middle_name": "",
                    "last_name": "Ockerby",
                    "name_suffix": "",
                    "institution": "The University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Suddendorf",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Redshaw",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24720/galley/21504/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24720/galley/14318/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24720/galley/18173/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24720/galley/21504/download/"
                }
            ]
        },
        {
            "pk": 24269,
            "title": "Reconstruction of visually stable perception from saccadic retinal inputs using corollary discharge signals-driven convLSTM neural networks",
            "subtitle": null,
            "abstract": "While subjective visual experiences are remarkably stable and coherent, their underlying data is incomplete and heavily influenced by the eyes' saccadic rhythm. In this work, we show that a deep and recurrent neural network can effectively reconstruct vibrant images from restricted retinal inputs during active vision. Our method includes the creation of a dataset for synthetic retinal inputs, containing intensity, color, and event-camera-generated motion data. We demonstrate the importance of both long-short-term memory and corollary discharge signals to image stabilization and the system's sensitivity to noise, corresponding to recent experimental findings. Our study contributes to the advancement of realistic and dynamic models for image reconstruction, providing insights into the complexities of active visual perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Computer Science; Machine learning; Perception; Vision; Computational Modeling; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8g15s854",
            "frozenauthors": [
                {
                    "first_name": "Yahia",
                    "middle_name": "",
                    "last_name": "Showgan",
                    "name_suffix": "",
                    "institution": "The Open University of Israel",
                    "department": ""
                },
                {
                    "first_name": "Hadar",
                    "middle_name": "",
                    "last_name": "Cohen Duwek",
                    "name_suffix": "",
                    "institution": "Open University of Israel",
                    "department": ""
                },
                {
                    "first_name": "Elishai",
                    "middle_name": "",
                    "last_name": "Ezra Tsur",
                    "name_suffix": "",
                    "institution": "The Open University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24269/galley/13865/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24269/galley/21505/download/"
                }
            ]
        },
        {
            "pk": 24638,
            "title": "Recovering cognitive events from trial-level pupil time courses",
            "subtitle": null,
            "abstract": "Pupil dilation is assumed to be a slow and indirect reflection of latent cognitive events. Deconvolution approaches promise a more precise study of these events, assuming that they all trigger a delayed pupil response.\n\nHowever, conventional deconvolution approaches neglect the possibility that between-event timings and the shape of the pupil responses differ between subjects, trials, and cognitive events. Accounting for this variability however is crucial to 1) achieve precise recovery of latent events and 2) to investigate how trial-level predictors influence cognitive processes.\n\nWe present a new method that performs trial-level deconvolution by combining generalized additive mixed models with Hidden semi-Markov models. We tested this method on synthetic data and subsequently applied it to data from a lexical decision experiment (N=24) and recovered six processing events. Investigating the trial-level durations of the recovered events revealed that early visual and late decision-related processing were influenced differently by frequency and word-type.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Computer Science; Neuroscience; Machine learning; Bayesian modeling; Computational Modeling; Electroencephalography (EEG); Mathematical modeling; Statistics"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7xz4q2p9",
            "frozenauthors": [
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Krause",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Jelmer",
                    "middle_name": "",
                    "last_name": "Borst",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Jacolien",
                    "middle_name": "",
                    "last_name": "van Rij",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24638/galley/21506/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24638/galley/14235/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24638/galley/18017/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24638/galley/21506/download/"
                }
            ]
        },
        {
            "pk": 24576,
            "title": "Recovering individual mental representations of facial affect using Variational Auto-Encoder Guided Markov Chain Monte Carlo with People",
            "subtitle": null,
            "abstract": "People's mental representations of complex stimuli, such as images of facial affect, are difficult to elicit. To address this challenge, methods such as Markov Chain Monte Carlo with People (MCMCP), integrate human agents into computer-based sampling algorithms. However, such methods suffer from slow convergence, making them impractical for recovering the representations of individuals. Here, we extended MCMCP by introducing an adapted Variational Auto-Encoder (VAE) with domain knowledge as an auxiliary agent, guiding the sampling process away from less useful experimental trials. To test this approach, we ran a new experiment comparing such a VAE-guided MCMCP against baseline MCMCP in terms of convergence speed and quality of recovering human representations of facial affect. Preliminary results demonstrated that most guided chains converged on an individual's facial affect representation within a single experimental session, faster than the baseline methods, and results showed the extent of individual differences in facial affect representations. Thus, VAE-guided MCMCP provides a promising framework for interfacing machine intelligence with psychological experiments to enhance our understanding of human cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Emotion; Computational Modeling; Neural Networks"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/96c7b4x9",
            "frozenauthors": [
                {
                    "first_name": "Haijiang",
                    "middle_name": "",
                    "last_name": "Yan",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Nick",
                    "middle_name": "",
                    "last_name": "Chater",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Christian",
                    "middle_name": "",
                    "last_name": "Tsvetkov",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Sanborn",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24576/galley/21507/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24576/galley/14173/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24576/galley/21507/download/"
                }
            ]
        },
        {
            "pk": 21479,
            "title": "Recovering Mental Representations from Large Language Models with Markov Chain Monte Carlo",
            "subtitle": null,
            "abstract": "Simulating sampling algorithms with people has proven a useful method for efficiently probing and understanding their mental representations. We propose that the same methods can be used to study the representations of Large Language Models (LLMs). While one can always directly prompt either humans or LLMs to disclose their mental representations introspectively, we show that increased efficiency can be achieved by using LLMs as elements of a sampling algorithm. We explore the extent to which we recover human-like representations when LLMs are interrogated with Direct Sampling and Markov chain Monte Carlo (MCMC). We found a significant increase in efficiency and performance using adaptive sampling algorithms based on MCMC. We also highlight the potential of our method to yield a more general method of conducting Bayesian inference with LLMs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Psychology; Behavioral Science; Decision making; Intelligent agents; Language and thought; Machine learning; Pattern recognition; Perception; Computational M"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4fj2f7br",
            "frozenauthors": [
                {
                    "first_name": "Jian-Qiao",
                    "middle_name": "",
                    "last_name": "Zhu",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Haijiang",
                    "middle_name": "",
                    "last_name": "Yan",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21479/galley/11078/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21479/galley/21924/download/"
                }
            ]
        },
        {
            "pk": 24302,
            "title": "Re-Examining Base-Rate Neglect: The Effect Of Context",
            "subtitle": null,
            "abstract": "Classic base-rate neglect studies have been consistently criticised for lacking ecological validity. A study by Welsh & Navarro (2012) found this heuristic was significantly reduced when participants perceived the base rate as more relevant. The present study aims to study this phenomenon through a more realistic scenario while simultaneously capturing participants' written reasoning. Using mixed-methods, participants (N = 2,052) read an engaging scenario regarding a person who committed infidelity and containing a base-rate and specific information where the contextual information regarding the base-rate was manipulated. They were then asked to provide an estimate of the person's likelihood to cheat in the future. Results show that each of our three manipulations to the context of the base rate are significant in affecting participants' estimates, supporting Welsh and Navarro's findings. Analysis of participants' written reasoning demonstrates the sophistication and nuance of participants' engagement with the base-rate, challenging the original view of this supposed heuristic.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Causal reasoning; Decision making; Problem Solving; Reasoning; Qualitative Analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1v2727wr",
            "frozenauthors": [
                {
                    "first_name": "Nine",
                    "middle_name": "",
                    "last_name": "Adler",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Stephen",
                    "middle_name": "H",
                    "last_name": "Dewitt",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24302/galley/13898/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24302/galley/21494/download/"
                }
            ]
        },
        {
            "pk": 24327,
            "title": "Refixation Strategies in Sentential Word Reading: An Exploration by Linked Linear Mixed Models",
            "subtitle": null,
            "abstract": "The current study undertakes refixation patterns on words in sentential reading. Utilizing a Linked Linear Mixed Model approach, the analysis focused on words with a single fixation and the first fixation from words with a double fixation. The model findings revealed a relationship between refixation probability and fixation locations, with initial fixations tending to occur closer to the beginning of a word in instances of higher refixation likelihood. Incorporating predicted and residual values of the fixation location models into the fixation duration models resulted in congruence in the observed fixation locations, durations, and residual values. Finally, the models revealed differences between progressive and regressive second fixations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Reading; Eye tracking; Statistics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7m11b8t7",
