API Endpoint for journals.

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        {
            "pk": 49187,
            "title": "Agent Preference in Children: The Role of Animacy and Event Coherence",
            "subtitle": null,
            "abstract": "<p>Thematic roles in language (Agents, Patients) are considered to be hierarchically organized in terms of their salience, and this hierarchy is rooted in their counterparts as event participants in cognition. Here, we examine the relative salience of Agents over Patients in two-participant causative events in Turkish-speaking 3- to 5-year-old children. We also test if this asymmetry is modulated by the animacy of the Patient (human vs. inanimate object) and specific to the presence of a coherent event. In an eye-tracked change detection task, changes to Agents were detected more accurately (and after fewer fixations) than changes to inanimate Patients when there was a coherent event. This asymmetry disappeared when the Patient was animate (for accuracy) and when event coherence was disrupted (for both accuracy and fixations). These findings suggest an interplay of event roles and animacy in Agent preference.</p>",
            "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/8b7723hj",
            "frozenauthors": [
                {
                    "first_name": "Ceren",
                    "middle_name": "",
                    "last_name": "Barış",
                    "name_suffix": "",
                    "institution": "Özyeğin University",
                    "department": ""
                },
                {
                    "first_name": "Ercenur",
                    "middle_name": "",
                    "last_name": "Ünal",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Psycholinguistics",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49187/galley/37148/download/"
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                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49187/galley/38693/download/"
                }
            ]
        },
        {
            "pk": 50474,
            "title": "Age-related changes in cognitive flexibility: fMRI meta-analysis",
            "subtitle": null,
            "abstract": "<p>To examine neural mechanisms underlying cognitive flexibility changes with ageing, we synthesized findings from 87 fMRI studies, comprising 120 experiments with 2308 adult participants distributed across young, middle-age, and older groups. Our meta-analysis was focused on rule-retrieval and rule-discovery processes, assessed with Task-Switching Paradigm and Wisconsin Card Sorting Test, respectively. Activation Likelihood Estimation analyses revealed age-related decreases in brain activation related to general switching ability, particularly in posterior regions, alongside an anterior shift in older adults, consistent with the Posterior-Anterior Shift in Aging (PASA) model. Rule-retrieval tasks consistently engaged left-lateralized frontoparietal regions across all age groups, with middle-age adults additionally recruiting the right cerebellum and medial-frontal gyrus. For rule-discovery tasks, age-related decline was observed in bilateral frontoparietal regions, while older adults also showed unique activation in the left inferior-frontal gyrus. These findings highlight differential ageing trajectories for rule retrieval and rule discovery, potentially reflecting compensatory neural mechanisms and dedifferentiation processes.</p>",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Neuroscience; Psychology; Cognitive development; Development; Other; fMRI"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0zn5r8z3",
            "frozenauthors": [
                {
                    "first_name": "Zhanna",
                    "middle_name": "",
                    "last_name": "Chuikova",
                    "name_suffix": "",
                    "institution": "HSE University",
                    "department": ""
                },
                {
                    "first_name": "Andrei",
                    "middle_name": "",
                    "last_name": "Faber",
                    "name_suffix": "",
                    "institution": "HSE University",
                    "department": ""
                },
                {
                    "first_name": "Andrei",
                    "middle_name": "",
                    "last_name": "Filatov",
                    "name_suffix": "",
                    "institution": "HSE University",
                    "department": ""
                },
                {
                    "first_name": "Andriy",
                    "middle_name": "",
                    "last_name": "Myachykov",
                    "name_suffix": "",
                    "institution": "University of Macau",
                    "department": ""
                },
                {
                    "first_name": "Yury",
                    "middle_name": "",
                    "last_name": "Shtyrov",
                    "name_suffix": "",
                    "institution": "Aarhus University",
                    "department": ""
                },
                {
                    "first_name": "Marie",
                    "middle_name": "",
                    "last_name": "Arsalidou",
                    "name_suffix": "",
                    "institution": "York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50474/galley/38436/download/"
                }
            ]
        },
        {
            "pk": 49314,
            "title": "Age-related differences in forming conjunctive memories of what, when and where",
            "subtitle": null,
            "abstract": "Aging greatly affects memory, but not all aspects are impaired equally. Past research has demonstrated that older adults show greater deficits in remembering where an object was encountered compared to what was experienced. A third dimension, that has received less attention in this context is memory for when events occurred. In this study, we employed a Sequential Memory Task (SMT) in which participants memorized spatio-temporal visual object sequences over repeated exposures. In two experiments with 39 younger (YAs, 18-35 years) and 53 older adults (OAs, 65-75 years), we examined age-related differences in sequence memory (when) and the interplay between item (what), and location (where) knowledge. Our results revealed that memory was stronger for item sequences than for location sequences or item-location combinations in both younger and older adults. In addition, older adults exhibited greater age-related deficits in location-related memory. We also found that item and location memory were bi-directionally related and that even pure item sequence reports involved location memory and vice versa. Both age groups relied more on item-location binding associations than on transition learning, but computational modeling indicated a higher reliance on independent location transition learning in OAs than YAs. This suggests that the strong age-related impairment in spatial location memory was in part driven by age-differences in memory binding. These findings provide insights into age-related changes in spatio-temporal sequence memory, and highlight distinct learning strategies in younger and older adults.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Learning; Memory; Comparative Studies; Computational Modeling; Knowledge representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/92r8t53q",
            "frozenauthors": [
                {
                    "first_name": "Xiangjuan",
                    "middle_name": "",
                    "last_name": "Ren",
                    "name_suffix": "",
                    "institution": "UniversitŠt Hamburg",
                    "department": ""
                },
                {
                    "first_name": "Marit",
                    "middle_name": "",
                    "last_name": "Petzka",
                    "name_suffix": "",
                    "institution": "UniversitŠt Hamburg",
                    "department": ""
                },
                {
                    "first_name": "Nicolas",
                    "middle_name": "",
                    "last_name": "Schuck",
                    "name_suffix": "",
                    "institution": "UniversitŠt Hamburg",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49314/galley/37275/download/"
                }
            ]
        },
        {
            "pk": 49566,
            "title": "Age-related differences in processing event knowledge during real-time language comprehension",
            "subtitle": null,
            "abstract": "To understand language, we use knowledge about everyday events to create rich internal (situation) models. Although knowledge increases with age, fluid cognitive abilities tend to decline, potentially making it more difficult to access that knowledge. Here, we asked how aging affects the ability to use event knowledge during real-time language comprehension. We recorded event-related brain potentials as younger and older adults read vignettes about everyday events. Both groups showed facilitation on the N400 (a neuroelectric marker of semantic processing) for words that fit the context. However, only younger adults showed facilitated N400s to anomalous but event-related words compared to unrelated anomalies. Among older adults (aged 53-80), there was a negative correlation between age and N400 effects of event-relatedness. We conclude that real-time access to event knowledge during language comprehension may shift across the course of the adult lifespan such that older adults restrict activation to the most immediately relevant content.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Cognitive development; Language Comprehension; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0hq6k684",
            "frozenauthors": [
                {
                    "first_name": "Melissa",
                    "middle_name": "",
                    "last_name": "Troyer",
                    "name_suffix": "",
                    "institution": "University of Nevada Las Vegas",
                    "department": ""
                },
                {
                    "first_name": "Rachel",
                    "middle_name": "",
                    "last_name": "Myers",
                    "name_suffix": "",
                    "institution": "University of Illinois at Urbana-Champaign",
                    "department": ""
                },
                {
                    "first_name": "Kara",
                    "middle_name": "D.",
                    "last_name": "Federmeier",
                    "name_suffix": "",
                    "institution": "University of Illinois",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49566/galley/37528/download/"
                }
            ]
        },
        {
            "pk": 50361,
            "title": "A Graph Theory Approach to the Bidialectical Nature of English",
            "subtitle": null,
            "abstract": "The English lexicon is a creole consisting of early-learned Anglo-Saxon (AS) words and late-learned Latinate (LA) words with some other origins at lower frequency.  The creole nature of the lexicon is most evident in pronunciation rules. We pair etymological and age of acquisition data for ~20,000 English words with phonological and semantic networks to study word organization over time.   Analyses reveal dramatic sound and meaning shifts over time in the most densely connected cores of the graphs. Phonologically, there is a shift in middle school from AS \"air\" words to LA \"ale\" words.  Semantically, the dense core shifts from an AS/LA balanced set of food and number words to medicinal and chemical terms between junior high and high school. These shifts are evident in monolinguals.  This AS to LA shift also affects individuals from diverse language backgrounds, especially L2 English learners from L1 Latinate (e.g., Spanish) and non-Latinate languages.  The implications of our findings will be discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Complex systems; Language acquisition; Phonology; Semantic memory"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4fz9z168",
            "frozenauthors": [
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "Brown",
                    "name_suffix": "",
                    "institution": "Oregon State University",
                    "department": ""
                },
                {
                    "first_name": "My",
                    "middle_name": "V. H.",
                    "last_name": "Nguyen",
                    "name_suffix": "",
                    "institution": "University of Houston",
                    "department": ""
                },
                {
                    "first_name": "Arturo",
                    "middle_name": "E.",
                    "last_name": "Hernandez",
                    "name_suffix": "",
                    "institution": "University of Houston",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50361/galley/38323/download/"
                }
            ]
        },
        {
            "pk": 49258,
            "title": "AI-enhanced semantic feature norms for 786 concepts",
            "subtitle": null,
            "abstract": "Semantic feature norms have been foundational in the study\nof human conceptual knowledge, yet traditional methods face\ntrade-offs between concept/feature coverage and verifiability\nof quality due to the labor-intensive nature of norming studies.\nHere, we introduce a novel approach that augments a dataset\nof human-generated feature norms with responses from large\nlanguage models (LLMs) while verifying the quality of norms\nagainst reliable human judgments. We find that our AI-enhanced\nfeature norm dataset, NOVA: Norms Optimized\nVia AI, shows much higher feature density and overlap\namong concepts while outperforming a comparable human-only\nnorm dataset and word-embedding models in predicting\npeople's semantic similarity judgments. Taken together, we\ndemonstrate that human conceptual knowledge is richer than\ncaptured in previous norm datasets and show that, with proper\nvalidation, LLMs can serve as powerful tools for cognitive\nscience research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Concepts and categories; Representation; Semantic memory; Knowledge representation"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/83q779kc",
            "frozenauthors": [
                {
                    "first_name": "Siddharth",
                    "middle_name": "",
                    "last_name": "Suresh",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Kushin",
                    "middle_name": "",
                    "last_name": "Mukherjee",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Tyler",
                    "middle_name": "",
                    "last_name": "Giallanza",
                    "name_suffix": "",
                    "institution": "Princeton Neuroscience Institute",
                    "department": ""
                },
                {
                    "first_name": "Mia",
                    "middle_name": "",
                    "last_name": "Patil",
                    "name_suffix": "",
                    "institution": "University of Wisconsin Madison",
                    "department": ""
                },
                {
                    "first_name": "Xizheng",
                    "middle_name": "",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Timothy",
                    "middle_name": "T",
                    "last_name": "Rogers",
                    "name_suffix": "",
                    "institution": "University of Wisconsin- Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49258/galley/37219/download/"
                }
            ]
        },
        {
            "pk": 49145,
            "title": "AIPsychoBench: Understanding the Psychometric Differences between LLMs and Humans",
            "subtitle": null,
            "abstract": "Large Language Models (LLMs) with hundreds of billions of parameters have exhibited human-like intelligence by learning from vast amounts of internet-scale data. However, the uninterpretability of large-scale neural networks raises concerns about the reliability of LLM. Studies have attempted to assess the psychometric properties of LLMs by borrowing concepts from human psychology to enhance their interpretability, but they fail to account for the fundamental differences between LLMs and humans. This results in high rejection rates when human scales are reused directly. Furthermore, these scales do not support the measurement of LLM psychological property variations in different languages. This paper introduces AIPsychoBench, a specialized benchmark tailored to assess the psychological properties of LLM. It uses a lightweight role-playing prompt to bypass LLM alignment, improving the average effective response rate from 70.12% to 90.40%. Meanwhile, the average biases are only 3.3% (positive) and 2.1% (negative), which are significantly lower than the biases of 9.8% and 6.9%, respectively, caused by traditional jailbreak prompts. Furthermore, among the total of 112 psychometric subcategories, the score deviations for seven languages compared to English ranged from 5% to 20.2% in 43 subcategories, providing the first comprehensive evidence of the linguistic impact on the psychometrics of LLM.",
            "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/39k8f46q",
            "frozenauthors": [
                {
                    "first_name": "Wei",
                    "middle_name": "",
                    "last_name": "Xie",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Shuoyoucheng",
                    "middle_name": "",
                    "last_name": "Ma",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Zhenhua",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Xiaobing",
                    "middle_name": "",
                    "last_name": "Sun",
                    "name_suffix": "",
                    "institution": "Agency for Science, Technology and Research",
                    "department": ""
                },
                {
                    "first_name": "Kai",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "University of Chinese Academy of Sciences",
                    "department": ""
                },
                {
                    "first_name": "Enze",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "College of Computer Science and Technology, National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Wei",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "College of Computer Science and Technology",
                    "department": ""
                },
                {
                    "first_name": "Hanying",
                    "middle_name": "",
                    "last_name": "Tong",
                    "name_suffix": "",
                    "institution": "College of Computer Science and Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49145/galley/37106/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49145/galley/38651/download/"
                }
            ]
        },
        {
            "pk": 49324,
            "title": "Algorithmic representations in the human brain that underlie schema generalisation",
            "subtitle": null,
            "abstract": "The human brain represents structure in the external world as \"cognitive maps\". However, it remains unknown how it represents structure in one's own behaviour. Recent findings show rodent medial-prefrontal cortex (mPFC) does this with a structure-sensitive representation, where all future actions are represented simultaneously. Here, using 7T fMRI, we test for this representation and its properties in humans. Using RSA and a computational model, we show this representation in mPFC and orbitofrontal cortex, while entorhinal and orbitofrontal cortices contain a pure abstraction of task structure. Preceding the future actions representation, action plans are ‘loaded' to mPFC once subjects were given all action-relevant information, suggestively through replay. iEEG data of patients solving the same task shows that sharp-wave ripple rate is increased during this planning time. Together, our findings suggest an algorithm of how human mPFC encodes future actions, and provide evidence for a replay-based mechanism of loading that representation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Action; Cognitive architectures; Decision making; Memory; Spatial cognition; Computational Modeling; Electroencephalography (EEG); fMRI"