            "frozenauthors": [
                {
                    "first_name": "Ay≈üegül",
                    "middle_name": "",
                    "last_name": "Ōzkan",
                    "name_suffix": "",
                    "institution": "Jagiellonian University",
                    "department": ""
                },
                {
                    "first_name": "Cengiz",
                    "middle_name": "",
                    "last_name": "Acarturk",
                    "name_suffix": "",
                    "institution": "Jagiellonian University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24327/galley/13924/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24327/galley/21508/download/"
                }
            ]
        },
        {
            "pk": 24096,
            "title": "Regret Theory predicts decoy effects in risky and multiattribute choice",
            "subtitle": null,
            "abstract": "Regret Theory (Loomes & Sugden, 1982) is a theory of decision making based on the idea that people consider not only outcome utility, but also future regret or rejoicing, which depends on both the chosen option and foregone options. Regret theory was originally proposed as a theory of choice under uncertainty. Here, we demonstrate that Regret Theory also predicts the widely studied attraction, compromise, and similarity context effects. First, we show that it predicts attraction effects in choice among gamble triples. Second, we apply Regret Theory to non-gamble multi-attribute choice settings and show that both predicts these context effects and predicts a within-subject dissociation between the compromise and similarity effects previously observed in empirical studies. Regret Theory provides a foundation for a unified account of risky and multi-attribute choice, and we believe the form we present here provides the simplest account to date that explains phenomena in both domains.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Computer-based experiment; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6g72j3xw",
            "frozenauthors": [
                {
                    "first_name": "Logan",
                    "middle_name": "A",
                    "last_name": "Walls",
                    "name_suffix": "",
                    "institution": "University of Michigan",
                    "department": ""
                },
                {
                    "first_name": "Andrew",
                    "middle_name": "",
                    "last_name": "Howes",
                    "name_suffix": "",
                    "institution": "University of Exeter",
                    "department": ""
                },
                {
                    "first_name": "Rick",
                    "middle_name": "",
                    "last_name": "Lewis",
                    "name_suffix": "",
                    "institution": "University of Michigan",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24096/galley/13690/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24096/galley/21509/download/"
                }
            ]
        },
        {
            "pk": 24477,
            "title": "Relating Hopfield Networks to Episodic Control",
            "subtitle": null,
            "abstract": "Neural Episodic Control is a powerful reinforcement learning framework that employs a differentiable dictionary to store non-parametric memories. It was inspired by episodic memory on the functional level, but lacks a direct theoretical connection to the associative memory models generally used to implement such a memory. We first show that the dictionary is an instance of the recently proposed Universal Hopfield Network framework. We then introduce a continuous approximation of the dictionary readout operation in order to derive two energy functions that are Lyapunov functions of the dynamics. Finally, we empirically show that the dictionary outperforms the Max separation function, which had previously been argued to be optimal, and that performance can further be improved by replacing the Euclidean distance kernel by a Manhattan distance kernel. These results are enabled by the generalization capabilities of the dictionary, so a novel criterion is introduced to disentangle memorization from generalization when evaluating associative memory models.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Action; Machine learning; Memory; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1f37d1hd",
            "frozenauthors": [
                {
                    "first_name": "Hugo",
                    "middle_name": "",
                    "last_name": "Chateau-Laurent",
                    "name_suffix": "",
                    "institution": "Inria centre at the university of Bordeaux",
                    "department": ""
                },
                {
                    "first_name": "Frederic",
                    "middle_name": "",
                    "last_name": "Alexandre",
                    "name_suffix": "",
                    "institution": "Inria centre at the university of Bordeaux",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24477/galley/21510/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24477/galley/14074/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24477/galley/21510/download/"
                }
            ]
        },
        {
            "pk": 24541,
            "title": "Relationship between emotional linkages and perceived emotion during a joint task",
            "subtitle": null,
            "abstract": "Emotional physiological responses are altered not only by external events, but also by the emotions of the people in front of us. While these interpersonal emotional linkages are considered an important aspect of empathy, it is unclear how they relate to cognitive empathy, that is, how we perceive others' emotions. We investigated the relationship between emotional linkage and emotional cognition in an experiment in which two participants estimate each other's emotions while their heart rates were measured during a thrilling joint task using a block game. We also collected data from the two observers because, in reality, in addition to understanding the emotions of the interacting partner, it is sometimes necessary to understand the emotions of a non-interacting person from a third-person perspective. The results suggest that, for game players, their own heart rate is related to perceived partner emotion, and for observers, the degree of heart rate synchrony between observers is related to perceived player emotion. Capturing emotional cognition in a joint task requires consideration of both individual emotion and interpersonal emotional linkages.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Emotion; Emotion Perception; Empathy"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3hb871td",
            "frozenauthors": [
                {
                    "first_name": "Aiko",
                    "middle_name": "",
                    "last_name": "Murata",
                    "name_suffix": "",
                    "institution": "Nippon Telegraph and Telephone Corporation",
                    "department": ""
                },
                {
                    "first_name": "Shiro",
                    "middle_name": "",
                    "last_name": "Kumano",
                    "name_suffix": "",
                    "institution": "Nippon Telegraph and Telephone Corporation",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24541/galley/21511/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24541/galley/14138/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24541/galley/21511/download/"
                }
            ]
        },
        {
            "pk": 24652,
            "title": "Relationship Between Spatial and Number Development: Spatial Location Knowledge but not Mental Rotation relates to Numerical Skills of Preschoolers",
            "subtitle": null,
            "abstract": "Space helps us understand abstract math concepts (Winter et al., 2015). Mental rotation is often studied for its predictive role in math development (Casey et al., 2015; Geer et al., 2019). The association between spatial location knowledge and math development remains overlooked despite the significance of left-right body space encoding in numbers (SNARC effect, Dehaene et al., 1993). This ongoing study investigates the link between preschoolers' mental rotation skills, spatial location knowledge, and various mathematical abilities (symbolic, non-symbolic, counting). Preliminary analyses (N= 20; Mage= 4;6) using R showed a significant relationship between spatial location knowledge and symbolic math (r= .43; p= .05) and counting skills (r= .51; p= .02), while no such association is found between mental rotation skills and mathematical abilities (all ps> .05). These findings demonstrate a strong link between spatial location knowledge, but not mental rotation, and development of preschoolers' mathematical skills.\n\nKeywords: space; number; preschoolers",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Development; Problem Solving; Spatial cognition"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9ck8h54v",
            "frozenauthors": [
                {
                    "first_name": "Hüseyin",
                    "middle_name": "",
                    "last_name": "Yalçıner",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                },
                {
                    "first_name": "Dilay",
                    "middle_name": "Z.",
                    "last_name": "Karadoller",
                    "name_suffix": "",
                    "institution": "Koç University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24652/galley/21512/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24652/galley/14250/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24652/galley/18042/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24652/galley/21512/download/"
                }
            ]
        },
        {
            "pk": 24329,
            "title": "Relative Rank Predicts Judgements About Others' Pro-Environmental Behavior",
            "subtitle": null,
            "abstract": "Judgements about others' behavior is often made based on the relative rank of that behavior. We investigated this in the new domain of pro-environmental behavior, specifically for the categories of energy and water consumption, food (meat) consumption and transport choice. Using unimodal and bimodal distributions, we experimentally manipulated three fictional individuals' (common points) rank positions while keeping their absolute frequency of behaviors constant. Consistent with previous literature, participants' judgements about these people's pro-environmental behavior differed based on their rank position. Rank effects were not moderated by the perceived Importance of others' behavior, the perceived Visibility of the behavior, or the perceived level of Control. The results of this experiment are in line with a Decision by Sampling account of judgments of pro-environmental behavior, and set a foundation for future research seeking to conduct behavioral interventions (such as rank-based nudges) within this domain. Prior to this, however, future studies should investigate whether the smaller effect sizes found in this experiment, compared to those seen in previous research, are attributable to methodological differences, or the domain itself.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Decision making"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8773g5rr",
            "frozenauthors": [
                {
                    "first_name": "Harry",
                    "middle_name": "D.",
                    "last_name": "Coulson",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Harris",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24329/galley/13926/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24329/galley/21513/download/"
                }
            ]
        },
        {
            "pk": 21557,
            "title": "Relative Value Biases in Large Language Models",
            "subtitle": null,
            "abstract": "Studies of reinforcement learning in humans and animals have demonstrated a preference for options that yielded relatively better outcomes in the past, even when those options are associated with lower absolute reward. The present study tested whether large language models would exhibit a similar bias. We had gpt-4-1106-preview (GPT-4 Turbo) and Llama-2-70B make repeated choices between pairs of options with the goal of maximizing payoffs. A complete record of previous outcomes was included in each prompt. Both models exhibited relative value decision biases similar to those observed in humans and animals. Making relative comparisons among outcomes more explicit magnified the bias, whereas prompting the models to estimate expected outcomes caused the bias to disappear. These results have implications for the potential mechanisms that contribute to context-dependent choice in human agents.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Decision making; Learning; Large Language Models"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1t3926gd",
            "frozenauthors": [
                {
                    "first_name": "William",
                    "middle_name": "M",
                    "last_name": "Hayes",
                    "name_suffix": "",
                    "institution": "Binghamton University",
                    "department": ""
                },
                {
                    "first_name": "Nicolas",
                    "middle_name": "",
                    "last_name": "Yax",
                    "name_suffix": "",
                    "institution": "École normale supérieure",
                    "department": ""
                },
                {
                    "first_name": "Stefano",
                    "middle_name": "",
                    "last_name": "Palminteri",
                    "name_suffix": "",
                    "institution": "École normale supérieure",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21557/galley/11156/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21557/galley/14633/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21557/galley/21514/download/"
                }
            ]
        },
        {
            "pk": 24249,
            "title": "REM (1997) Predicts Recognition. Tested With 2AFC, and 4AWC",
            "subtitle": null,
            "abstract": "We use a novel paradigm to test models of long-term recognition memory: After studying lists, tests are made with two items, both OLD, both NEW, or one of each. Some tests used Two-Alternative Forced Choice (2AFC) in which Ss were asked to choose the item more likely OLD (Experiment 2 asked Ss to choose the item more likely NEW); other tests used four-way classification (4WC) in which Ss were asked to classify the two items as 1) both old, 2) both new, 3) left old, right new, or 4) left new, right old. Each S studied lists containing 12 words, 24 words, 12 pictures, 24 pictures, or lists of 12 words randomly mixed with 12 pictures (so tests were both words, both pictures or one each). All the choice probabilities were predicted well by the Retrieving Effectively from Memory model (REM) of Shiffrin and Steyvers (1997) using mostly the three 1997 parameter values and the REM decision threshold of odds of 1.0. Signal-detection modeling (unequal variance Gaussian strength distributions) predicted the choice probabilities with different parameters for different conditions. Initial analysis and modeling of Response times suggested that REM may be well suited to predict differing accuracy and response time results for judgments of OLD and NEW.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Memory; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6171b2tz",
            "frozenauthors": [
                {
                    "first_name": "Zainab",
                    "middle_name": "",
                    "last_name": "Mohamed",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                },
                {
                    "first_name": "Constantin",
                    "middle_name": "G.",
                    "last_name": "Meyer-Grant",
                    "name_suffix": "",
                    "institution": "University of Freiburg",
                    "department": ""
                },
                {
                    "first_name": "Richard",
                    "middle_name": "",
                    "last_name": "Shiffrin",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24249/galley/13845/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24249/galley/21515/download/"
                }
            ]
        },
        {
            "pk": 21520,
            "title": "Remembered Futures and Anticipated Pasts: The Recursive Grammar of Mental Time Travel",
            "subtitle": null,
            "abstract": "One feature of mental time travel is the ability to recursively embed temporal perspectives across different times: humans can remember how we anticipated the future and anticipate how we will remember the past. This recursive structure might be formalised in terms of a “grammar” that is reflective of but more general than linguistic notions of absolute and relative tense. Here I provide a foundation for this grammatical framework, emphasising a bounded (rather than unbounded) role of recursion in supporting mental time travel to a limited temporal depth and to actual and possible scenarios. Anticipated counterfactual thinking, for instance, entails three levels of mental time travel to a possible scenario (“in the future I will reflect on how my past self could have taken a different future action”) and is implicated in complex human decision-making. This perspective calls for further research into the nature and origins of recursive mental time travel.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognition of Time; Event cognition; Memory; Representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3xz0681s",
            "frozenauthors": [
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Redshaw",
                    "name_suffix": "",
                    "institution": "University of Queensland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21520/galley/11119/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21520/galley/14596/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21520/galley/21516/download/"
                }
            ]
        },
        {
            "pk": 24622,
            "title": "Remembering better: A bridge between paired-associate learning and higher-order cognition",
            "subtitle": null,
            "abstract": "Paired-associate learning is a classic paradigm addressing a most fundamental memory task: recalling examples of arbitrary associations between elements. One lesson is that semantics matters to this otherwise episodic task in that elaborative rehearsal connecting the words facilitates cued-recall. We ask whether two forms of semantic elaboration, inspired by higher-order cognition, can produce even better performance. Control groups performed ordinary elaborative study tasks (integrated imagery and compare/contrast) within a traditional paired-associate learning task. Experimental groups either: (1) completed a conceptual combination task requiring them to invent a novel concept aptly captured by the noun-noun pair; or (2) invoked relational cognition skills by predicating a propositional statement wherein the two concepts each fulfilled roles in a semantic relationship. Across three experiments relational predication showed a sizable advantage in cued-recall relative to controls; and additional evidence revealed a less robust benefit of conceptual combination. Implications for theory and application are discussed",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Learning; Memory"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1km4m9bn",
            "frozenauthors": [
                {
                    "first_name": "Keith",
                    "middle_name": "L",
                    "last_name": "Sherman",
                    "name_suffix": "",
                    "institution": "Binghamton University",
                    "department": ""
                },
                {
                    "first_name": "Kenneth",
                    "middle_name": "",
                    "last_name": "Kurtz",
                    "name_suffix": "",
                    "institution": "Binghamton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24622/galley/21517/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24622/galley/14219/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24622/galley/17987/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24622/galley/21517/download/"
                }
            ]
        },
        {
            "pk": 24744,
            "title": "Repair in Children's Language Acquisition: Universal Principles and Patterns of Variation",
            "subtitle": null,
            "abstract": "We study repair in child-directed, child-surrounding and child speech in longitudinal corpora of 4 languages: English, Russian, Chintang and Indonesian (age range: 2;01-3;04). We distinguish open requests (e.g. 'huh?'), restricted requests (e.g. 'you saw what?'), and restricted offers (reformulation or recast, e.g. 'you saw a bird?').\nOur results indicate that in the aggregated model, clarification requests develop in children independently from adult speech, pointing to early universal emergence. When we analyse repair types separately, only restricted offers in both CDS and CSS are significantly predictive factors for the number of reformulations in child speech. Since this repair type is used by caregivers to provide both positive and negative feedback to children, they follow a special path of acquisition dependent on input distributions. \nTherefore, we propose that early repair acquisition relies on individual cognitive development of children as well as language exposure to the recast frequency in the caregiver speech.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language development; Pragmatics; Corpus studies; Cross-linguistic analysis"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9s76z2m9",
            "frozenauthors": [
                {
                    "first_name": "Liudmyla",
                    "middle_name": "",
                    "last_name": "Feurstein",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Sabine",
                    "middle_name": "",
                    "last_name": "Stoll",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24744/galley/21518/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24744/galley/14342/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24744/galley/18200/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24744/galley/21518/download/"
                }
            ]
        },
        {
            "pk": 24574,
            "title": "Representation in Large Language Models",
            "subtitle": null,
            "abstract": "Cognitive scientists attribute representations to complex systems in order to explain their behavior. The shocking facility with which Large Language Models (LLMs) perform difficult linguistic and non-linguistic tasks has generated an increasing amount of speculation concerning what sorts of internal representations might underlie this behavior (whether personal, sub-personal, and of which kinds) and what properties such representations might have (for instance, whether they are grounded). This paper aims to elaborate and defend a conservative explanatory methodology, based on analyses of particular LLM behaviors, according to which attribution of sub-personal representations is key to explaining model performance which is robust, systematic, and flexible, especially in zero-shot settings, and that behavioral benchmarking alone is insufficient to resolve questions about representation due to the mutual underdetermination of performance and competence. The resulting view should help frame future explanations of LLM behavior, and provide an empirically grounded alternative to mere a priori speculation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Language understanding; Representation; Large Language Models"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/77d131m7",