                }
            ],
            "section": "Abstracts with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8vz352cz",
            "frozenauthors": [
                {
                    "first_name": "Svenja",
                    "middle_name": "",
                    "last_name": "KŸchenhoff",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Alon",
                    "middle_name": "",
                    "last_name": "Baram",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Mohamady",
                    "middle_name": "",
                    "last_name": "El-Gaby",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Mathias",
                    "middle_name": "",
                    "last_name": "SablŽ-Meyer",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Harris",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Jacob",
                    "middle_name": "",
                    "last_name": "Bakermans",
                    "name_suffix": "",
                    "institution": "Geneva University Neurocenter",
                    "department": ""
                },
                {
                    "first_name": "Shraddha",
                    "middle_name": "",
                    "last_name": "Shah",
                    "name_suffix": "",
                    "institution": "Baylor College of Medicine",
                    "department": ""
                },
                {
                    "first_name": "Eleonora",
                    "middle_name": "",
                    "last_name": "Bartoli",
                    "name_suffix": "",
                    "institution": "Baylor College of Medicine",
                    "department": ""
                },
                {
                    "first_name": "Andrew",
                    "middle_name": "",
                    "last_name": "Watrous",
                    "name_suffix": "",
                    "institution": "Baylor College of Medicine",
                    "department": ""
                },
                {
                    "first_name": "Adrish",
                    "middle_name": "",
                    "last_name": "Anand",
                    "name_suffix": "",
                    "institution": "Baylor College of Medicine",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Donoghue",
                    "name_suffix": "",
                    "institution": "Columbia University",
                    "department": ""
                },
                {
                    "first_name": "Sandra",
                    "middle_name": "",
                    "last_name": "Maesta-Pereira",
                    "name_suffix": "",
                    "institution": "Columbia University",
                    "department": ""
                },
                {
                    "first_name": "Uros",
                    "middle_name": "",
                    "last_name": "Topalovic",
                    "name_suffix": "",
                    "institution": "University of California",
                    "department": ""
                },
                {
                    "first_name": "John",
                    "middle_name": "",
                    "last_name": "Sakon",
                    "name_suffix": "",
                    "institution": "University of California",
                    "department": ""
                },
                {
                    "first_name": "Elliot",
                    "middle_name": "H",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "University of Utah",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49324/galley/37285/download/"
                }
            ]
        },
        {
            "pk": 49154,
            "title": "Alignment of Representational Complexity as a Latent Control Parameter in Referential Communication",
            "subtitle": null,
            "abstract": "Despite large inter-individual differences in experience and conceptual structures, humans converge on referents largely underspecified by the signals exchanged during communication. Many neural networks have become extremely sensitive to context-dependent relationships between signals, but remain relatively blind to their referents outside the signal space. Here, we study how human interlocutors dynamically coordinate both their signal and referential spaces over extended communicative interactions. We identify a latent control parameter, representational complexity, that may regulate referential coordination in human communication. Using a custom hierarchical Transformer model, we generate movement- and interaction-level embeddings from neurotypical (NT) and autistic (ASC) dyads engaged in an experimental semiotic task. By leveraging ASC-related communicative variance, we identify changes in parameters that track the representational dimensionality of signals and referents as communication unfolds. Movement-level embeddings (within-trial dependencies) could not differentiate the two groups, indicating comparable communicative behaviors. In contrast, interactionlevel embeddings (across-trial dependencies) distinguished ASC from NT dyads with high accuracy. Crucially, representational complexity, i.e. dyadic alignment in the interaction-level intrinsic dimensionality used to encode communicative histories, tracked referential coordination demands, with greater misalignment in ASC dyads under referential volatility. These findings suggest that referential alignment is an interaction-level process, driven by the dynamic adaptation of representational complexity, rather than statistical relationships between signals alone.",
            "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/3bk1x8mw",
            "frozenauthors": [
                {
                    "first_name": "Amir Homayun",
                    "middle_name": "",
                    "last_name": "Hallajian",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Saskia B.J",
                    "middle_name": "",
                    "last_name": "Koch",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Jana",
                    "middle_name": "",
                    "last_name": "Ba_n‡kov‡",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Ivan",
                    "middle_name": "",
                    "last_name": "Toni",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Arjen",
                    "middle_name": "",
                    "last_name": "Stolk",
                    "name_suffix": "",
                    "institution": "Dartmouth College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49154/galley/37115/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49154/galley/38660/download/"
                }
            ]
        },
        {
            "pk": 49381,
            "title": "A Linguistic Analysis of Spontaneous Thoughts: Investigating Experiences of Deja Vu, Unexpected Thoughts, and Involuntary Autobiographical Memories",
            "subtitle": null,
            "abstract": "The onset of spontaneous thoughts are reflective of dynamic interactions between cognition, emotion, and attention. Typically, these experiences are studied through subjective appraisals that focus on their triggers, phenomenology, and emotional salience. In this work, we use linguistic signatures to investigate Déjà Vu, Involuntary Autobiographical Memories, and Unexpected Thoughts. Specifically, we analyze the inherent characteristics of the linguistic patterns in participant generated descriptions of these thought types. We show how, by positioning language as a window into spontaneous cognition, existing theories on these attentional states can be updated and reaffirmed. Our findings align with prior research, reinforcing that Déjà Vu is a metacognitive experience characterized by abstract and spatial language, Involuntary Autobiographical Memories are rich in personal and emotionally significant detail, and Unexpected Thoughts are marked by unpredictability and cognitive disruption. This work is demonstrative of languages' potential to reveal deeper insights into how internal spontaneous cognitive states manifest through expression.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Linguistics; Psychology; Language and thought; Machine learning; Natural Language Processing"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/82s563d7",
            "frozenauthors": [
                {
                    "first_name": "Videep",
                    "middle_name": "",
                    "last_name": "Venkatesha",
                    "name_suffix": "",
                    "institution": "Colorado State University",
                    "department": ""
                },
                {
                    "first_name": "Mary",
                    "middle_name": "Cati",
                    "last_name": "Poulos",
                    "name_suffix": "",
                    "institution": "University of Minnesota Twin Cities",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "Steadman",
                    "name_suffix": "",
                    "institution": "University of Minnesota",
                    "department": ""
                },
                {
                    "first_name": "Caitlin",
                    "middle_name": "",
                    "last_name": "Mills",
                    "name_suffix": "",
                    "institution": "University of Minnesota",
                    "department": ""
                },
                {
                    "first_name": "Anne",
                    "middle_name": "M.",
                    "last_name": "Cleary",
                    "name_suffix": "",
                    "institution": "Colorado State University",
                    "department": ""
                },
                {
                    "first_name": "Nathaniel",
                    "middle_name": "",
                    "last_name": "Blanchard",
                    "name_suffix": "",
                    "institution": "Colorado State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49381/galley/37343/download/"
                }
            ]
        },
        {
            "pk": 49304,
            "title": "All Eyes on the Hippocampus: The Primate Hippocampus as a Visually-Guided Cognitive Graph",
            "subtitle": null,
            "abstract": "Spatial memory is a core cognitive function of many mobile animals. The study of spatial cognition is highly interdisciplinary and different approaches have led to discordant hypotheses about spatial memory. The neuroscientific discovery of place cells and grid cells in the rodent hippocampus and entorhinal cortex led to the highly influential \"cognitive map\" hypothesis. Conversely, behavioral evidence led to the \"cognitive graph\" hypothesis that suggests memory is distortion-prone. We argue that between-species differences in sensory and perceptual systems cause vision to play a predominant role in primates. We build on previous modeling work by developing a visual version of the SR model to show that it can provide a unified framework to account for seemingly disparate findings from the brain and behavior, thus providing evidence for our hypothesis that primate (e.g., human) spatial cognition is driven by the hippocampal system, which instantiates a visually-guided cognitive graph.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Psychology; Behavioral Science; Memory; Spatial cognition; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8444g7k8",
            "frozenauthors": [
                {
                    "first_name": "Derek",
                    "middle_name": "J.",
                    "last_name": "Huffman",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Linh",
                    "middle_name": "Khanh",
                    "last_name": "Dang",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Olivia",
                    "middle_name": "Roan",
                    "last_name": "Doherty",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Amrit",
                    "middle_name": "",
                    "last_name": "Shakya",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Ainsley",
                    "middle_name": "K",
                    "last_name": "Bonin",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49304/galley/37265/download/"
                }
            ]
        },
        {
            "pk": 49127,
            "title": "All you ever wanted to ask about Dynamic Field Theory",
            "subtitle": null,
            "abstract": "\\section{How does the mind emerge from the brain? }\nA neural process theory of cognition is one of the central goals l of cognitive science. Connectionism was developed in pursuit of that goal leading to a range of proposed frameworks such as LISA and DORA \\cite{DoumasEtAl2022}, SPAUN \\cite{StewartEliasmith2012} and many others \\cite{KotserubaTsotso2020}. The rise of neural AI reframes the question of how neural accounts may reach higher cognition \\cite{SmolenskyEtAl2022,OReillyEtAl2022}. \n\nBut what is meant by neural process theory ? Which neural principles would form the basis for such a theory? And what is it a theory of? What properties of cognition must such a theory address? \n\nDynamic Field Theory (DFT) gives specific answers to these questions, postulating that the dynamics of neural populations are the level of neural processing that most closely reflects the laws of cognition. It emphasizes the emergence of cognition from the sensory-motor domain, so that a theory of cognition must address both acting and thinking.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Workshop",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/44v2j1f2",
            "frozenauthors": [
                {
                    "first_name": "Gregor",
                    "middle_name": "",
                    "last_name": "Schšner",
                    "name_suffix": "",
                    "institution": "Ruhr-UniversitŠt Bochum",
                    "department": ""
                },
                {
                    "first_name": "Yulia",
                    "middle_name": "",
                    "last_name": "Sandamirskaya",
                    "name_suffix": "",
                    "institution": "ZHAW",
                    "department": ""
                },
                {
                    "first_name": "Aaron",
                    "middle_name": "",
                    "last_name": "Buss",
                    "name_suffix": "",
                    "institution": "University of Tennessee",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49127/galley/37088/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49127/galley/38633/download/"
                }
            ]
        },
        {
            "pk": 49466,
            "title": "Alpha band activity over the sensorimotor cortex during passive music listening correlates with beat tapping performance",
            "subtitle": null,
            "abstract": "Theories of music perception argue over whether observed motor area activation during passive music listening actively contributes to perception or is the product of a distributed representation. There is a growing amount of evidence linking Alpha rhythms in the motor cortex to action inhibition and imagination during passive music listening. In this work, we examine Alpha band power modulation and its association to beat perception using a sensorimotor synchronization task and a natural music listening task with electroencephalography (EEG). We sought to find an association between Alpha band modulation over the primary motor cortex and beat tapping performance. We found that greater Alpha power correlated with worse tapping performance. These results may point to a negative association between motor inhibition and beat perception and a complementary positive association between movement imagination and beat perception and production. We address these findings in terms of the HAPEM theory proposed by Schubotz (2003). This framework suggests that motor activation reflects a predictive representation formed from audio-motor association cortices, lacking proprioceptive information which could be acquired through musical training.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Action; Embodied Cognition; Music; Perception"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2wt0q98s",
            "frozenauthors": [
                {
                    "first_name": "Francisco",
                    "middle_name": "",
                    "last_name": "Cossavella",
                    "name_suffix": "",
                    "institution": "Laboratorio de Inteligencia Artificial Aplicada Instituto de Investigaci—n en Ciencias de la Computaci—n, CONICET- UBA",
                    "department": ""
                },
                {
                    "first_name": "Mart’n",
                    "middle_name": "",
                    "last_name": "Dottori",
                    "name_suffix": "",
                    "institution": "Universidad de San AndrŽs",
                    "department": ""
                },
                {
                    "first_name": "Martin",
                    "middle_name": "",
                    "last_name": "Miguel",
                    "name_suffix": "",
                    "institution": "McMaster University",
                    "department": ""
                },
                {
                    "first_name": "Diego",
                    "middle_name": "",
                    "last_name": "Fernandez Slezak",
                    "name_suffix": "",
                    "institution": "Universidad de Buenos Aires",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49466/galley/37428/download/"
                }
            ]
        },
        {
            "pk": 49581,
            "title": "A Mechanistic Perspective of Face Perception Latency: Predictive Coding",
            "subtitle": null,
            "abstract": "Face processing is widely regarded in cognitive science as the integration of individual features into a holistic percept. However, recent neuroscience research highlights a more nuanced interplay between holistic and featural mechanisms, with specific facial features receiving greater emphasis during early perception. Event-related potential studies reveal that the number and type of parafoveal features significantly influence neural response delays, yet the underlying mechanistic model remains unclear. This paper examines these phenomena through the lens of the predictive coding network, a biologically plausible alternative to traditional deep neural networks. Our findings show that predictive coding networks accurately simulate the influence of parafoveal features on neural response times while upholding the saliency hierarchy of facial features. These results provide a computational explanation for the observed neural delays and highlight the potential of predictive coding as a robust framework for understanding face perception in the human brain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Perception; Bayesian modeling; Computational neuroscience; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4vb934hv",
            "frozenauthors": [
                {
                    "first_name": "William",
                    "middle_name": "",
                    "last_name": "Pugsley",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Junteng",
                    "middle_name": "",
                    "last_name": "Zheng",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Roxane",
                    "middle_name": "",
                    "last_name": "Itier",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Jeff",
                    "middle_name": "",
                    "last_name": "Orchard",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49581/galley/37543/download/"
                }
            ]
        },
        {
            "pk": 50400,
            "title": "A Meta-analysis of Age-related effect on Loss Aversion",
            "subtitle": null,