            "frozenauthors": [
                {
                    "first_name": "Cameron",
                    "middle_name": "C",
                    "last_name": "Yetman",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24574/galley/21519/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24574/galley/14171/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24574/galley/21519/download/"
                }
            ]
        },
        {
            "pk": 21480,
            "title": "Representations as Language: An Information-Theoretic Framework for Interpretability",
            "subtitle": null,
            "abstract": "Large scale neural models show impressive performance across a wide array of linguistic tasks. Despite this they remain, largely, black-boxes - learning vector-representations of their input that prove difficult to interpret. This limits our ability to understand what they learn, and when the learn it, or characterise why they often fail to generalise systematically. To address this we introduce a novel approach to interpretability that looks at the mapping a model learns from sentences to representations as a kind of language in its own right. In doing so we introduce a set of information-theoretic measures that quantify how structured a model's representations are with respect to its input, and when during training that structure arises. Our measures are fast to compute, grounded in linguistic theory, and can predict which models will generalise best based on their representations. We use these measures to describe two distinct phases of training a transformer: an initial phase of in-distribution learning which reduces task loss, then a second stage where representations becoming robust to noise. Generalisation performance begins to increase during this second phase, drawing a link between generalisation and robustness to noise. Finally we look at how model size affects the structure of the representational space, showing that larger models ultimately compress their representations more than their smaller counterparts.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Linguistics; Complex systems; Representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/00x5698v",
            "frozenauthors": [
                {
                    "first_name": "Henry",
                    "middle_name": "",
                    "last_name": "Conklin",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Kenny",
                    "middle_name": "",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21480/galley/11079/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21480/galley/21925/download/"
                }
            ]
        },
        {
            "pk": 21710,
            "title": "Resource-Rational Encoding of Reward Information in Planning",
            "subtitle": null,
            "abstract": "Working memory is widely assumed to underlie multi-step planning, where representations of possible future actions and rewards are iteratively updated before determining a choice. But most working memory research focuses on a context where stimuli are presented simultaneously and the value of encoding each stimulus is independent of others. It is unclear how working memory functions in planning scenarios where the rewards of future actions unfold over time, are retained in working memory, and must be integrated for plan selection. To bridge this gap, we adapted a version of the \"mouselab task\" in which participants sequentially observe the reward at each node in a decision tree before selecting a plan that maximizes cumulative rewards. We specified a theoretical model to characterize the optimal encoding and maintenance strategy for this task given the working memory constraints, which trades off the cost of storing information with the potential benefit of informing later choices. The model encoded rewards in choice-relevant plans more often, in particular, rewards on the best and (to a lesser extent) worst plans. We then tested this hypotheses on human participants, who showed the same pattern in the accuracy of their explicit recall. Our study thus establishes an empirical and theoretical foundation for models of how people encode and maintain information during planning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Psychology; Action; Decision making; Machine learning; Memory; Perception; Agent-based Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8sb1c95h",
            "frozenauthors": [
                {
                    "first_name": "Zhuojun",
                    "middle_name": "",
                    "last_name": "Ying",
                    "name_suffix": "",
                    "institution": "UCSD",
                    "department": ""
                },
                {
                    "first_name": "Frederick",
                    "middle_name": "",
                    "last_name": "Callaway",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Anastasia",
                    "middle_name": "",
                    "last_name": "Kiyonaga",
                    "name_suffix": "",
                    "institution": "UC San Diego",
                    "department": ""
                },
                {
                    "first_name": "Marcelo",
                    "middle_name": "G",
                    "last_name": "Mattar",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21710/galley/11309/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21710/galley/22103/download/"
                }
            ]
        },
        {
            "pk": 21663,
            "title": "Resource-rational moral judgment",
            "subtitle": null,
            "abstract": "There is wide agreement that the mind has different mechanisms it can use to make moral judgments. But how does it decide which one to use when?  Recent theoretical work has suggested that people select mechanisms of moral judgment in a way that is resource-rational --- that is, by rationally trading off effort against utility. For instance, people may follow general rules in low-stakes situations, but engage more computationally intensive mechanisms such as consequentialist or contractualist reasoning when the stakes are high. Here, we evaluate whether humans and large language models (LLMs) exhibit resource-rational moral reasoning in two moral dilemmas by manipulating the stakes of each scenario. As predicted, we found that the higher the stakes, the more people employed a more effortful mechanism over following a general rule. However, there was mixed evidence for similar resource-rational moral reasoning in the LLMs. Our results provide evidence that people's moral judgments reflect resource-rational cognitive constraints, and they highlight the opportunities for developing AI systems better aligned with human moral values.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Psychology; Reasoning; Large Language Models"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4jg1t212",
            "frozenauthors": [
                {
                    "first_name": "Sarah",
                    "middle_name": "A",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Xiang",
                    "middle_name": "",
                    "last_name": "Ren",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                },
                {
                    "first_name": "Tobias",
                    "middle_name": "",
                    "last_name": "Gerstenberg",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Yejin",
                    "middle_name": "",
                    "last_name": "Choi",
                    "name_suffix": "",
                    "institution": "University of Washington",
                    "department": ""
                },
                {
                    "first_name": "Sydney",
                    "middle_name": "",
                    "last_name": "Levine",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21663/galley/11262/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21663/galley/14571/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21663/galley/22040/download/"
                }
            ]
        },
        {
            "pk": 24550,
            "title": "Restless Sleep, Uncertain Minds: Learning and Inhibitory Control Under Partial Sleep Deprivation.",
            "subtitle": null,
            "abstract": "This study assesses how partially sleep-deprived individuals learn regularities in a predictable yet uncertain environment and evaluates the impact of their expectations on inhibitory control performance. Participants were randomly assigned to undergo either an 8-hour (well-rested, WR, n=36) or a 4-hour (sleep-restriction, SR, n=32) sleep period before performing a Go/No-Go task in which we systematically varied the proportions of Go and No-Go trials (20%-80%, 80%-20%, 50%-50%). Preliminary results showed faster reaction times with increasing \"Go\" probability for both groups. The WR group showed a growing Go-Probability effect over time, unlike the SR group, suggesting potential differences in the underlying learning styles (e.g., meta- learning). As for accuracy, commission errors were more frequent as the probability of “Go” increased, irrespective of the group. To delve further into the effects of sleep deprivation on learning, a Bayesian model for individual learning under uncertainty will be implemented.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Motor control; Predictive Processing; Sleep; Bayesian modeling"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/65b2f0n7",
            "frozenauthors": [
                {
                    "first_name": "Margherita",
                    "middle_name": "",
                    "last_name": "Calderan",
                    "name_suffix": "",
                    "institution": "University of Padova",
                    "department": ""
                },
                {
                    "first_name": "Antonino",
                    "middle_name": "",
                    "last_name": "Visalli",
                    "name_suffix": "",
                    "institution": "University of Padova",
                    "department": ""
                },
                {
                    "first_name": "Roberta",
                    "middle_name": "",
                    "last_name": "Sellaro",
                    "name_suffix": "",
                    "institution": "University of Padova",
                    "department": ""
                },
                {
                    "first_name": "Nicola",
                    "middle_name": "",
                    "last_name": "Cellini",
                    "name_suffix": "",
                    "institution": "University of Padova",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24550/galley/21520/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24550/galley/14147/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24550/galley/21520/download/"
                }
            ]
        },
        {
            "pk": 24348,
            "title": "Rethinking AI: Moving Beyond Humans as Exclusive Creators",
            "subtitle": null,