            "abstract": "Prospect Theoretic Loss aversion (λ) suggests we overvalue losses compared to gains during decision making but the influence of age on loss aversion is unclear. We conducted a random-effects meta-analysis on 7 studies that measured loss aversion and the age of participants. The pooled estimate (β=0.0886, 95%CI [0.0087 0.1686] revealed an effect of age on loss aversion. Considering age as continuous (n=1103, 5 studies; β = -0.005233, t= -2.511, p = 0.0122) or categorical (n=1856, 8 studies; β=0.00856, t= 0.111, p = 0.912) reflected substantial differences. Dividing participants broadly (&lt; 46 and &gt; 45 years) to explore differences in estimates of loss aversion (λ&gt;1, λ =1, λ&lt;1), also found significant differences, X2 (2, 1856)=7.5362, p = 0.0231. These findings underscore the veracity of meta-analysis for advancing and explicating previously underexplored aspects of decision theory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Behavioral Science; Cognitive development; Decision making"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5ww0n6wx",
            "frozenauthors": [
                {
                    "first_name": "Mehak",
                    "middle_name": "",
                    "last_name": "Gupta",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Delhi",
                    "department": ""
                },
                {
                    "first_name": "Sumitava",
                    "middle_name": "",
                    "last_name": "Mukherjee",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Delhi",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50400/galley/38362/download/"
                }
            ]
        },
        {
            "pk": 49434,
            "title": "A metacognitive appraisal of quitting",
            "subtitle": null,
            "abstract": "Stopping decisions are frequently modeled as decisions to switch to alternative activities once the current activity stops being adequately rewarding, such as in optimal foraging theory, as well as more recent metacognitive models. However, the sense of stopping and making decisions in such frameworks is highly platonic, with both decisions and stopping actions occurring instantaneously. In contrast, the phenomenology of quitting actions that one is undertaking appears to be temporally extended and metacognitively challenging. We study the metacognitive covariates of quitting decisions made by chess players using a large database of chess games sourced from an online chess portal. Our analysis reveals that players tend to persevere when they are playing against stronger opponents and after having played poor moves. We also find that a history of quitting games makes players more likely to quit in future games, but that having recently quit in a game offers some protective effect against quitting. Finally, we find that quitting a game makes it more likely that a player will play a game again soon. We place these results in the context of modeling quitting as a metacognitive choice affected by multiple competing goals.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Embodied Cognition; Other; Computational Modeling; Quantitative Behavior"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/02n5p1j5",
            "frozenauthors": [
                {
                    "first_name": "Hariharan",
                    "middle_name": "",
                    "last_name": "Purohit",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology Kanpur",
                    "department": ""
                },
                {
                    "first_name": "Nisheeth",
                    "middle_name": "",
                    "last_name": "Srivastava",
                    "name_suffix": "",
                    "institution": "Indian Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49434/galley/37396/download/"
                }
            ]
        },
        {
            "pk": 49188,
            "title": "A Metacognitive Model of Memory Encoding Modulated by Rewards",
            "subtitle": null,
            "abstract": "Despite robust empirical evidence supporting the role of reward in enhancing memory, the relationship between reward and memory shows complex patterns. We present a novel computational model that considers how people optimally allocate limited cognitive resources during memory encoding. Unlike previous accounts that directly link rewards with stronger memory encoding, we allow our model to adaptively decide how much to encode based on the overall reward environment and one's limited cognitive resources. Our model's predictions align closely with human behavior across three experiments. It explains why high-reward items are better remembered than low-reward items only when presented together but not separately, and how memory is modulated by rewards of both current and preceding (but not future) items. We also collected data demonstrating that this insensitivity to rewards of future items can be reversed when participants anticipate upcoming rewards. These findings provide evidence that memory encoding is an active process involving meta-level control rather than a passive response to individual reward values.",
            "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/8hx6t7d5",
            "frozenauthors": [
                {
                    "first_name": "Si",
                    "middle_name": "",
                    "last_name": "Ma",
                    "name_suffix": "",
                    "institution": "Rutgers University, New Brunswick",
                    "department": ""
                },
                {
                    "first_name": "Qiong",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Rutgers University - New Brunswick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49188/galley/37149/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49188/galley/38694/download/"
                }
            ]
        },
        {
            "pk": 49423,
            "title": "A minimalistic representation model for head direction system",
            "subtitle": null,
            "abstract": "We propose a minimalistic representational model for the head direction (HD) system, a crucial component of spatial navigation in mammals. Our model leverages the symmetry of the rotation group U(1) and the inherent circular geometry of the head direction. We develop fully connected and convolutional versions of the model, both aiming to learn a high-dimensional representation of head direction that captures essential properties of HD cells. Our learning method results in representations that form a perfect 2D circle when projected onto their principal components, reflecting the underlying geometry of the problem. We also demonstrate that individual dimensions of our learned representation exhibit Gaussian-like tuning profiles akin to biological HD cells. Our model achieves accurate multi-step path integration, effectively updating its internal heading estimate over time. These results demonstrate that simple symmetry-based constraints can yield biologically realistic HD representations, offering new insights into the computational principles underlying spatial navigation in mammals.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Machine learning; Representation; Computational neuroscience"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0k45f96z",
            "frozenauthors": [
                {
                    "first_name": "Minglu",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "University of California - Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Dehong",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California - Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Deqian",
                    "middle_name": "",
                    "last_name": "Kong",
                    "name_suffix": "",
                    "institution": "University of California - Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Wen-Hao",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "UT Southwestern Medical Center",
                    "department": ""
                },
                {
                    "first_name": "Yingnian",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "University of California - Los Angeles",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49423/galley/37385/download/"
                }
            ]
        },
        {
            "pk": 49293,
            "title": "A Model of Approximate and Incremental Noisy-Channel Language Processing",
            "subtitle": null,
            "abstract": "How are comprehenders able to extract meaning from utterances in the presence of production errors? The noisy-channel theory provides an account grounded in Bayesian inference: comprehenders may interpret utterances non-literally in favor of an alternative with higher prior probability that is close under some error model. However, we lack implemented computational models of prior expectation and error likelihood capable of predicting human processing of arbitrary utterances. Here, we model sentence processing for ``noisy\" utterances as incremental and approximate probabilistic inference over intended sentences and production errors. We demonstrate that the model reproduces patterns in human behavior for anomalous sentences in three separate case studies from the noisy-channel literature. \nOur results offer a step towards an algorithmic account of inference during real-world language comprehension. Our model code, implemented in Gen, is available at https://github.com/thomashikaru/noisy_channel_model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language Comprehension; Natural Language Processing; Computational Modeling; Eye tracking; Symbolic computational modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9kr1b1gm",
            "frozenauthors": [
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Clark",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Jacob",
                    "middle_name": "Hoover",
                    "last_name": "Vigly",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Edward",
                    "middle_name": "",
                    "last_name": "Gibson",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Roger",
                    "middle_name": "",
                    "last_name": "Levy",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49293/galley/37254/download/"
                }
            ]
        },
        {
            "pk": 50435,
            "title": "A Modular Framework for Analyzing Theory of Mind Learning in Competitive Tasks",
            "subtitle": null,
            "abstract": "A key challenge of theory of mind, or the ability to reason about others' mental states, is understanding the process by which others' perceptions influence their beliefs. While specific tasks---like competitive feeding---benchmark participants' ability to infer beliefs, it remains unclear how such capabilities can be learned. In this work, we introduce a modular framework that solves a computational, competitive-feeding-like game in which two agents compete. By systematically replacing modules of a successful rule-based framework with neural networks, we identify which capabilities can be learned from narrow sets of experiences, and which are critical for robust generalization. Using feature extraction techniques, we analyze how different architectures process task-relevant information. Finally, we describe and compare three novel approaches to improving generalization via first-person exposure to uncertainty: role reversal with the opponent, artificial observation masking, and synthesizing beliefs from conflicting information.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Animal cognition; Cognitive development; Theory of Mind; Neural Networks"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8fw411f1",
            "frozenauthors": [
                {
                    "first_name": "Joel",
                    "middle_name": "",
                    "last_name": "Michelson",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Deepayan",
                    "middle_name": "",
                    "last_name": "Sanyal",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Maithilee",
                    "middle_name": "",
                    "last_name": "Kunda",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50435/galley/38397/download/"
                }
            ]
        },
        {
            "pk": 50162,
            "title": "Amortizing Structure Discovery with Generative Flow Networks",
            "subtitle": null,
            "abstract": "An open problem in cognitive science is how the human mind discovers and represents structures for human knowledge. To address this problem via a computational approach, Kemp and Tenenbaum (2008) introduce a posterior distribution which assesses the goodness of fit for a structure to some data; however, Kemp and Tenenbaum's method finding structures with high probability under this posterior relied on hand-crafted search heuristics, was intractable at inference, and lacked convergence guarantees to the true posterior distribution of structures. To address this, we amortize this process with a generative flow network (GFlowNet), a novel framework for developing probabilistic models. When trained, our GFlowNet samples structures proportional to Kemp and Tenenbaum's posterior. We show preliminary results on synthetic datasets that highlights the benefit of our approach in both scaleability and simplicity.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Bayesian modeling; Computational Modeling; Knowledge representation"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5zd5d4k5",
            "frozenauthors": [
                {
                    "first_name": "Alex",
                    "middle_name": "",
                    "last_name": "Guerra",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Aditya",
                    "middle_name": "",
                    "last_name": "Palaparthi",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Sarah-jane",
                    "middle_name": "",
                    "last_name": "Leslie",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "",
                    "last_name": "Hawkins",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50162/galley/38124/download/"
                }
            ]
        },
        {
            "pk": 49629,
            "title": "Amplifying Truth? Vocal Volume and Speakers' Self-Perceived Truthfulness",
            "subtitle": null,
            "abstract": "This study was the first to examine whether the volume of one's voice serves as an embodied cue for assessing information credibility. Eighty U.S. undergraduate students were randomly assigned to one of three conditions: loud, soft, or control. They read aloud in their assigned loudness condition while rating the truthfulness of trivia statements, followed by silently rating additional statements. The results revealed no significant effect of voice loudness on truthfulness ratings. When examining confidence levels reflected in the ratings, an interaction effect between reading status and loudness condition emerged. Participants who controlled their volume (either loud or soft) rated statements with higher confidence compared to when rating statements silently. These findings suggest that speakers do not associate their own voice loudness with the truthfulness of information.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Embodied Cognition; Social cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/40h7m2p3",
            "frozenauthors": [
                {
                    "first_name": "Yi",
                    "middle_name": "",
                    "last_name": "Shao",
                    "name_suffix": "",
                    "institution": "Oklahoma City University",
                    "department": ""
                },
                {
                    "first_name": "Ruby",
                    "middle_name": "K.",
                    "last_name": "Bautista",
                    "name_suffix": "",
                    "institution": "Oklahoma City University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49629/galley/37591/download/"
                }
            ]
        },
        {
            "pk": 49588,
            "title": "A Multimodal In Vitro Diagnostic Method for Parkinson's Disease Combining Facial Expressions and Behavioral Gait Data",
            "subtitle": null,
            "abstract": "Parkinson's disease (PD), characterized by its incurable nature, rapid progression, and severe disability, poses significant challenges to the lives of patients and their families. Given the aging population, the need for early detection of PD is increasing. In vitro diagnosis has garnered attention due to its non-invasive nature and low cost. However, existing methods present several challenges: 1) limited training data for facial expression diagnosis; 2) specialized equipment and acquisition environments required for gait diagnosis, resulting in poor generalizability; 3) the risk of misdiagnosis or missed diagnosis when relying on a single modality. To address these issues, we propose a novel multimodal in vitro diagnostic method for PD, leveraging facial expressions and behavioral gait. Our method employs a lightweight deep learning model for feature extraction and fusion, aimed at improving diagnostic accuracy and facilitating deployment on mobile devices. Furthermore, we have established the largest multimodal PD dataset in collaboration with a hospital and conducted extensive experiments to validate the effectiveness of our proposed method.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Computer Science; Face Processing; Pattern recognition; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9p96f55f",
            "frozenauthors": [
                {
                    "first_name": "Wei",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                },
                {
                    "first_name": "Yinxuan",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                },
                {
                    "first_name": "Yintao",
                    "middle_name": "",
                    "last_name": "Zhou",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                },
                {
                    "first_name": "Zhengyu",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Nanchang University Second Affiliated Hospital",
                    "department": ""
                },
                {
                    "first_name": "Jing",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Nanchang University Second Affiliated Hospital",
                    "department": ""
                },
                {
                    "first_name": "Meng",
                    "middle_name": "",
                    "last_name": "Pang",
                    "name_suffix": "",
                    "institution": "Nanchang University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49588/galley/37550/download/"
                }
            ]
        },
        {
            "pk": 49244,
            "title": "An ACT-R model of resource-rational performance in a pragmatic reference game",
            "subtitle": null,
            "abstract": "In the Gricean tradition, pragmatic competence is part of the general human capacity for social reasoning. Indeed, human performance in reference games involving ad-hoc implicatures sometimes aligns with idealized models of rational interaction. But such experiments have also found that humans derive far fewer implicatures than ideal models, subject to individual differences unrelated to social reasoning. In this paper, we consider whether these patterns could arise from the resource-rational deployment of a core social competence, such that individuals choose from various strategies of interpretation, given those strategies' resource demands and success rates, subject to individually-varying predispositions and exploration tendencies. We construct a model of this resource- rational performance in the cognitive architecture ACT-R—to our knowledge the first mechanistic model of performance in these tasks—and we examine its predictions for multi-trial reference games across two model experiments. The model reproduces the key patterns in the human data, providing an initial proof of concept for the role of resource-rationality in these tasks and opening a new avenue for understanding individual differences in pragmatic reasoning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Cognitive architectures; Language Comprehension; Pragmatics; Symbolic computational modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6mw6t8rc",
            "frozenauthors": [
                {
                    "first_name": "John",
                    "middle_name": "",
                    "last_name": "Duff",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Mayn",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Vera",
                    "middle_name": "",
                    "last_name": "Demberg",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49244/galley/37205/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49244/galley/38750/download/"
                }
            ]
        },
        {
            "pk": 49943,
            "title": "Analogical Relatedness Between Exemplars of Schema-Governed Categories",
            "subtitle": null,
            "abstract": "The traditional perspective on analogical thinking has shown that relational similarity is key in determining analogical relatedness, outweighing entity similarity. However, evidence supporting this perspective comes from studies where the combination of the elements composing the compared facts does not activate schema-governed categories whose mismatch could compete with similarity between relations during the evaluation of analogical relatedness. In Experiment 1, we assessed the relative impact of common category membership and relational similarity on judgments of analogical relatedness. Pairs of events where only a common category was present received higher scores than pairs where neither a common category nor similar relations were present, and also than pairs maintaining only similar relations. In Experiment 2, we examined the extent to which judgments of analogical relatedness were affected by whether the compared situations fared similarly along relevant dimensions of the schema-governed categories to which they belonged. Ratings were higher for pairs where the analogs matched compared to pairs where they did not match. We concluded that in comparisons in which at least one of the events activates a schema-governed category, people assess analogical relatedness through criteria that depart from those postulated by traditional studies.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Analogy; Quantitative Behavior"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/48w5t2tp",
            "frozenauthors": [
                {
                    "first_name": "Ricardo",
                    "middle_name": "A",
                    "last_name": "Minervino",
                    "name_suffix": "",
                    "institution": "University of Comahue",
                    "department": ""
                },
                {
                    "first_name": "Pablo",
                    "middle_name": "",
                    "last_name": "Rodriguez Osztreicher",
                    "name_suffix": "",
                    "institution": "Tel Aviv University",
                    "department": ""
                },
                {
                    "first_name": "Maximo",
                    "middle_name": "",
                    "last_name": "Trench",
                    "name_suffix": "",
                    "institution": "University of Comahue",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49943/galley/37905/download/"
                }
            ]
        },
        {
            "pk": 50216,
            "title": "An EEG study of forming new phonemic categories by naive listeners of Mandarin",
            "subtitle": null,
            "abstract": "The current study investigates the formation of new phonemic categories by examining the neurophysiological changes before and after training. Native English speakers tend to perceive Mandarin retroflexes as English fricatives ([ʂ] → [ʃ]) (Rasmussen &amp; Bohn, 2015). In our experiment, native English speakers unfamiliar with Mandarin underwent a pre-training EEG recording in a passive auditory oddball paradigm. Then in two consecutive days, they learned Mandarin words containing retroflexes before undergoing a post-training EEG. The current result shows that the difference in the amplitude of P300 – an indicator of stimuli differentiation (Calcus et al., 2015) – between the retroflex [ʂ] (rare) and non-retroflex [ʃ] (frequent) is larger in post-training than pre-training, suggesting that they are learning to distinguish the two fricatives. Our current findings suggest that the formation of the new phonemic category can be observed in the processing stage that overlaps with P300.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Linguistics; Learning; Perception; Electroencephalography (EEG)"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8bg90544",
            "frozenauthors": [
                {
                    "first_name": "Chung-Lin",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Needle",
                    "middle_name": "",
                    "last_name": "de Carvalho Wang",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Luoyi",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Yuehan",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Ruitong",
                    "middle_name": "",
                    "last_name": "Jiang",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Joyce",
                    "middle_name": "",
                    "last_name": "McDonough",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50216/galley/38178/download/"
                }
            ]
        },
        {
            "pk": 49925,
            "title": "An Effective Strategy to Reduce Interference: Effects of Unitization on the Development of Memory Binding",
            "subtitle": null,
            "abstract": "Memory binding is the ability to bind together multiple components in a memory trace. Previous studies have shown that one way to improve memory binding is to integrate multiple components into the same item in a meaningful way – a strategy known as unitization. To further investigate unitization as a source of development of memory binding, in terms of whether a unitization strategy has different effects on different memory structures and different age groups, the current study incorporated a semantic unitization strategy into a memory binding task and recruited multiple age groups for the experiment. Results showed that unitization led to a marked improvement in three-way binding for 7-year-olds and adults, but not for 5-year-olds, suggesting that semantic unitization could be a driving force for the development of complex memory binding in childhood and even beyond adulthood, but its effect in young children might still be limited due to their immaturity.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "memory"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4642r3gk",
            "frozenauthors": [
                {
                    "first_name": "Jiangmeng",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "Ohio State University",
                    "department": ""
                },
                {
                    "first_name": "Vladimir",
                    "middle_name": "",
                    "last_name": "Sloutsky",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49925/galley/37887/download/"
                }
            ]
        },
        {
            "pk": 50020,
            "title": "An Enactivist Interpretation of Aphantasia",
            "subtitle": null,
            "abstract": "Aphantasia is a phenomenon in which the aphantasic subject fails to voluntarily conduct sensory imagination. That is to say, the mental image aphantasic subjects generated during sensory imagination is much less vivid than what normal people would report that they can generate. This paper proposes an enactivist interpretation of aphantasia, which suggests that aphantasia is the phenomenon resulted from a disrupted balance between the top-down processing by brain activity and the bottom-up processing by body-environment interaction, which leads to: 1) the conceptual content emerging in body-environment interaction overwhelms the phenomenal characteristics of the mental image generated within the brain, and 2) the \"phenomenon absence\" of the generated mental image signified by the real-time body-environment interaction becomes so profound that the mental image generated in sensory imagination fails to be conceptualized as vivid from the first-person perspective.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Philosophy; Concepts and categories; Consciousness; Embodied Cognition; cognitive neuropsychology"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6jc735kr",
            "frozenauthors": [
                {
                    "first_name": "Qiantong",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Chinese Academy of Sciences, Institute of Philosophy",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50020/galley/37982/download/"
                }
            ]
        },
        {
            "pk": 49822,
            "title": "A Neural Network Model of Complementary Learning Systems: Pattern Separation and Completion for Continual Learning",
            "subtitle": null,
            "abstract": "Learning new information without forgetting prior knowledge is central to human intelligence. In contrast, neural network models suffer from catastrophic forgetting: a significant degradation in performance on previously learned tasks when acquiring new information. The Complementary Learning Systems (CLS) theory offers an explanation for this human ability, proposing that the brain has distinct systems for pattern separation (encoding distinct memories) and pattern completion (retrieving complete memories from partial cues). To capture these complementary functions, we leverage the representational generalization capabilities of variational autoencoders (VAEs) and the robust memory storage properties of Modern Hopfield networks (MHNs), combining them into a neurally plausible continual learning model.  We evaluate this model on the Split-MNIST task, a popular continual learning benchmark, and achieve close to state-of-the-art accuracy ~90%, substantially reducing forgetting. Representational analyses empirically confirm the functional dissociation: the VAE underwrites pattern completion, while the MHN drives pattern separation. By capturing pattern separation and completion in scalable architectures, our work provides a functional template for modeling memory consolidation, generalization, and continual learning in both biological and artificial systems.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Cognitive Neuroscience; Learning; Machine learning; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6084m9rc",
            "frozenauthors": [
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Jun",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Vijay",
                    "middle_name": "",
                    "last_name": "Marupudi",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Raj",
                    "middle_name": "Sanjay",
                    "last_name": "Shah",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Sashank",
                    "middle_name": "",
                    "last_name": "Varma",
                    "name_suffix": "",
                    "institution": "Georgia Tech",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49822/galley/37784/download/"
                }
            ]
        },
        {
            "pk": 50247,
            "title": "A Neurosymbolic Model of Human Reasoning on the Abstraction and Reasoning Corpus",
            "subtitle": null,
            "abstract": "The Abstraction and Reasoning Corpus (ARC) is a visual program synthesis benchmark designed to test out-of-distribution generalization in machines. Although recent advancements have led to human-level performance on ARC, it is still unclear how people solve ARC tasks. Other work has demonstrated that people often make errors when reasoning about these problems, and sometimes fail to infer the true underlying program. In this work, we explore the hypothesis that the cognitive mechanisms supporting reasoning are more approximate, graded and resource-limited compared to those suggested by purely discrete, program-induction models. Taking inspiration from previous work on program sketches and partial programs, we model human reasoning in the ARC domain using a neurosymbolic, meta-learned model that interleaves symbolic operations with approximate, statistical pattern completion. We then evaluate the model against human errors from H-ARC, a recent, comprehensive behavioral dataset on the training and evaluation sets of ARC.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Machine learning; Reasoning; Computational Modeling; Neural Networks"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1pf7x0x0",
            "frozenauthors": [
                {
                    "first_name": "Solim",
                    "middle_name": "",
                    "last_name": "LeGris",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "NYU",
                    "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": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50247/galley/38209/download/"
                }
            ]
        },
        {
            "pk": 50056,
            "title": "An Experience-First Approach to Autistic Pragmatics",
            "subtitle": null,
            "abstract": "Pragmatic atypicality is widely considered to be a central characteristic of autism. This is often explained as a consequence of Theory of Mind deficits. However, this account is flawed and biased. In this paper, we revisit the Double Empathy Problem and provide an experience-first approach to autistic pragmatics. We start with proposing a mechanistic explanation of a link between experiential differences and intentionality understanding in linguistic contexts using the Interpretive Sensory Access theory. Then, we explain how theories of common ground in communication involve factors beyond intention recognition and even beyond cooperation, highlighting how the egocentric nature of communication is relevant to one's attention and experiences. Taken together, we put forward an experience-based approach to understand autistic pragmatic atypicalities. This view is compatible with many other non-linguistic characteristics well-documented in autism, and prioritizes the experience of autistic people, instead of framing it as a communication disorder with a \"mind-reading failure\".",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Philosophy; Consciousness; Pragmatics; Theory of Mind"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/93k5t04h",
            "frozenauthors": [
                {
                    "first_name": "Yage",
                    "middle_name": "G.",
                    "last_name": "Xin",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                },
                {
                    "first_name": "Dezhi",
                    "middle_name": "",
                    "last_name": "Luo",
                    "name_suffix": "",
                    "institution": "University of Michigan",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50056/galley/38018/download/"
                }
            ]
        },
        {
            "pk": 49436,
            "title": "An Explorative Investigation into Leveraging LLMs to Predict University Students' Learning Motivation",
            "subtitle": null,
            "abstract": "Learning motivation is a key variable in learning. Therefore, its assessment has consistently been a popular research topic. While traditional methods like self-report still dominate, methods integrating passive mobile sensing have emerged, using smartphones to collect behavioral data and assess learning motivation via statistical and machine learning techniques. Recent advances in large language models (LLMs) offer new perspectives for psychological measurements, yet their application in learning motivation assessment remains underexplored. To bridge this gap, we propose a novel approach that integrates LLMs with passive mobile sensing to assess and predict students' learning motivation. We constructed our dataset using mobile sensing data and self-report measures, then designed zero-shot and few-shot tasks embedded in LLMs to evaluate the performance. Ultimately, our findings indicate the feasibility and highlight the potential of leveraging LLMs to predict learning motivation levels based on mobile sensing data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Human-computer interaction; Learning"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8xq2h626",
            "frozenauthors": [
                {
                    "first_name": "Yu",
                    "middle_name": "",
                    "last_name": "Feng",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Tongyu",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Yatong",
                    "middle_name": "",
                    "last_name": "Zu",
                    "name_suffix": "",
                    "institution": "Jilin University",
                    "department": ""
                },
                {
                    "first_name": "Adriano",
                    "middle_name": "",
                    "last_name": "Tavares",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Tiago",
                    "middle_name": "",
                    "last_name": "Gomes",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Hao",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Jilin University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49436/galley/37398/download/"
                }
            ]
        },
        {
            "pk": 49673,
            "title": "An Ideal Observer Model of Audiovisual Detection Captures Modality-Specific, but not Amodal, Confidence Ratings",
            "subtitle": null,
            "abstract": "Detecting objects in the environment, and forming a sense of confidence in these decisions typically involves multisensory processing. We sought to characterize how humans form amodal and modality-specific confidence judgments during audiovisual detection. We found that participants made more accurate detection and confidence judgments for audiovisual than unimodal stimuli. To explain these results, we extended a Bayesian evidence accumulation model to audiovisual detection and successfully reproduced both unimodal and audiovisual detection judgments. Despite being fitted to decisions and decision times alone, our model accurately reproduced modality-specific confidence. It failed, however, to account for amodal confidence, suggesting that the latter might not arise from optimal signal integration in detection contexts. Our results indicate that, in the presence of audiovisual signals, different integration rules apply for perceptual and metacognitive decisions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Perception; Bayesian modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3pt9z89f",
            "frozenauthors": [
                {
                    "first_name": "Perrine",
                    "middle_name": "",
                    "last_name": "Porte",
                    "name_suffix": "",
                    "institution": "UniversitŽ Grenoble Alpes",
                    "department": ""
                },
                {
                    "first_name": "Matan",
                    "middle_name": "",
                    "last_name": "Mazor",
                    "name_suffix": "",
                    "institution": "University of Oxford",
                    "department": ""
                },
                {
                    "first_name": "Louise",
                    "middle_name": "",
                    "last_name": "Goupil",
                    "name_suffix": "",
                    "institution": "CNRS",
                    "department": ""
                },
                {
                    "first_name": "Nathan",
                    "middle_name": "",
                    "last_name": "Faivre",
                    "name_suffix": "",
                    "institution": "CNRS",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49673/galley/37635/download/"