            "abstract": "Termed the 'Made-by-Human Hypothesis,' I challenge the commonly accepted notion that Artificial Intelligence (AI) is exclusively crafted by humans, emphasizing its impediment to progress. I argue that influences beyond human agency significantly shape AI's trajectory. Introducing the 'Hybrid Hypothesis,' I suggest that the creation of AI is multi-sourced; methods such as evolutionary algorithms influencing AI originate from diverse sources and yield varied impacts. I argue that the development of AI models will increasingly adopt a 'Human+' hybrid composition, where human expertise merges with AI's intrinsic mechanisms, which themselves are influenced by non-human sources. The Hybrid Hypothesis posits that the origin of AI extends beyond human influence, prompting a thorough exploration of unresolved issues in the field of artificial intelligence.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Human-computer interaction; Machine learning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2zr474zq",
            "frozenauthors": [
                {
                    "first_name": "Renee",
                    "middle_name": "",
                    "last_name": "Ye",
                    "name_suffix": "",
                    "institution": "Ruhr-Universität Bochum",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24348/galley/13945/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24348/galley/21521/download/"
                }
            ]
        },
        {
            "pk": 24743,
            "title": "Rethinking Inference: A Multidimensional Model of Inference for Human and Nonhuman Animals",
            "subtitle": null,
            "abstract": "Traditional conceptions of inference emphasize explicit following of logical rules, often tied to the possession of natural language, thereby implying that non-human animals cannot make inferences. However, comparative research shows extensive evidence of the success of several species of non-human animals in nonverbal reasoning tasks, putting pressure on the traditional view. We deny two traditional assumptions about inference: the lingualism of thought, and the requirement of explicit rule following. We suggest instead a multidimensional model of inference illustrated through several case studies. Thereby, we categorize informational transfers across three dimensions by marking the degree of context-independence, the format of representation, and the type of perspectivity involved. By allowing for a more nuanced interpretation of empirical data than the traditional view, our framework is able to accommodate inferential behaviors of both linguistic and non-linguistic agents, and shed light on varied manifestations of inference across species and developmental stages.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Animal cognition; Language and thought; Reasoning; Representation; Situated cognition; Comparative Studies"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5wn031j8",
            "frozenauthors": [
                {
                    "first_name": "Albert",
                    "middle_name": "",
                    "last_name": "Newen",
                    "name_suffix": "",
                    "institution": "Ruhr-Universität Bochum",
                    "department": ""
                },
                {
                    "first_name": "Sanja",
                    "middle_name": "",
                    "last_name": "Sreckovic",
                    "name_suffix": "",
                    "institution": "Ruhr University Bochum",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24743/galley/21522/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24743/galley/14341/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24743/galley/18199/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24743/galley/21522/download/"
                }
            ]
        },
        {
            "pk": 21608,
            "title": "Rethinking Probabilities: Why Corpus Frequencies Cannot Capture Speakers' Dynamic Linguistic Behavior",
            "subtitle": null,
            "abstract": "Because information theory equates information with event occurrence probabilities, when applying its methods, language researchers typically take the information provided by words to be their relative frequencies in a corpus. This implicitly assumes words occur uniformly across contexts, however empirically, word distributions are bursty: the likelihood of most words appearing in most contexts is small, whereas the likelihood of a word recurring in context is much higher. In an elicitation study we examined whether speakers are sensitive to the dynamic word occurrence probabilities this implies. Consistent with proposals that prenominal adjectives increase noun predictability, participants produced numerous seemingly redundant adjectives prior to unambiguous nouns at first mention. However, despite receiving no feedback, they produced significantly fewer adjectives before subsequent mentions of the same nouns, indicating they had re-evaluated their probabilities. These results support the idea that prenominal adjectives facilitate efficient communication, and that speakers' representations of lexical probabilities are dynamic.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language Production; Language understanding; Predictive Processing"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2j30n0bn",
            "frozenauthors": [
                {
                    "first_name": "Santina",
                    "middle_name": "Simone",
                    "last_name": "Kemper",
                    "name_suffix": "",
                    "institution": "Humboldt Universität zu Berlin",
                    "department": ""
                },
                {
                    "first_name": "Holly",
                    "middle_name": "Elizabeth",
                    "last_name": "Jenkins",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Elizabeth",
                    "middle_name": "",
                    "last_name": "Wonnacott",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Ramscar",
                    "name_suffix": "",
                    "institution": "University of Tübingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21608/galley/11207/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21608/galley/22001/download/"
                }
            ]
        },
        {
            "pk": 21481,
            "title": "Reuse and Remixing in Question Asking Across Development",
            "subtitle": null,
            "abstract": "Question asking is a key tool for learning, especially in childhood. However, formulating good questions is challenging. In any given situation, many questions are possible but only few are informative. In the present work, we investigate two ways 5- to 10-year-olds and adults simplify the challenge of formulating questions: by reusing previous questions, and by remixing components of previous questions to form new questions. Our experimental results suggest that children and adults reuse and remix questions and adaptively modulate reuse depending on how informative a question will be in a particular situation. This work shows that task-relevant experience asking questions provides fodder for future questions, simplifying the challenge of inquiry and enabling effective learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Learning; Reasoning"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5vb4s3z5",
            "frozenauthors": [
                {
                    "first_name": "Emily",
                    "middle_name": "G",
                    "last_name": "Liquin",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Marjorie",
                    "middle_name": "",
                    "last_name": "Rhodes",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Todd",
                    "middle_name": "M",
                    "last_name": "Gureckis",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21481/galley/11080/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21481/galley/21926/download/"
                }
            ]
        },
        {
            "pk": 24193,
            "title": "Revealing human planning strategies with eye-tracking",
            "subtitle": null,
            "abstract": "Most recent research on human planning attempts to adjudicate between a small set of hypothesized models based on their ability to predict participants' choices, using carefully designed experiments and/or model comparison. Here, we propose an alternative approach. We designed a task in which gaze is highly indicative of participants' planning operations, allowing us to discover properties of human planning from eye-tracking data in a data-driven way. Our results reveal ways that people's planning strategies have both similarities and differences with classical planning algorithms like best-first search and Monte Carlo tree search. They also provide a more nuanced perspective on previously proposed properties of human planning like pruning and depth limits. We conclude that planning research would benefit greatly from an increased use of rich sources of data that provide more direct evidence about the internal processes underlying sequential decision-making.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Attention; Decision making; Problem Solving; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8sm0k8z2",
            "frozenauthors": [
                {
                    "first_name": "Frederick",
                    "middle_name": "",
                    "last_name": "Callaway",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Miaomiao",
                    "middle_name": "",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Marcelo",
                    "middle_name": "G",
                    "last_name": "Mattar",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24193/galley/13789/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24193/galley/21523/download/"
                }
            ]
        },
        {
            "pk": 24403,
            "title": "Revealing the Dynamics of Medical Diagnostic Reasoning as Step-by-Step Cognitive Process Trajectories",
            "subtitle": null,
            "abstract": "A detailed understanding of the cognitive process underlying diagnostic reasoning in medical experts is currently lacking. While high-level theories like hypothetico-deductive reasoning were proposed long ago, the inner workings of the step-by-step dynamics within the mind remain unknown. We present a fully automated approach to elicit, monitor, and record diagnostic reasoning processes at a fine-grained level. A web-based user interface enables physicians to carry out a full diagnosis process on a simulated patient, given as a pre-defined clinical vignette. By collecting the physician's information queries and hypothesis revisions, highly detailed diagnostic reasoning trajectories are captured leading to a diagnosis and its justification. Four expert epileptologists with a mean experience of 19 years were recruited to evaluate the system and share their impressions in semi-structured interviews. We find that the recorded trajectories validate proposed theories on broader diagnostic reasoning, while also providing valuable additional details extending previous findings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Case-based reasoning; Decision making; Reasoning; Case studies"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4qn3z59m",
            "frozenauthors": [
                {
                    "first_name": "Dominik",
                    "middle_name": "",
                    "last_name": "Battefeld",
                    "name_suffix": "",
                    "institution": "Research Center Cognitive Interaction Technology (CITEC), Bielefeld University",
                    "department": ""
                },
                {
                    "first_name": "Sigrid",
                    "middle_name": "",
                    "last_name": "Mues",
                    "name_suffix": "",
                    "institution": "Dpt. of Neurology, Ruhr-Epileptology",
                    "department": ""
                },
                {
                    "first_name": "Tim",
                    "middle_name": "",
                    "last_name": "Wehner",
                    "name_suffix": "",
                    "institution": "University Hospital Knappschaftskrankenhaus Bochum, Dept. of Neurology, Ruhr-Epileptology, Bochum",
                    "department": ""
                },
                {