                }
            ]
        },
        {
            "pk": 49510,
            "title": "An Incremental Program Induction Model of Slow Mapping Words to Meanings",
            "subtitle": null,
            "abstract": "The process by which people adjust, enrich, and revise their understanding of word meanings over time – so-called ‘Slow Mapping' – has often been overlooked, particularly in terms of how a computationally bounded learner might approach such a task. To address this gap, we propose a process model of incremental word-meaning induction. This proposal is inspired by recent work on concept and theory change grounded in a probabilistic language of thought (pLOT). We focus on the problem of fixing the meanings of words from usage examples, taking kinship terms as our test domain. We frame word meaning induction at a computational level as a program induction problem, and hypothesize that individual learners search for possible meanings as evidence arrives via a mutative Markov-Chain Monte-Carlo search scheme. We show this idea provides a better description of how participants' generalizations and tentative definitions of alien kinship words shift as evidence arrives, outperforming normative accounts and other baselines.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Concepts and categories; Language acquisition; Bayesian modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9677j1jp",
            "frozenauthors": [
                {
                    "first_name": "Ella",
                    "middle_name": "",
                    "last_name": "Markham",
                    "name_suffix": "",
                    "institution": "The University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Hugh",
                    "middle_name": "",
                    "last_name": "Rabagliati",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Neil",
                    "middle_name": "R.",
                    "last_name": "Bramley",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49510/galley/37472/download/"
                }
            ]
        },
        {
            "pk": 49308,
            "title": "An information bottleneck view of social stereotype use",
            "subtitle": null,
            "abstract": "For decades, social psychologists have wondered about the cognitive foundations of social stereotype use. Arguments have generally centred either resource constraints, framing stereotypes as `energy-saving devices', or `fit', framing stereotypes as tools to represent real structure in the social environment that sometimes go awry. These resource-based and fit-based accounts have typically been presented as being in opposition to one another. In this paper, we seek to show that both are compatible under an information bottleneck model of agent representation. Through a simple simulation experiment, we demonstrate how stereotype use emerges in resource-rational representations as a function of both capacity constraints and the structure of the social environment. We then use the same framework to consider a possible explanation for the outgroup homogeneity bias in terms of limited cognitive capacity.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Concepts and categories; Representation; Social cognition; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/86c4482s",
            "frozenauthors": [
                {
                    "first_name": "Max",
                    "middle_name": "Louis",
                    "last_name": "Taylor-Davies",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Tadeg",
                    "middle_name": "",
                    "last_name": "Quillien",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49308/galley/37269/download/"
                }
            ]
        },
        {
            "pk": 50419,
            "title": "An Intervention Program: Helping Deaf Children with Hearing Parents in Acquiring Turkish Sign Language",
            "subtitle": null,
            "abstract": "Many deaf children first encounter a language in deaf schools, often experiencing adverse effects of late exposure on several aspects of language. Little is known about how late acquisition of sign language affects lexical sign acquisition and how the structural architecture of signs modulates this process. Here, we investigate the lexical development of late-signing children (N=11; MeanAge=84.7 months) through 8-week intervention using mobile-compatible web-app teaching lexical signs in Turkish Sign Language to investigate whether (1) children acquire basic signs during intervention and (2) phonological complexity influences this process. Preliminary results revealed a significant improvement in sign learning (β=1.7545, p&lt;0.001) regardless of phonological complexity (ps&gt;0.05). Findings underline the importance of accessible platforms to support language development for this population and extend previous work on the effect of phonological complexity on articulation accuracy during learning in hearing adults by showing its lack of influence in deaf children on 2-choice recognition without articulation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language acquisition; Field studies"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6wc7w6kp",
            "frozenauthors": [
                {
                    "first_name": "Hilal",
                    "middle_name": "",
                    "last_name": "…zdemir",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                },
                {
                    "first_name": "Maharrem",
                    "middle_name": "",
                    "last_name": "Ayar",
                    "name_suffix": "",
                    "institution": "Centre for Mind and Brain",
                    "department": ""
                },
                {
                    "first_name": "Dilay",
                    "middle_name": "Z.",
                    "last_name": "Karadoller",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50419/galley/38381/download/"
                }
            ]
        },
        {
            "pk": 50087,
            "title": "An Investigation of [l]-[n] Merger among Hubei Dialect Speakers: Cross-Linguistic Evidence from Perception and Production",
            "subtitle": null,
            "abstract": "This study investigates Hubei dialect speakers' ability to distinguish and identify Mandarin and English words with [l]-[n] onsets through AX discrimination and identification tasks, along with their production in Hubei dialect, Mandarin, and English. Results showed lower accuracy in discriminating [l] and [n] in English and Mandarin, especially with stimuli containing a high vowel, nasal coda, or diphthong beginning with a high or front vowel. Participants with more dialect use and later Mandarin acquisition were less sensitive to the contrast. Directionality of merger varied across participants. No significant effects of linguistic or social factors were found in identification, except a positive effect of initial high vowels in Mandarin diphthongs. Acoustic measures showed no significant differences, suggesting an [l]-[n] merger. These findings provide insights into non-native speech perception and production and suggest implications for pronunciation training.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Language acquisition; Language Production; Perception; Cross-linguistic analysis"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/14c7c4j4",
            "frozenauthors": [
                {
                    "first_name": "Yan",
                    "middle_name": "",
                    "last_name": "Shi",
                    "name_suffix": "",
                    "institution": "University of Utah",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50087/galley/38049/download/"
                }
            ]
        },
        {
            "pk": 50243,
            "title": "A Normative Account of Specialization: How Task and Environment Shape Role Differentiation in Collaboration",
            "subtitle": null,
            "abstract": "In collaborative groups, both humans and artificial intelligence (AI) agents frequently adopt specialized roles, yet the conditions that govern the optimal degree of specialization remain poorly understood. In this work, we propose that specialist teams outperform generalist ones when environmental constraints limit task parallelizability---the potential to execute task components concurrently. Drawing inspiration from distributed systems, we introduce a heuristic to predict the relative efficiency of generalist versus specialist teams and validate it through three multi-agent reinforcement learning (MARL) experiments in Overcooked-AI, demonstrating that key factors limiting task parallelizability influence specialization. Notably, as the task space expands, agents reliably converge on specialist strategies, even when generalist ones are theoretically more efficient, suggesting that specialization may help mitigate costly learning demands. Our findings provide a normative framework for understanding when and why specialization emerges as the optimal strategy in collaborative settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Intelligent agents; Interactive behavior; Machine learning; Mathematical modeling"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7nh7c08d",
            "frozenauthors": [
                {
                    "first_name": "Elizabeth",
                    "middle_name": "",
                    "last_name": "Mieczkowski",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Ruaridh",
                    "middle_name": "",
                    "last_name": "Mon-Williams",
                    "name_suffix": "",
                    "institution": "Edinburgh University",
                    "department": ""
                },
                {
                    "first_name": "Neil",
                    "middle_name": "R.",
                    "last_name": "Bramley",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "Guy",
                    "last_name": "Lucas",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Natalia",
                    "middle_name": "A",
                    "last_name": "VŽlez",
                    "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": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50243/galley/38205/download/"
                }
            ]
        },
        {
            "pk": 49167,
            "title": "A Normative Model of Delay Discounting Across the Lifespan: Tradeoffs Between Mortality, Fertility, and Parenting",
            "subtitle": null,
            "abstract": "The developmental trajectory of delay discounting has been debated for over 30 years, with empirical findings often inconsistent. The controversy stems partly from the absence of formal models to guide empirical investigation and theoretical construction. We proposed a normative model of delay discounting across the lifespan, building on the work of Sozou and Seymour (2003), which emphasizes the tradeoff between mortality, fertility, and parenting in determining delay discounting. We simulated the model across varying parameter spaces and identified a U-shaped association between age and delay discounting, with stronger parental investment postponing the turning point of the function and reducing the overall discount rate. Empirical data supported these predictions, demonstrating a U-shaped age effect and highlighting the role of parental care motivation in explaining cultural and age-related differences in delay discounting. The results suggest that variance in delay discounting can be understood as a rational adaptation to life history tradeoffs.",
            "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/59x0r7x8",
            "frozenauthors": [
                {
                    "first_name": "Junsong",
                    "middle_name": "",
                    "last_name": "Lu",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                },
                {
                    "first_name": "Xiaotian",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "the Chinese University of Hong Kong, Shenzhen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49167/galley/37128/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49167/galley/38673/download/"
                }
            ]
        },
        {
            "pk": 49889,
            "title": "Another Brick in the Wall? A Null Effect of Boundaries on Spatial Memory Judgments in a Novel, Highly Immersive, First-Person Object-Placement Task",
            "subtitle": null,
            "abstract": "Spatial memory is evolutionarily important for many animals. Boundaries can systematically distort spatial memory in line with hierarchical models, while other evidence supports more metric path-integration theories. To test these competing theories, we developed a novel, highly immersive Object Placement Task (OPT) in virtual reality to examine the effect of boundaries on human spatial memory. Our task decomposes spatial memory into 3 components: 1) object-placement errors, 2) distance judgments, and 3) angular judgments (i.e., our single task provides multidimensional information about spatial memory). Thirty participants used the OPT to recall object positions in environments with or without a central boundary. Bayesian analyses showed that distance influenced memory performance, but boundary presence had no significant effect (Bayes factors favored the null models). These findings suggest a set of conditions in which boundaries may not impact memory. We discuss potential modulators of boundary effects and present our open-source task for future research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Animal cognition; Behavioral Science; Memory; Spatial cognition"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6d11q44r",
            "frozenauthors": [
                {
                    "first_name": "Derek",
                    "middle_name": "J.",
                    "last_name": "Huffman",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Paisley",
                    "middle_name": "J",
                    "last_name": "Annes",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Sinan",
                    "middle_name": "",
                    "last_name": "Yumurtaci",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "J.",
                    "last_name": "Starrett Ambrose",
                    "name_suffix": "",
                    "institution": "University of California, Irvine",
                    "department": ""
                },
                {
                    "first_name": "Amrit",
                    "middle_name": "",
                    "last_name": "Shakya",
                    "name_suffix": "",
                    "institution": "Colby College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49889/galley/37851/download/"
                }
            ]
        },
        {
            "pk": 50193,
            "title": "Anxiety Impacts Reinforcement Learning Subprocesses In a Choose-Your-Own-Adventure Text-Based Game",
            "subtitle": null,
            "abstract": "Reinforcement learning (RL)—using past choices and outcomes to learn best policies—can model the effects of anxiety in human learning. RL mechanisms are commonly studied using game-like computer tasks; but real-life learning often happens in naturalistic settings, with artificial stimuli less involved than day-to-day situations and objects. We used an online \"choose your own adventure\" text game to test how modality of interaction—narrative versus gamified—impacts the effect of anxiety on RL. 211 participants completed five \"chapters\" (blocks) of seven choices, followed by informative feedback about underlying story structure. Higher anxiety scores linked to lower model-free accuracy and higher reaction times. An RL model with memory-decay and attention components showed comparable learning rates, but more decision noise and lower attention in anxious participants. This data shows that anxiety impacts RL in naturalistic processing contexts and holds potential insights into the use of narrative, RL-based gamification in educational settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Psychology; Learning; Representation; Computational Modeling"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4v74024b",
            "frozenauthors": [
                {
                    "first_name": "Andra",
                    "middle_name": "",
                    "last_name": "Geana",
                    "name_suffix": "",
                    "institution": "Providence College",
                    "department": ""
                },
                {
                    "first_name": "TESSA",
                    "middle_name": "",
                    "last_name": "MEDEIROS",
                    "name_suffix": "",
                    "institution": "Providence College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50193/galley/38155/download/"
                }
            ]
        },
        {
            "pk": 49973,
            "title": "A \"p &lt; .05\" Boundary Effect in the Encoding and Retrieval of p-values from Scientific Texts",
            "subtitle": null,
            "abstract": "‘Statistical significance' is more than just a label. Cognitive psychological theories suggest it may represent a mental concept of a category of p-values due to the pervasive practice of dichotomous interpretation of p-values. This paper builds on previous research identifying categorical boundary effects in the initial information processing of p-values by examining the encoding and retrieval of p-values embedded in the context of scientific abstracts. A sample of 30 U.S. graduate students in the psychological sciences read blocks of abstracts, then were prompted to recall certain details, including p-values. Results show that memory for p-values was skewed away from the .05 boundary, suggesting that training in dichotomous ‘p &lt; .05' thinking may lead to categorical biases in memory for p-values. These results set up experiments to test mechanistic hypotheses of boundary effects on statistical cognition as well as the efficacy of teaching interventions to address and ameliorate these categorical biases.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Memory; Situated cognition; Statistics"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/08x7m34h",
            "frozenauthors": [
                {
                    "first_name": "V. N. Vimal",
                    "middle_name": "",
                    "last_name": "Rao",
                    "name_suffix": "",
                    "institution": "University of Illinois",
                    "department": ""
                },
                {
                    "first_name": "Jeffrey",
                    "middle_name": "K.",
                    "last_name": "Bye",
                    "name_suffix": "",
                    "institution": "California State University, Dominguez Hills",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49973/galley/37935/download/"
                }
            ]
        },
        {
            "pk": 50445,
            "title": "\"Apples and Oranges\" - Evaluating Reaction Time Measures as a Paradigm to Contrast Expert vs. Novice Performance in Complex, Dynamic Task Environments",
            "subtitle": null,
            "abstract": "Previous research has effectively employed the fast-paced action puzzle video-game Tetris for understanding the acquisition of extreme expertise in complex, dynamic environments. A common approach when contrasting expert to novice performance has been the dissection of their interactions with the environment into disjoint sub-tasks – such as reaction time (RT), measured by the input latency to new events on screen. The crucial, underlying assumption to this paradigm is task consistency at all levels of expertise. Using data collected from participants of the Tetris World Championship 2019 and from novices in our lab, we show that this assumption does not hold. While for novices the RT task type remains the same across all conditions, for experts - depending on environmental parameters - RT task type undergoes a shift and under specific conditions does not represent an RT task anymore. Thus, expert vs. novice sub-task comparison may not be a valid paradigm.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Action; Decision making; Problem Solving; Skill acquisition and learning; Comparative Studies"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7z14d4n4",
            "frozenauthors": [
                {
                    "first_name": "Alexander",
                    "middle_name": "",
                    "last_name": "Lutsevich",
                    "name_suffix": "",
                    "institution": "Rensselaer Polytechnic Institute",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50445/galley/38407/download/"
                }
            ]
        },
        {
            "pk": 49351,
            "title": "Applications of transcranial Direct Current Stimulation (tDCS) for modulating the Face Inversion Effect (FIE): Reducing and Enhancing Recognition",
            "subtitle": null,
            "abstract": "We report a large study examining the effects of tDCS on the FIE. Subjects randomly assigned to one of the four tDCS groups and engaged with an old/new recognition task involving upright and inverted faces. 1) Sham tDCS during the study phase and recognition task; 2) Anodal tDCS during the study phase followed by sham tDCS during the recognition task; 3) Anodal tDCS during the study phase followed by cathodal tDCS during the recognition task; 4) Cathodal tDCS during the study phase followed by sham tDCS during the recognition task. Group 2 confirmed that anodal tDCS reduces the FIE vs. sham (Group 1) by disrupting performance for upright faces. Group 3 showed that cathodal tDCS applied after anodal, increased the FIE vs. Group 2, bringing it back to sham level, by enhancing upright faces.  Group 4 revealed that cathodal tDCS applied after sham has no effect on the baseline FIE",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Psychology; Face Processing; Learning; Memory"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0q52d68m",
            "frozenauthors": [
                {
                    "first_name": "Ciro",
                    "middle_name": "",
                    "last_name": "Civile",
                    "name_suffix": "",
                    "institution": "University of Exeter",
                    "department": ""
                },
                {
                    "first_name": "Wang",
                    "middle_name": "",
                    "last_name": "Guangtong",
                    "name_suffix": "",
                    "institution": "University of Exeter",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49351/galley/37312/download/"
                }
            ]
        },
        {
            "pk": 49217,
            "title": "A Pragmatic Model of Spatial Language",
            "subtitle": null,
            "abstract": "Spatial language is an integral part of everyday communication, but existing theories fail to explain the cognitive processing underlying the interpretation of spatial descriptions. The traditional spatial template theory does not attempt to provide a mechanism behind the computation of acceptability ratings, nor does it adequately address the effect of distractors or the conversational context. In this study, we propose a new model of spatial pragmatics, based on the Rational Speech Act (RSA) framework. This Bayesian model shows how the patterns of spatial language understanding follow directly from the principles of pragmatics. Our model accounts for previously found effects of angle, distance, and distractors on acceptability ratings and indication behavior. We test these predictions in an experiment consisting of various tasks. The results largely support our model's predictions, suggesting that pragmatic reasoning might play a role in spatial language use.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language Comprehension; Language Production; Spatial cognition; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/69v8f5r9",
            "frozenauthors": [
                {
                    "first_name": "Midas",
                    "middle_name": "",
                    "last_name": "Vanooteghem",
                    "name_suffix": "",
                    "institution": "KULeuven",
                    "department": ""
                },
                {
                    "first_name": "Walter",
                    "middle_name": "",
                    "last_name": "Schaeken",
                    "name_suffix": "",
                    "institution": "KU Leuven",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49217/galley/37178/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49217/galley/38723/download/"
                }
            ]
        },
        {
            "pk": 50483,
            "title": "A Preliminary Investigation of Spatial Ability and Spatial Anxiety in Prosthetics and Orthotics Students",
            "subtitle": null,
            "abstract": "Spatial ability is crucial in STEM and medical fields, including prosthetics and orthotics (P&amp;O), which focuses on designing, fabricating and fitting of prostheses and orthoses. However, spatial ability in P&amp;O practitioners remains unexplored. This study examined spatial ability in P&amp;O master's students using mental rotation and cross-sectioning tasks, and assessed spatial anxiety, including imagery anxiety, mental manipulation anxiety, and navigation anxiety. At orientation, female students reported higher overall spatial anxiety, but there were no gender differences in spatial ability. Mental manipulation anxiety was negatively correlated with cross-sectioning ability in females (r = -0.44, p = 0.009) but not in males (r = -0.08, p = 0.080). After six months, female spatial anxiety decreased, and overall cross-sectioning ability improved. Gender differences in spatial anxiety decreased, though navigation anxiety remained higher in females (t(46) = 2.60, p = 0.01). P&amp;O program participation appears to improve spatial ability and reduce spatial anxiety.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Learning; Spatial cognition"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2xw6b26h",
            "frozenauthors": [
                {
                    "first_name": "Danielle",
                    "middle_name": "",
                    "last_name": "Rothschild Doyle",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Kiley",
                    "middle_name": "",
                    "last_name": "McKee",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Mackenzie",
                    "middle_name": "",
                    "last_name": "Drummond",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Cavanaugh",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Mindy",
                    "middle_name": "",
                    "last_name": "Thorpe",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Reed",
                    "middle_name": "",
                    "last_name": "Stevens",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Uttal",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50483/galley/38445/download/"
                }
            ]
        },
        {
            "pk": 50064,
            "title": "A preliminary study to Assess Self-regulated learning and Academic Emotional Regulation of College Students Using Smartphones",
            "subtitle": null,
            "abstract": "Many of the self-regulated learning (SRL) skills and academic emotional regulation (AER) strategies of student life remain hidden. iSense continuous sensing app provides a novel method to monitor and assess the impact of social interactions, sleep patterns, app usage, and mobility on SRL skills and AER strategies. In a year-long study involving 211 university students, the iSense collected behavioral data from smartphones continuously and unobtrusively. The results revealed significant correlations between passive sensor data and SRL/AER self-reports such as task strategies, time management, situational selection, and social support. These findings enhance our understanding of students' learning and emotional regulation behaviors while offering a foundation for personalized learning support tools based on mobile sensing. By applying dynamic behavioral data, iSense demonstrates its potential for advancing contextualized learning analytics and psychological intervention systems.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Philosophy; Human-computer interaction"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2mn5f5wq",
            "frozenauthors": [
                {
                    "first_name": "Tongyu",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Jiaying",
                    "middle_name": "",
                    "last_name": "Gao",
                    "name_suffix": "",
                    "institution": "School of Artificial intenlligence",
                    "department": ""
                },
                {
                    "first_name": "Yu",
                    "middle_name": "",
                    "last_name": "Feng",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Yatong",
                    "middle_name": "",
                    "last_name": "Zu",
                    "name_suffix": "",
                    "institution": "Jilin University",
                    "department": ""
                },
                {
                    "first_name": "Adriano",
                    "middle_name": "",
                    "last_name": "Tavares",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Tiago",
                    "middle_name": "",
                    "last_name": "Gomes",
                    "name_suffix": "",
                    "institution": "University of Minho",
                    "department": ""
                },
                {
                    "first_name": "Sandro",
                    "middle_name": "",
                    "last_name": "Pinto",
                    "name_suffix": "",
                    "institution": "Universidade do Minho",
                    "department": ""
                },
                {
                    "first_name": "Hao",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Jilin University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50064/galley/38026/download/"
                }
            ]
        },
        {
            "pk": 49648,
            "title": "A Quantum Model of Arousal and Yerkes Dodson Law",
            "subtitle": null,
            "abstract": "We present the Oscillating Field Perturbation (OFP) model, a quantum model that provides a quantitative account of the Yerkes-Dodson law concerning the relationship between arousal and performance. Inspired by neural models, OFP conceptualizes cognitive control as an oscillating field that perturbs a quantum system, and represents arousal as the ``gain'' induced by this field. By integrating OFP with the Multiple Particle Multiple Well (MPMW) framework, we demonstrate that OFP successfully explains how the shape of the Yerkes-Dodson law varies with task difficulty and familiarity, consistent with empirical findings. To the best of the authors' knowledge, OFP is the first model to provide a unified account of the empirical variations in the shape of the Yerkes-Dodson law.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Psychology; Computational Modeling; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1j01k2cx",
            "frozenauthors": [
                {
                    "first_name": "Jiaqi",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Jerome",
                    "middle_name": "",
                    "last_name": "Busemeyer",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49648/galley/37610/download/"
                }
            ]
        },
        {
            "pk": 49524,
            "title": "A Quantum Statistical Model of Decision Making in a Single-Cell Eukaryote",
            "subtitle": null,
            "abstract": "The single-celled protist Stentor roselii has long been observed to exhibit complex decision-making behaviors, yet existing machine learning and classical computational models have struggled to replicate its actions. In this paper, we propose a novel quantum-statistical framework to model S. roselii's behavioral responses to environmental stimuli. By leveraging quantum circuits with amplitude dampening and memory effects, we construct a quantum behavioral model that captures the probabilistic and hierarchical nature of S. roselii's decision making. Our results suggest that quantum statistical theory provides a powerful tool for representing and simulating biological decision processes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Biology; Animal cognition; Decision making; Agent-based Modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4ph93789",
            "frozenauthors": [
                {
                    "first_name": "Jad",
                    "middle_name": "",
                    "last_name": "Soucar",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Francis",
                    "middle_name": "",
                    "last_name": "Steen",
                    "name_suffix": "",
                    "institution": "University of California",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49524/galley/37486/download/"
                }
            ]
        },
        {
            "pk": 49355,
            "title": "A Rational Model of Dimension-reduced Human Categorization",
            "subtitle": null,
            "abstract": "Humans can categorize with only a few samples despite the numerous features. To mimic this ability, we propose a novel mixture of probabilistic principal component analyzers (mPPCA) model with dimension-reduced category representations, along with a theoretical analysis of rational dimensionality choices in categorization. Tests on the {\\tt CIFAR-10H} natural image categorization dataset show that introducing a single principal component for each category effectively improves predictions of human categorization patterns. We further use mPPCA to account for human category generalization with very few samples. In our experiments with visual patterns of varying size and color, combining principal components and the hierarchical prior leads to significantly better predictions of human generalization within and beyond previously learned categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Bayesian modeling; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/17z1w2g9",
            "frozenauthors": [
                {
                    "first_name": "Yifan",
                    "middle_name": "",
                    "last_name": "Hong",
                    "name_suffix": "",
                    "institution": "Tsinghua University",
                    "department": ""
                },
                {
                    "first_name": "Chen",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "Tsinghua University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49355/galley/37316/download/"
                }
            ]
        },
        {
            "pk": 49998,
            "title": "Architecture and the Self: Empirical Inquiry on Christopher Alexander's Theory of Living Structure",
            "subtitle": null,
            "abstract": "The Biophilia hypothesis emphasizes humanity's intrinsic desire to connect with nature, which in turn nurtures authenticity. Architectural designs that echo natural patterns can evoke feelings of wholeness, inspiration, and comfort, as proposed by architectural theorist Christopher Alexander in his Theory of Living Structure. This study empirically examined the connection between architecture and the authentic self. Participants engaged with Chinese philosophical texts from Chuang Tzu and The Analects of Confucius to explore their authentic selves. They then evaluated image pairs, assessing preference, liveliness, and self-connection, with one image exemplifying living structures characterized by multiple scales, varied patterns, and interconnected centers. Our participants exhibited a strong preference for living structures. Notably, individuals with lower susceptibility to external influence, an essential component of authenticity, were more likely to perceive living structures as self-connected. Our findings offer valuable insights into human-centered architectural design aimed at fostering authentic living.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Aesthetics; Art and Cognition; Cognitive Humanities; Consciousness; Computer-based experiment; Quantitative Behavior"
                }
            ],
            "section": "Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2h86h5cg",
            "frozenauthors": [
                {
                    "first_name": "Chengwen",
                    "middle_name": "",
                    "last_name": "E",
                    "name_suffix": "",
                    "institution": "BNU-HKBU United International College",
                    "department": ""
                },
                {
                    "first_name": "Rongrong",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "Guangdong Provincial/Zhuhai Key Laboratory IRADS",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49998/galley/37960/download/"
                }
            ]
        },
        {
            "pk": 49150,
            "title": "Are Expressions for Music Emotions the Same Across Cultures?",
            "subtitle": null,
            "abstract": "Music evokes profound emotions, yet the universality of emotional descriptors across languages remains debated. A key challenge in cross-cultural research on music emotion is biased stimulus selection and manual curation of taxonomies, predominantly relying on Western music and languages. To address this, we propose a balanced experimental design with nine online experiments in Brazil, the US, and South Korea, involving N=672 participants. First, we sample a balanced set of popular music from these countries. Using an open-ended tagging pipeline, we then gather emotion terms to create culture-specific taxonomies. Finally, using these bottom-up taxonomies, participants rate emotions of each song. This allows us to map emotional similarities within and across cultures. Results show consistency in high arousal, high valence emotions but greater variability in others. Notably, machine translations were often inadequate to capture music-specific meanings. These findings together highlight the need for a domain-sensitive, open-ended, bottom-up emotion elicitation approach to reduce cultural biases in emotion research.",
            "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/6bg3n8ft",
            "frozenauthors": [
                {
                    "first_name": "Elif",
                    "middle_name": "",
                    "last_name": "Celen",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Empirical Aesthetics",
                    "department": ""
                },
                {
                    "first_name": "Pol",
                    "middle_name": "",
                    "last_name": "van Rijn",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Empirical Aesthetics",
                    "department": ""
                },
                {
                    "first_name": "Harin",
                    "middle_name": "",
                    "last_name": "Lee",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Empirical Aesthetics",
                    "department": ""
                },
                {
                    "first_name": "Nori",
                    "middle_name": "",
                    "last_name": "Jacoby",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Empirical Aesthetics",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49150/galley/37111/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49150/galley/38656/download/"
                }
            ]
        },
        {
            "pk": 50112,
            "title": "Are Global Statistics Discarded Statistics? An Investigation of What Types of  Co-Occurrence Statistics Could Support the Acquisition of Semantic Knowledge",
            "subtitle": null,