                    "first_name": "Patrick",
                    "middle_name": "",
                    "last_name": "House",
                    "name_suffix": "",
                    "institution": "Epileptologicum Hamburg",
                    "department": ""
                },
                {
                    "first_name": "Christoph",
                    "middle_name": "",
                    "last_name": "Kellinghaus",
                    "name_suffix": "",
                    "institution": "Klinikum Osnabrück",
                    "department": ""
                },
                {
                    "first_name": "Jörg",
                    "middle_name": "",
                    "last_name": "Wellmer",
                    "name_suffix": "",
                    "institution": "University Hospital Knappschaftskrankenhaus Bochum, Dpt. of Neurology, Ruhr-Epileptology",
                    "department": ""
                },
                {
                    "first_name": "Stefan",
                    "middle_name": "",
                    "last_name": "Kopp",
                    "name_suffix": "",
                    "institution": "Bielefeld University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24403/galley/14000/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24403/galley/21524/download/"
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            ]
        },
        {
            "pk": 21522,
            "title": "Revisiting Joke Comprehension with Surprisal and Contextual Similarity: Implication from N400 and P600 Components",
            "subtitle": null,
            "abstract": "Recent studies link surprisal —a measure of conditional probability of words in context—to the N400 component size in event-related potentials (ERP), supporting a role for predictive coding in language comprehension. An alternative account argues that N400 variations are better explained by a retrieval mechanism sensitive to the semantic similarity between a word and its preceding context. Because jokes often rely on the presence of unexpected words that relate to the prior context multiple ways, they afford observation of the relative importance of contextual predictability and contextual similarity. We employed state-of-the-art machine learning to assess the surprisal and contextual semantic similarity of critical words in jokes and control stimuli. Using regression models to predict ERP, we found contextual similarity best explains N400 and P600 responses, supporting the semantic similarity account. Additionally, jokes elicit enhanced N400 and P600 responses that go beyond that attributable to their surprisal and contextual semantic similarity.",
            "language": null,
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; cognitive neuropsychology; Language understanding; Semantics; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/01n9j76q",
            "frozenauthors": [
                {
                    "first_name": "Haoyin",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Masaki",
                    "middle_name": "",
                    "last_name": "Nakanishi",
                    "name_suffix": "",
                    "institution": "1986",
                    "department": ""
                },
                {
                    "first_name": "Seana",
                    "middle_name": "",
                    "last_name": "Coulson",
                    "name_suffix": "",
                    "institution": "UC San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21522/galley/11121/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21522/galley/14598/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21522/galley/21525/download/"
                }
            ]
        },
        {
            "pk": 21628,
            "title": "Revisiting the effects of interword spacing and root frequency in Arabic visual processing",
            "subtitle": null,
            "abstract": "In this study we investigated the role of interword spacing and its interaction with Arabic root frequencies by studying readers' eye movement patterns when they read Arabic sentences. Our eye-tracking experiment results did not show any significant evidence for the interword spacing effect on Arabic word processing, which concurred with the earlier work by Leung et al. (2021). On the other hand, we replicated an earlier experiment conducted by Hermena et al. (2020) on the effect of Arabic root frequencies on word processing. Contrary to their finding, our results showed that words which differed in root frequencies significantly modulated eye movement measures. This provided another support to the status of Arabic non-concatenative roots as a morphological unit.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Morphology; Reading; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3td452x0",
            "frozenauthors": [
                {
                    "first_name": "Tommi",
                    "middle_name": "",
                    "last_name": "Leung",
                    "name_suffix": "",
                    "institution": "United Arab Emirates University",
                    "department": ""
                },
                {
                    "first_name": "Fatima",
                    "middle_name": "",
                    "last_name": "Boush",
                    "name_suffix": "",
                    "institution": "United Arab Emirates University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21628/galley/11227/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21628/galley/14536/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21628/galley/22041/download/"
                }
            ]
        },
        {
            "pk": 24636,
            "title": "Revisiting the Role of Observational Contexts for Learning Hard Nouns",
            "subtitle": null,
            "abstract": "Children learn words that name objects (“ball”) and those that name abstract concepts (“story”). One view of learning is that different inputs matter for different words (Snedeker & Gleitman, 2004). That is, many argue that although the observational contexts in which words occur are sufficient for learning object names, they are not for learning abstract “hard words” (Gleitman et al., 2005). This study revisited the contributions of observational contexts to learning one type of hard word: nouns denoting non-basic level object categories (“hard nouns” like “friend”; Kako, 2005). In a new artificial learning paradigm, we reveal that although observational contexts were insufficient for full hard noun learning, they afforded learners partial knowledge that allowed them to succeed in some learning tasks. These data highlight how observational contexts may lay the foundation for learning hard nouns, and underscore how definitions of learning impact our understanding of how the input shapes it.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Language development; Language learning; Semantic memory; Statistical learning"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5sq0r262",
            "frozenauthors": [
                {
                    "first_name": "Kosta",
                    "middle_name": "",
                    "last_name": "Boskovic",
                    "name_suffix": "",
                    "institution": "University of Connecticut",
                    "department": ""
                },
                {
                    "first_name": "Sumarga",
                    "middle_name": "H.",
                    "last_name": "Suanda",
                    "name_suffix": "",
                    "institution": "University of Connecticut",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24636/galley/21526/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24636/galley/14233/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24636/galley/18013/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24636/galley/21526/download/"
                }
            ]
        },
        {
            "pk": 24067,
            "title": "Reward Count(s): Negative Recency in Probabilistic Experience-Based Learning",
            "subtitle": null,
            "abstract": "Learning how to make decisions from experience is often studied using probabilistic outcome prediction or choice tasks, as in conditioning, reward learning, or risky gambles (e.g., response A provides reward in 75% of the cases, response B in 25% over repeated trials with feedback). One debated phenomenon in such tasks is that of negative recency, describing that learners expect the rare event after observing a streak of common events (e.g., Gamblers fallacy). Here, we show that this behavior, despite instructing participants to use a visual stimulus, also occurs in probabilistic single-cue conditioning training, where participants predicted whether digging at a specific location on a plane (visual cue) leads to finding a Vase or Nothing (events), when they received reward for correct predictions. We manipulated reward magnitude in three conditions (equal for both common and rare events vs. high for common event vs. high for rare event, between factor). We further manipulated whether the label of the rare event was framed as event (finding a Vase) or non-event (finding Nothing; between factor). The results suggest, that reward magnitude affected the emergence of negative recency, being most prevalent when correctly predicting the rare event yielded a high reward, and least prevalent when the common event yielded a high reward. Interestingly, the event label instead rather affected when the rare event was expected, such that common Vase runs were expected to end earlier than common Nothing runs. We discuss the findings from conditioning and economic perspectives, generally concerning experience-based learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Decision making; Learning; Statistical learning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4c20293n",
            "frozenauthors": [
                {
                    "first_name": "René",
                    "middle_name": "",
                    "last_name": "Schlegelmilch",
                    "name_suffix": "",
                    "institution": "University of Bremen",
                    "department": ""
                },
                {
                    "first_name": "Andy",
                    "middle_name": "J",
                    "last_name": "Wills",
                    "name_suffix": "",
                    "institution": "Plymouth University",
                    "department": ""
                },
                {
                    "first_name": "Bettina",
                    "middle_name": "",
                    "last_name": "von Helversen",
                    "name_suffix": "",
                    "institution": "University of Bremen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24067/galley/13661/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24067/galley/21527/download/"
                }
            ]
        },
        {
            "pk": 24369,
            "title": "Risky Decisions from Personal and Observed Experience",
            "subtitle": null,
            "abstract": "People often learn about risks from other people. In the current study, we investigated the impact of social learning on risky decisions from experience by incorporating direct observational learning. Participants were placed in pairs – one participant observed the other participant sampling from different options, and then both made decisions based on this personal/observed experience. Participants tended to underweight rare outcomes less when learning from observed experience, particularly with high-value rare outcomes. This difference was not reliably significant, however, suggesting a subtle effect. The study discusses potential contributing factors such as active hypothesis testing, psychological distance, social environment, competitiveness, and goal alignment to explain the results. Overall, the findings contribute to understanding the dynamics of social learning in risky decision-making.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision making; Learning; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/77v8h56g",