            "abstract": "Much research examining the development of semantic knowledge has focused on patterns of co-occurrence in language. An often-made distinction concerns ‘local' co-occurrences (word pairs that appear close together) and ‘global' co-occurrences (word pairs that appear in similar linguistic contexts), with some recent accounts arguing that only local co-occurrences are exploitable by young children. We tested the alternative view that this dichotomy may be misaligned with natural language input. First, we performed a descriptive analysis of the co-occurrence structure present in the input. This analysis suggests that global co-occurrences are frequent in the input to children. Second, we performed a descriptive analysis of the semantic information encoded by local and global statistics in the CHILDES corpus; this analysis suggests that both local and global co-occurrences encode patterns of similarity that could support the acquisition of structured semantic representations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Development; Language acquisition; Semantics of language; Statistical learning; Corpus studies"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/16v77798",
            "frozenauthors": [
                {
                    "first_name": "Molly",
                    "middle_name": "I",
                    "last_name": "Niehaus",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Tijana",
                    "middle_name": "",
                    "last_name": "Slepcev",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Catarina",
                    "middle_name": "",
                    "last_name": "Vales",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50112/galley/38074/download/"
                }
            ]
        },
        {
            "pk": 49600,
            "title": "Are object state changes represented during language comprehension? A non-replication and extension",
            "subtitle": null,
            "abstract": "Previous work suggests that non-visual object properties like\nweight are automatically integrated into event models during\nlanguage comprehension. Horchak and Garrido (2021) found\nthat Portuguese speakers' response times were faster when the\nstate of a presented object (e.g., a smashed tomato) matched\nthe event implied by the preceding sentence (e.g., You drop a\nbowling ball on a tomato). In an exact replication in English\n(Experiment 1), we failed to replicate this weight-state match\neffect. In Experiment 2, we examined the potential role of\nsentence focus, manipulating whether the target item served as\nthe subject or direct object in the sentence. Response times\nrevealed a weight-state match effect, but only when the target\nobject was the focus (i.e., subject) of the sentence. Overall,\nthese findings suggest that the representation of object state\nchanges during language comprehension may depend on the\ninteraction of object properties and language-specific syntactic   \nconstraints.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Embodied Cognition; Event cognition; Language Comprehension; Representation"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8gr5r4dh",
            "frozenauthors": [
                {
                    "first_name": "Channing",
                    "middle_name": "E",
                    "last_name": "Hambric",
                    "name_suffix": "",
                    "institution": "Bowdoin College",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "J.",
                    "last_name": "Holmes",
                    "name_suffix": "",
                    "institution": "Reed College",
                    "department": ""
                },
                {
                    "first_name": "Abhilasha",
                    "middle_name": "",
                    "last_name": "Kumar",
                    "name_suffix": "",
                    "institution": "Bowdoin College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49600/galley/37562/download/"
                }
            ]
        },
        {
            "pk": 50374,
            "title": "Are people aware of biases in their judgment and decision-making? A rigorous large-scale test",
            "subtitle": null,
            "abstract": "People exhibit systemic biases in their judgment and decision-making, and these biases are often presumed to operate outside of awareness. Nevertheless, there are surprisingly few direct empirical examinations of this question. Here, in two studies (total N = 727), we test participants' awareness of 11 classic biases. Participants completed a series of tasks, each inducing one bias (e.g., the anchoring effect, decoy effect, halo effect, etc.), and then reported whether and how they believed they were influenced by each bias. We found that, aggregating across tasks, participants' reports tracked how much they were actually influenced by each bias (with correlations between 0.3 - 0.45), indicating significant awareness. There were also substantial individual differences, with many participants exhibiting near-perfect awareness. This research argues against the notion that people are inherently unaware of their decision-making biases, and instead supports views that place conscious processing closer to the center of human decision-making.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Consciousness; Decision making; Computer-based experiment; Quantitative Behavior"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1jg2t986",
            "frozenauthors": [
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Morris",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Noa",
                    "middle_name": "",
                    "last_name": "Perlmutter",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Sofia",
                    "middle_name": "",
                    "last_name": "Montinola",
                    "name_suffix": "",
                    "institution": "Massachusetts General Hospital",
                    "department": ""
                },
                {
                    "first_name": "Hedy",
                    "middle_name": "",
                    "last_name": "Kober",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Molly",
                    "middle_name": "J",
                    "last_name": "Crockett",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50374/galley/38336/download/"
                }
            ]
        },
        {
            "pk": 50264,
            "title": "Are \"sweet talks\" literally sweet?: A study of taste imagery evoked by Japanese emotional words",
            "subtitle": null,
            "abstract": "In many languages, the speakers use taste-related words to express emotions. This preregistered study extends preceding survey study findings by applying attribute conditioning paradigm to examine whether emotional words influence gustatory imagery of nonsense words. Native Japanese-speaking participants underwent an attribute conditioning consisting of five phases: the first evaluative phase, a conditioning phase, the second evaluative phase, a contingency awareness questionnaire, and a contingency memory task. In the evaluative phases, participants rated nonsense words on emotional (i.e., valence, arousal, and familiarity) and taste-related (i.e., sweetness, saltiness, sourness, bitterness, umami, and spiciness) impressions. Emotional words with positive (e.g., happy, vacation) or negative meanings (e.g., sad, thief) were used as unconditioned stimuli. Results demonstrated that nonsense words paired with positive-meaning words were associated with sweetness and umami, while those paired with negative-meaning words were associated with saltiness, sourness, bitterness, and spiciness. These findings provide psycholinguistic insights into metaphorical expression using taste-related words.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Emotion; Language Comprehension; Semantics of language"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6vg6d0vh",
            "frozenauthors": [
                {
                    "first_name": "Mizuki",
                    "middle_name": "",
                    "last_name": "Yoshio",
                    "name_suffix": "",
                    "institution": "Hiroshima University",
                    "department": ""
                },
                {
                    "first_name": "Toshimune",
                    "middle_name": "",
                    "last_name": "Kambara",
                    "name_suffix": "",
                    "institution": "Hiroshima University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50264/galley/38226/download/"
                }
            ]
        },
        {
            "pk": 49832,
            "title": "Are there different types of error monitoring? A microstates analysis of error-related brain activity across three tasks",
            "subtitle": null,
            "abstract": "Error monitoring is commonly studied using various inhibitory control tasks, involving response withholding, response cancellation, or response selection. However, it remains unclear whether there is a common neural mechanism underlying error monitoring across these tasks or if it is specific to distinct types of cognitive failures. To identify both similarities and differences in the neural processing of errors across go/no-go, stop-signal, and flanker tasks, we employed microstate analysis. This method allows to study the dynamically evolving topographical patterns of neural activity throughout the brain. Our results revealed that the early phase of error monitoring in all tasks predominantly engages the supplementary motor area. In addition, we observed task-specific neural activity encompassing visual and motor areas in the go/no-go task, the dorsal part of the anterior cingulate cortex in the stop-signal task, and its ventral part in the flanker task. These findings suggest that error monitoring involves a collection of interconnected cognitive processes, rather than a uniform mechanism across tasks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Action; Motor control; cognitive neuropsychology; Electroencephalography (EEG)"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0kq52644",
            "frozenauthors": [
                {
                    "first_name": "Anna",
                    "middle_name": "",
                    "last_name": "Grabowska",
                    "name_suffix": "",
                    "institution": "Jagiellonian University",
                    "department": ""
                },
                {
                    "first_name": "Filip",
                    "middle_name": "",
                    "last_name": "Sondej",
                    "name_suffix": "",
                    "institution": "Jagiellonian University",
                    "department": ""
                },
                {
                    "first_name": "Magdalena",
                    "middle_name": "",
                    "last_name": "Senderecka",
                    "name_suffix": "",
                    "institution": "Jagiellonian University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49832/galley/37794/download/"
                }
            ]
        },
        {
            "pk": 49259,
            "title": "Are two-year-olds intrinsically motivated to explore their own competence?",
            "subtitle": null,
            "abstract": "Children are keen explorers of the outside world: They systematically explore surprising findings and test hypotheses during play. However, less is known about whether toddlers are similarly driven to explore and learn about the self. The present work adapts classic exploratory play paradigms to ask whether toddlers are intrinsically motivated to explore their own competence. In Experiment 1, we selected Montessori practical life toys that were verified to be developmentally appropriate and equally appealing to toddlers (N = 24, ages 24-35 months). In Experiment 2, 2-year-olds (N = 49, ages 24-35 months) played with these toys along with a parent. Toys were presented in pairs. In each pair, the parent guided the toddler's hand while playing with one toy, which provided confounded evidence about the toddler's competence, and took turns playing the other toy independently, which provided unconfounded evidence. When given a chance to freely explore the toys on their own, toddlers first approached the confounded toy, which suggests that toddlers sought to resolve uncertainty about their competence. As a further test of this idea, Experiment 3 (N = 11, ongoing) asks whether toddlers' exploration is modulated by task difficulty. Preliminary results suggest that toddlers explore confounded toys more often for more challenging tasks compared to easier ones. Together, our work provides insights into children's early motivation to understand the self, and this understanding is an important first step for researchers, educators, and parents to better encourage and scaffold this motivation throughout development.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Development; Learning; Developmental analysis"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/38z2w881",
            "frozenauthors": [
                {
                    "first_name": "Bella",
                    "middle_name": "",
                    "last_name": "Fascendini",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Bonan",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Natalia",
                    "middle_name": "A",
                    "last_name": "Vélez",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49259/galley/37220/download/"
                }
            ]
        },
        {
            "pk": 50037,
            "title": "Are You Sure About That? The Impact of Semantic Relatedness on Learning Through Testing, JOLs, and Passive Restudy",
            "subtitle": null,
            "abstract": "Recent work has shown that producing memory ratings during study may lead to greater retention than practice testing in some circumstances (Higham, 2023). This may be related to a phenomenon called judgment of learning (JOL) reactivity, in which making immediate JOLs during study can enhance later recall. However, JOLs and testing have not been directly compared in a typical testing effect (TE) paradigm. This study compared passive restudy, study with immediate JOLs, and testing in a TE paradigm. In Experiment 1, we found no clear TE and only tentative JOL reactivity when word pairs were not semantically related. In Experiment 2, the associative strength of the word pairs was increased. A robust TE emerged along with weak JOL reactivity. Importantly, testing significantly outperformed JOL and passive restudy. These findings are among the first to suggest that semantic relatedness is crucial for the TE and clarify how JOLs compare to testing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Instruction and teaching; Learning; Memory; Semantic memory"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9gs9v9qf",
            "frozenauthors": [
                {
                    "first_name": "Alejandro",
                    "middle_name": "",
                    "last_name": "Carranza",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Tim",
                    "middle_name": "C",
                    "last_name": "Rickard",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Emma",
                    "middle_name": "H",
                    "last_name": "Geller",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50037/galley/37999/download/"
                }
            ]
        },
        {
            "pk": 50440,
            "title": "Artificial Neural Networks Reveal a Cognitive Continuum Toward Human Abstraction",
            "subtitle": null,
            "abstract": "Do neural network models that fail to behave human-like reflect a fundamental divergence from human cognition, or do they mirror earlier developmental or evolutionary stages? We propose that such models may, in fact, offer insights into the origins of human abstraction. We evaluated over 200 pretrained neural networks alongside macaques, Tsimane natives, US adults and children on three visual match-to-sample tasks targeting increasing levels of abstraction: visual-semantic similarity, shape regularity, and relational reasoning. As task demands grow more abstract, just like monkey's, model decisions increasingly diverge from adult human behavior. However, representational similarity analyses reveal shared internal structure with all human groups, suggesting overlapping cognitive strategy. We further show that model alignment depends on specific design choices—architecture, scale, training regime, and language supervision—highlighting which inductive biases support human-like abstraction.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Concepts and categories; Representation; Comparative Analysis"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9t85d0vq",
            "frozenauthors": [
                {
                    "first_name": "Li",
                    "middle_name": "",
                    "last_name": "Wenjie",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Margaret",
                    "middle_name": "",
                    "last_name": "Henderson",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Yonatan",
                    "middle_name": "",
                    "last_name": "Bisk",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Jessica",
                    "middle_name": "",
                    "last_name": "Cantlon",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50440/galley/38402/download/"
                }
            ]
        },
        {
            "pk": 50367,
            "title": "A Shared Spatial Mental Representation System for Navigation and Reasoning",
            "subtitle": null,
            "abstract": "Recent studies revealed that the brain's system for representing physical space is also recruited to represent relations that are not inherently spatial. We investigated the relationship between the ability to form these abstract spatial representations and other spatial abilities. In four experiments, participants created spatial representations of a series of premises relating objects on two dimensions (e.g., A is faster than B, B is louder than C) and answered inference questions based on these relations. The type of information, i.e., spatial information (A is above B) versus abstract, non-spatial information (A is smarter than B), did not affect task performance. Individual differences in how ‘grid-like' the created representations were, as well as reasoning consistency, correlated with some spatial abilities, including path integration. These findings are consistent with the view that a common spatial mental representation system underlies our ability to form mental representations of physical and abstract spaces.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Reasoning; Representation; Spatial cognition"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4dk740kh",
            "frozenauthors": [
                {
                    "first_name": "Mitchell",
                    "middle_name": "Eric",
                    "last_name": "Munns",
                    "name_suffix": "",
                    "institution": "University of California, Santa Barbara",
                    "department": ""
                },
                {
                    "first_name": "Mary",
                    "middle_name": "",
                    "last_name": "Hegarty",
                    "name_suffix": "",
                    "institution": "University of California, Santa Barbara",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50367/galley/38329/download/"
                }
            ]
        },
        {
            "pk": 49554,
            "title": "A Similarity-Aware Graph Transformer-enhanced Probabilistic Case-based Reasoning Model for Knowledge Graph Reasoning",
            "subtitle": null,