            "frozenauthors": [
                {
                    "first_name": "Alina",
                    "middle_name": "",
                    "last_name": "Gutoreva",
                    "name_suffix": "",
                    "institution": "Kazakh-British Technical University",
                    "department": ""
                },
                {
                    "first_name": "Elliot",
                    "middle_name": "Andrew",
                    "last_name": "Ludvig",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24369/galley/13966/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24369/galley/21528/download/"
                }
            ]
        },
        {
            "pk": 24488,
            "title": "Roles guide rapid inferences about agent knowledge and behavior",
            "subtitle": null,
            "abstract": "The ability to predict and understand other people's actions is critical for real-world social behavior. Here we hypothesized that representations of social roles (e.g., cashier, mechanic, doctor) enable people to build rapid expectations about what others know and how they might act. Using a self-paced reading paradigm and a variety of everyday roles, we show that the mere mention of a role (e.g., “mechanic”) supports real time expectations about what the person will do (e.g., in the mechanic case, take your car keys but not your cellphone) and the knowledge they might possess (e.g., in the mechanic case, having private information about your car). Moreover, people reported more surprisal when the events deviated from role expectations, and they were more likely to misremember what happened. Our results suggest that roles are a powerful route for social understanding that has been previously understudied in social cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Predictive Processing; Representation; Social cognition; Theory of Mind"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1ph8n2kk",
            "frozenauthors": [
                {
                    "first_name": "Aaron",
                    "middle_name": "",
                    "last_name": "Baker",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Yarrow",
                    "middle_name": "",
                    "last_name": "Dunham",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24488/galley/21529/download/"
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            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24488/galley/14085/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24488/galley/21529/download/"
                }
            ]
        },
        {
            "pk": 24722,
            "title": "Rounding and magnitude: Pragmatic halos are bigger for larger numbers",
            "subtitle": null,
            "abstract": "Round numbers are often interpreted approximately (Krifka, 2002), with \"pragmatic halos\" (Lasersohn, 1999) that encompass multiple permissible values. For example, stating \"there were 200 people at the meeting\" would be acceptable even if the exact count were 197 or 204. In line with the idea that larger numbers have more approximate representations (e.g., Cheyette & Piantadosi, 2020), we demonstrate that rounding and pragmatic halos are magnitude-dependent. First, an analysis of every single number in two large corpora (COCA, BNC) shows that indicators of rounding predict frequency (cf. Woodin et al., 2023), but crucially in interaction with magnitude, with round numbers over-represented for larger magnitudes. Second, we show that jigsaw puzzles often systematically deviate from what is advertised on the box in a way that depends on magnitude, e.g., a 1,000-piece puzzle may contain 1,024 pieces, whereas a 50-piece puzzle is more likely to contain the stated value exactly.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Other; Psychology; Language and thought; Other; Pragmatics; Representation; Corpus studies"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3dw7t70n",
            "frozenauthors": [
                {
                    "first_name": "Bodo",
                    "middle_name": "",
                    "last_name": "Winter",
                    "name_suffix": "",
                    "institution": "University of Birmingham",
                    "department": ""
                },
                {
                    "first_name": "Greg",
                    "middle_name": "",
                    "last_name": "Woodin",
                    "name_suffix": "",
                    "institution": "University of Birmingham",
                    "department": ""
                },
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Lorson",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
                "label": "PDF",
                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24722/galley/21530/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24722/galley/14320/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24722/galley/18177/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24722/galley/21530/download/"
                }
            ]
        },
        {
            "pk": 21626,
            "title": "Saccadic Eye Movements and Search Task Difficulty as Basis of Modelling User Knowledge in Information Seeking",
            "subtitle": null,
            "abstract": "Designing user-adaptive search systems necessitates modeling the user's knowledge state during information seeking. Gaze data offers insights into cognitive processes during task-based reading. Despite its potential, cognitive perspectives have been insufficiently explored in the representation of the user's knowledge state when designing search systems. We reanalyzed an eye-tracking dataset and constructed mixed-effects user models to identify which measurements of gaze activities (i.e., gaze metrics captured by eye trackers) are reflective of the user. Our study's findings indicate that there are statistically significant correlations between gaze metrics that measure the variability of saccadic eye movement and search performance. The accuracy of answers has been significantly influenced by the interaction between the control of saccade trajectories, measured by the standard deviation of absolute saccadic directions and the difficulty of the search task. We discuss the implications of these findings for the design of search systems adaptable to the user's state of knowledge.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Human Factors; Predictive Processing; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3ws2g8qm",
            "frozenauthors": [
                {
                    "first_name": "Ying-Hsang",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "Uppsala University",
                    "department": ""
                },
                {
                    "first_name": "Andreas",
                    "middle_name": "",
                    "last_name": "Nürnberger",
                    "name_suffix": "",
                    "institution": "Otto von Guericke University",
                    "department": ""
                },
                {
                    "first_name": "Jenny",
                    "middle_name": "",
                    "last_name": "Rettstatt",
                    "name_suffix": "",
                    "institution": "Chemnitz University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Marco",
                    "middle_name": "",
                    "last_name": "Ragni",
                    "name_suffix": "",
                    "institution": "TU Chemnitz",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21626/galley/11225/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21626/galley/14534/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21626/galley/22042/download/"
                }
            ]
        },
        {
            "pk": 24419,
            "title": "Same Same But Different: The Influence of Ambiguity Awareness on Speech and Gesture Production",
            "subtitle": null,
            "abstract": "We explored (1) the differences in prosody and gesture when speakers were aware and unaware of ambiguities, and (2) the insight of multimodal ambiguity resolution on communication efficiency. Thirty-two Mandarin speakers articulated twenty-two ambiguous Mandarin sentences. Half could be disambiguated using prosody (half couldn't). First, participants articulated each sentence and explained its meaning to a confederate, revealing their dominant interpretation and ambiguity awareness. Second, participants articulated the same ambiguous sentences twice according to hints indicating two meanings. Results showed participants hardly realised ambiguities. Speakers produced mostly more prominent prosody and more gestures when recognising ambiguities. When ambiguity was aware, prosodically unambiguous sentences were produced with various prosodic cues, with referential and non-referential gestures. However, prosodically ambiguous sentences were produced with more referential but hardly any non-referential gestures. In conclusion, speakers adopt multimodal strategies to achieve communication efficiency with a trade-off between modalities, depending on their ambiguity awareness.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language Production; Pragmatics; Gesture analysis; Statistics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3hn9k2h6",
            "frozenauthors": [
                {
                    "first_name": "Jiajun",
                    "middle_name": "",
                    "last_name": "GAO",
                    "name_suffix": "",
                    "institution": "University of Nottingham Ningbo China",
                    "department": ""
                },
                {
                    "first_name": "Yan",
                    "middle_name": "",
                    "last_name": "Gu",
                    "name_suffix": "",
                    "institution": "University of Essex",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24419/galley/14016/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24419/galley/21531/download/"
                }
            ]
        },
        {
            "pk": 24240,
            "title": "Schema Drift: Relational Concept Stability Across Repeated Comparison",
            "subtitle": null,
            "abstract": "Analogical reasoning is one of the most common ways individuals bring previous experience to bear on unfamiliar situations. Most theories describe this process as a structured comparison that involves mapping the relational properties between a familiar source and unfamiliar target. This both allows the transfer of useful inferences from the source to the target and highlights the common structure shared by both analogs, represented by an abstract schema. This schema can help with identifying and reasoning about structurally similar situations in the future. While researchers have studied how representations of source and target analogs undergo alterations as a result of this mapping process, little attention has been paid to how the abstract schemas thought to guide future analogical reasoning might similarly change with use. We explore this question in two experiments and present evidence that suggests abstract schemas do indeed drift under certain conditions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Analogy; Concepts and categories; Representation"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9sv0h8x9",
            "frozenauthors": [
                {
                    "first_name": "Richard",
                    "middle_name": "",
                    "last_name": "Vagnino",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                },
                {
                    "first_name": "Caren",
                    "middle_name": "M.",
                    "last_name": "Walker",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24240/galley/13836/download/"
                },
                {
                    "label": "PDF",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24240/galley/21532/download/"
                }
            ]
        },
        {
            "pk": 24274,
            "title": "Searching for Argument-Counterargument Relationships in Vector Embedding Spaces",
            "subtitle": null,
            "abstract": "Vector embedding spaces are representational structures that can capture both the similarity relationship between items and various other semantic relationships. Current state-of-the-art embedding models can generate embedding vectors for individual words and longer strings of text, enabling vector spaces to encode the similarity between entire documents of text. We investigated three embedding models to see if semantic relationships besides similarity are represented in these spaces across three embedding models, focusing on the relationship between arguments and counterarguments as a specific example. While there was not a linear subspace that captured the semantic relationship between an argument and its counterargument, we found that neural networks with a single hidden layer could partially learn the transformations between an argument's embedding and the corresponding counterargument's embedding in all three spaces. The trained models generalized across three different datasets of arguments, suggesting these partially learned transformations are applicable to arguments and counterarguments in general, not just tied to the semantic context of the models' training dataset. This approach has practical applications in designing information retrieval systems for intelligent agents and, potentially, in models of cognition that use vector embedding spaces as a representational structure.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Natural Language Processing; Semantics; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/56j610vg",
            "frozenauthors": [
                {
                    "first_name": "Cherrie",
                    "middle_name": "",
                    "last_name": "Chang",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                },
                {
                    "first_name": "Josh",
                    "middle_name": "",
                    "last_name": "de Leeuw",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24274/galley/13870/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24274/galley/21533/download/"
                }
            ]
        },
        {
            "pk": 24781,
            "title": "Searching for Functional Boundaries: Evaluating Effectiveness in Complex Adaptive Networks with Cognitive Dynamics.",
            "subtitle": null,
            "abstract": "The research focus on adaptivity in complex systems has propelled an exploration of diverse interactions characterized by state transition processes. However, the investigation of functional variances among processes, rooted in fundamental operands, remains insufficient. Recognizing this gap is crucial for unveiling the constituents of state transitions and their functional boundaries during ongoing adaptivity. To address this, our central focus is on quantifying the functional variance in the interactions of fundamental operands. This approach enables a systematic study of complex adaptive networks grounded in the dynamics of cognitive abilities, where elements adapt and evolve based on cognitive processes. To underscore this point, we emphasize translating ontologically irreducible networks into functionally representable ones at the meso-level, which is essential for assessing their effectiveness. Our active investigation during state transitions explores external interventions, aiming to shed light on mutual influences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Other; Philosophy; Action; Causal reasoning; Complex systems; Concepts and categories; Dynamical Systems; Embodied Cognition"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9vx7r5mh",
            "frozenauthors": [
                {
                    "first_name": "Kiran",
                    "middle_name": "",
                    "last_name": "Pala",
                    "name_suffix": "",
                    "institution": "University of Eastern Finland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24781/galley/21534/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24781/galley/14379/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24781/galley/18236/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24781/galley/21534/download/"
                }
            ]
        },
        {
            "pk": 21447,
            "title": "Second Order Uncertainty and Prospect Theory",
            "subtitle": null,
            "abstract": "Prospect Theory has been highly influential; however its experimental paradigm lacks higher orders of uncertainty. To introduce this, participants are asked to imagine themselves facing a choice between two bags containing 100,000 blue or red balls in unknown proportions. A red ball wins £500. Participants are shown samples from each bag; e.g., 5 balls from Bag 1 (3 red) and 100 balls from Bag 2 (55 red). The bags can be represented by distributions with Bag 1 having a higher mean probability estimate (60% vs 55%), but more variance (second order uncertainty) in that estimate. By varying observed frequencies and gain vs loss formats, we seek to determine if classic findings remain when higher order uncertainties are present. Results consistent with the four-fold pattern are seen for gains (uncertainty seeking at low probability values, uncertainty aversion at high probability values) but for losses, uncertainty aversion is seen at all values.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; cognitive neuropsychology; Decision making; Reasoning; Qualitative Analysis; Statistics"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6484281j",
            "frozenauthors": [
                {
                    "first_name": "Stephen",
                    "middle_name": "H",
                    "last_name": "Dewitt",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Michelle",
                    "middle_name": "",
                    "last_name": "Lam",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Andy",
                    "middle_name": "",
                    "last_name": "Shi",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Borys",
                    "middle_name": "",
                    "last_name": "Tam",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Samuel",
                    "middle_name": "Henri",
                    "last_name": "Dupret",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Toby",
                    "middle_name": "D",
                    "last_name": "Pilditch",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Lagnado",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21447/galley/11046/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21447/galley/21892/download/"
                }
            ]
        },
        {
            "pk": 24815,
            "title": "Seeing speech: Cerebral mecanisms of Cued Speech perception",
            "subtitle": null,
            "abstract": "Most alphabets are based on visual coding of phonemes and syllables, and similar visual codes were developed for visually conveying the sounds of speech to deaf people. Notably, Cued Speech (CS) allows for syllables to be specified by a combination of lip configuration, hand location and hand shape. The use of this communication system has been proven to improve general language skills in a deaf community characterized by low literacy. Meanwhile, the mechanisms of CS perception remain largely unknown.\nIn an fMRI study involving 3 groups of participants (deaf and hearing people proficient in CS and a group of hearing people naïve to CS), we identify the brain areas that process and, more specifically, encode the various components of CS. Particular attention is given to the role of expertise, and to the links between CS and reading, two coexisting visual codes for language that both compete and support each other.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Language Production; Language understanding; Perception; Reading; Speech recognition; fMRI"
                }
            ],
            "section": "Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1qt5r1fk",
            "frozenauthors": [
                {
                    "first_name": "Annahita",
                    "middle_name": "",
                    "last_name": "Sarré",
                    "name_suffix": "",
                    "institution": "Institut du Cerveau",
                    "department": ""
                },
                {
                    "first_name": "Laurent",
                    "middle_name": "",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Institut du Cerveau",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": {
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                "type": "pdf",
                "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24815/galley/21535/download/"
            },
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24815/galley/14413/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24815/galley/18270/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/24815/galley/21535/download/"
                }
            ]
        },
        {
            "pk": 21350,
            "title": "Selective maintenance of negative memories as a mechanism of spontaneous recovery of fear after extinction",
            "subtitle": null,
            "abstract": "Spontaneous recovery of fear after extinction is a well-established behavioral phenomenon. Different theories in psychology account for spontaneous recovery by proposing that it may result from temporal weighting, reduced processing of stimuli over time, enhanced salience of adverse events or return of the acquisition context. We propose a novel mechanism of spontaneous recovery: selective maintenance of adverse events, and ground this mechanism in a computational model of latent cause inference. To investigate the proposed mechanism, we collected behavioral data with an aversive conditioning and extinction task (N=280) and fit the data with computational models formalizing our and others' theories. Quantitative and qualitative model comparisons indicated that selective maintenance of adverse events accounts for spontaneous recovery better than alternative theories. As spontaneous recovery of fear after extinction can serve as a model of relapse after exposure therapy, we use this mechanistic understanding of spontaneous recovery to propose and simulate the effect of add-on interventions to prevent relapse after exposure therapy.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Emotion Disorder; Memory; Representation; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3mj8q8kx",
            "frozenauthors": [
                {
                    "first_name": "Isabel",
                    "middle_name": "",
                    "last_name": "Berwian",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Sashank",
                    "middle_name": "",
                    "last_name": "Pisupati",
                    "name_suffix": "",
                    "institution": "Limbic Ltd",
                    "department": ""
                },
                {
                    "first_name": "Jamie",
                    "middle_name": "Chin",
                    "last_name": "Chiu",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Yongjing",
                    "middle_name": "",
                    "last_name": "Ren",
                    "name_suffix": "",
                    "institution": "Rutgers University",
                    "department": ""
                },
                {
                    "first_name": "Yael",
                    "middle_name": "",
                    "last_name": "Niv",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2024-01-01T19:00:00+01:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21350/galley/10949/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/21350/galley/21795/download/"
                }
            ]
        }
    ]
}