            "abstract": "Knowledge Graph Reasoning (KGR) is an effective way to ameliorate sparsity and incompleteness problems by inferring new knowledge based on existing knowledge. The probabilistic case-based reasoning (CBR) model can gather reasoning paths from similar entities and relations in KG, thus outperforming rule-based and embedding-based KGR methods. However, it is still limited by some problems, such as insufficient learning of similarity features and sparse intermediate activations. This paper proposes a \\textbf{S}imilarity-\\textbf{A}ware graph transformer-enhanced probabilistic CBR model for \\textbf{KGR}, namely SA-KGR. The proposed model regards the reasoning task as the KG query answering and is composed of two phases. The first phase is similarity-aware graph transformer-based graph feature encoding, which equips the similarity matrix and Mixture-of-Expert network to obtain fine-grained similarity features that are more helpful for reasoning path generation. The second phase is similarity-enhanced probabilistic case-based reasoning, which can retrieve and infer query answers from the generated candidate paths to complete brain-like cognitive reasoning. Extensive experimental results on various benchmarks unambiguously demonstrate that the proposed SA-KGR model can obtain the state-of-the-art results of current CBR-based methods.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Case-based reasoning; Knowledge representation; Neural Networks"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1gz58677",
            "frozenauthors": [
                {
                    "first_name": "Yuejia",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Inner Mongolia University",
                    "department": ""
                },
                {
                    "first_name": "Jiantao",
                    "middle_name": "",
                    "last_name": "Zhou",
                    "name_suffix": "",
                    "institution": "Inner Mongolia University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49554/galley/37516/download/"
                }
            ]
        },
        {
            "pk": 49569,
            "title": "A simulation-heuristics dual-process model for intuitive physics",
            "subtitle": null,
            "abstract": "The role of mental simulation in human physical reasoning is widely acknowledged, but whether it is employed across scenarios with varying simulation costs and where its boundary lies remains unclear. Using a pouring-marble task, our human study revealed two distinct error patterns when predicting pouring angles, differentiated by simulation time. While mental simulation accurately captured human judgments in simpler scenarios, a linear heuristic model better matched human predictions when simulation time exceeded a certain boundary. Motivated by these observations, we propose a dual-process framework, Simulation-Heuristics Model (SHM), where intuitive physics employs simulation for short-time simulation but switches to heuristics when simulation becomes costly. By integrating computational methods previously viewed as separate into a unified model, SHM quantitatively captures their switching mechanism. The SHM aligns more precisely with human behavior and demonstrates consistent predictive performance across diverse scenarios, advancing our understanding of the adaptive nature of intuitive physical reasoning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Reasoning; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/49v704w7",
            "frozenauthors": [
                {
                    "first_name": "Shiqian",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Peking University",
                    "department": ""
                },
                {
                    "first_name": "Yuxi",
                    "middle_name": "",
                    "last_name": "Ma",
                    "name_suffix": "",
                    "institution": "Peking Unversity",
                    "department": ""
                },
                {
                    "first_name": "Jiajun",
                    "middle_name": "",
                    "last_name": "Yan",
                    "name_suffix": "",
                    "institution": "Institute of artificial intelligence",
                    "department": ""
                },
                {
                    "first_name": "Bo",
                    "middle_name": "",
                    "last_name": "Dai",
                    "name_suffix": "",
                    "institution": "Beijing Institute for General Artificial Intelligence (BigAI)",
                    "department": ""
                },
                {
                    "first_name": "Yujia",
                    "middle_name": "",
                    "last_name": "Peng",
                    "name_suffix": "",
                    "institution": "Peking University",
                    "department": ""
                },
                {
                    "first_name": "Chi",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Beijing Institute for General Artificial Intelligence",
                    "department": ""
                },
                {
                    "first_name": "Yixin",
                    "middle_name": "",
                    "last_name": "Zhu",
                    "name_suffix": "",
                    "institution": "Peking University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49569/galley/37531/download/"
                }
            ]
        },
        {
            "pk": 50455,
            "title": "Assessing Early Communicative Milestones in Preterm and Full-Term Children Using the Pebbles App",
            "subtitle": null,
            "abstract": "Children born preterm are at increased risk of delays in early communicative development. However, studies often focus on extremely or very preterm children (&lt; 32 weeks of gestation). To address this limitation, we use data from the Pebbles App, which reflects the gestational age distribution in the population. This app allows caregivers to document their child's development and assesses the age of attainment of 14 early communicative milestones. Preliminary analyses include more than 4000 children. For most communicative milestones, we did not find significant differences between preterm and full-term children within the first two years using corrected age. However, preterm children acquired some milestones, such as babbling, earlier than full-term children. A possible explanation is the greater communicative experience during the extended time in the extrauterine environment. These findings challenge traditional assumptions about language delays in preterm children and highlight the importance of using more representative samples.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Development; Language acquisition; Social cognition; Comparative Studies"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/65743339",
            "frozenauthors": [
                {
                    "first_name": "Miriam",
                    "middle_name": "Teresa",
                    "last_name": "Lšffler",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Tabea",
                    "middle_name": "",
                    "last_name": "StŠhli",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Lisa",
                    "middle_name": "",
                    "last_name": "Wagner",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Xin",
                    "middle_name": "",
                    "last_name": "Tong",
                    "name_suffix": "",
                    "institution": "University of Virginia",
                    "department": ""
                },
                {
                    "first_name": "Moritz MatthŠus",
                    "middle_name": "",
                    "last_name": "Daum",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Giancarlo",
                    "middle_name": "",
                    "last_name": "Natalucci",
                    "name_suffix": "",
                    "institution": "Larsson-Rosenquist Foundation Center for Neurodevelopment, Growth and Nutrition of the Newborn, Department of Neonatology, University of Zurich and University Hospital Zurich",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50455/galley/38417/download/"
                }
            ]
        },
        {
            "pk": 49455,
            "title": "Assessing the Role of Attention in the Animacy Effect Through Directed Forgetting",
            "subtitle": null,
            "abstract": "A growing body of research suggests the presence of an attentional component in the memory advantage of animate items. Most research on this animacy effect is focused on remembering, but its effects on forgetting are less well-researched. With the use of pupillometry, we investigated the attentional processes present in the selective remembering and directed forgetting of animate and inanimate items. More specifically, we investigated whether external and internal attention are affected by the animacy status of to-be-remembered and to-be-forgotten words in an item-method directed forgetting task with retro cues, followed by a recognition task for all previously presented items. Our behavioral results demonstrate the directed forgetting effect: accuracy on the recognition task was higher for to-be-remembered words than for to-be-forgotten words. Additionally, we found an advantage of animacy, with higher accuracy for animate words than for inanimate words, regardless of cue. The pupillometry results demonstrate differential internal attention for to-be-remembered and to-be-forgotten words during cueing, with larger pupil sizes for remember cues than for forget cues, but no effect of animacy. We did however find an animacy effect on external attention during stimulus presentation, with smaller pupil sizes for animate words than for inanimate words, which may reflect precision of encoding. This suggests that not internal attention, but external attention is influenced by animacy status, potentially explaining the memory advantage of animate items through the richness-of-encoding hypothesis.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Memory; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0z3118xn",
            "frozenauthors": [
                {
                    "first_name": "Julia",
                    "middle_name": "",
                    "last_name": "Perik",
                    "name_suffix": "",
                    "institution": "Erasmus University Rotterdam",
                    "department": ""
                },
                {
                    "first_name": "Muhammet Ikbal",
                    "middle_name": "",
                    "last_name": "Sahan",
                    "name_suffix": "",
                    "institution": "Erasmus University Rotterdam",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "",
                    "last_name": "Verheyen",
                    "name_suffix": "",
                    "institution": "Erasmus University Rotterdam",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49455/galley/37417/download/"
                }
            ]
        },
        {
            "pk": 49675,
            "title": "Assessing the Verbal Redundancy Effect by Adding Narration to Written Text  in Native and Non-Native Speakers",
            "subtitle": null,
            "abstract": "The addition of verbal narration could impede reading performance, called the verbal redundancy effect. Two experiments in this study explored the moderating role of readers' vocabulary size and text difficulty in this effect. A total of 77 native English speakers in Experiment 1 and 45 non-native English speakers in Experiment 2 were divided into two groups of vocabulary-size in each experiment. In both experiments, participants read eight passages and answered questions. The study manipulated the narration presentation and text difficulty. Experiment 1 showed that adding narration impedes comprehension when high-vocabulary participants read easy passages, whereas it enhances comprehension when low-vocabulary participants read easy passages. The redundant narration effect was moderated by reading skills. Experiment 2 showed no significant narration effect, but comprehension scores were higher when high-vocabulary multilinguals read neutral passages with narration than without narration. These effects are aligned with previous research and well explained by cognitive load theory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Psychology; Learning; Memory; Reading; Computer-based experiment"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4bm458r7",
            "frozenauthors": [
                {
                    "first_name": "Takumi",
                    "middle_name": "",
                    "last_name": "Arima",
                    "name_suffix": "",
                    "institution": "Hiroshima University",
                    "department": ""
                },
                {
                    "first_name": "Sarah",
                    "middle_name": "",
                    "last_name": "Baker",
                    "name_suffix": "",
                    "institution": "National Institutes of Health",
                    "department": ""
                },
                {
                    "first_name": "Amos En Zhe",
                    "middle_name": "",
                    "last_name": "Lian",
                    "name_suffix": "",
                    "institution": "Raffles University",
                    "department": ""
                },
                {
                    "first_name": "Weng-Tink",
                    "middle_name": "",
                    "last_name": "Chooi",
                    "name_suffix": "",
                    "institution": "Universiti Sains Malaysia",
                    "department": ""
                },
                {
                    "first_name": "Aiko",
                    "middle_name": "",
                    "last_name": "Morita",
                    "name_suffix": "",
                    "institution": "Hiroshima University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49675/galley/37637/download/"
                }
            ]
        },
        {
            "pk": 49401,
            "title": "Association between cognitive reserve and spatial ability across the lifespan",
            "subtitle": null,
            "abstract": "Spatial navigation is a promising cognitive marker for several cognitive disorders. However, its clinical utility is still limited because spatial abilities are also influenced by non-pathological factors. Among these, the Cognitive Reserve (CR) stands out due to its strong influence on cognitive aging trajectories. However, the association between CR and spatial navigation across the lifespan has never been assessed. In this study, we collected spatial navigation data along with CR measures in a population with diverse demographic profiles. We found a strong decline in spatial ability with age, but no overall effect of the CR. We systematically analyzed the association between each CR item and spatial ability and found that the subscore related to reading habits was significantly associated with spatial navigation performance, even after correcting for multiple comparisons. We discuss the implications of these findings for early and personalized screening for cognitive disorders using a spatial navigation task.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Behavioral Science; Culture; Reading; Spatial cognition; Quantitative Behavior"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3sx2b0h0",
            "frozenauthors": [
                {
                    "first_name": "Syrine",
                    "middle_name": "",
                    "last_name": "Salouhou",
                    "name_suffix": "",
                    "institution": "CNRS, INSA Lyon, Universite Claude Bernard Lyon 1",
                    "department": ""
                },
                {
                    "first_name": "Victor",
                    "middle_name": "",
                    "last_name": "Gilles",
                    "name_suffix": "",
                    "institution": "Hôpital des Charpennes, UniversitŽ Claude Bernard Lyon 1, Hospices Civils de Lyon",
                    "department": ""
                },
                {
                    "first_name": "RŽmi",
                    "middle_name": "",
                    "last_name": "VallŽe",
                    "name_suffix": "",
                    "institution": "CNRS, INSA Lyon, Universite Claude Bernard Lyon 1",
                    "department": ""
                },
                {
                    "first_name": "Elo•n",
                    "middle_name": "",
                    "last_name": "Camussi",
                    "name_suffix": "",
                    "institution": "CNRS, INSA Lyon, Universite Claude Bernard Lyon 1",
                    "department": ""
                },
                {
                    "first_name": "Romain",
                    "middle_name": "",
                    "last_name": "Vuillemot",
                    "name_suffix": "",
                    "institution": "Ecole Centrale de Lyon, CNRS, INSA Lyon, Universite Claude Bernard Lyon 1",
                    "department": ""
                },
                {
                    "first_name": "Antoine",
                    "middle_name": "",
                    "last_name": "Garnier-Crussard",
                    "name_suffix": "",
                    "institution": "Hôpital des Charpennes, UniversitŽ Claude Bernard Lyon 1, Hospices Civils de Lyon",
                    "department": ""
                },
                {
                    "first_name": "Antoine",
                    "middle_name": "",
                    "last_name": "Coutrot",
                    "name_suffix": "",
                    "institution": "CNRS, INSA Lyon, Universite Claude Bernard Lyon 1",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49401/galley/37363/download/"
                }
            ]
        },
        {
            "pk": 50404,
            "title": "A Study of Context Effect in Large Language Models",
            "subtitle": null,
            "abstract": "Large language models (LLMs) are increasingly used for decision-making, raising ethical questions about their decisions compared to human decision makers. A key aspect of human decision-making is the context effect, particularly how decoy options alter previous choices. This study examines whether LLMs exhibit similar context effects in human cognition. We test multiple GPT models using semantic choice probability prompts to assess four context effects: similarity, attraction, repulsion, and compromise. While LLMs exhibit some differences in their context effect maps compared to humans, they consistently exhibit all four-context effects examined qualitatively. Since users primarily seek suggestions rather than direct decisions, we also prompt LLMs to generate suggestions and pros-and-cons analyses, with results further confirming the context sensitivity of the LLMs. These findings suggest GPT models are not only effective in assisting context-dependent decision-making but also offer a scalable, cost-efficient tool for designing psychological study of context effects.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Decision making; Natural Language Processing; Computer-based experiment"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4fv3t754",
            "frozenauthors": [
                {
                    "first_name": "Xinjie",
                    "middle_name": "",
                    "last_name": "Xie",
                    "name_suffix": "",
                    "institution": "Carleton College",
                    "department": ""
                },
                {
                    "first_name": "Jiaqi",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Jerome",
                    "middle_name": "",
                    "last_name": "Busemeyer",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50404/galley/38366/download/"
                }
            ]
        },
        {
            "pk": 50225,
            "title": "A study on playing cards to disentangle order and magnitude in the SNARC effect",
            "subtitle": null,
            "abstract": "The SNARC effect would reflect a left-to-right mental number line (MNL). The aim of this study was to disentangle the roles of numbers' magnitude and order in the SNARC effect by using playing cards as stimuli. While most people hold cards in ascending order (AO), consistent with the MNL, a subset of individuals stably hold cards in descending order (DO), opposite to the MNL, with low-value cards (e.g., 2) on the right and high-value cards (e.g., 6) on the left. In a magnitude classification task (Experiment 1) and in a parity judgement task (Experiment 2) involving both digits and playing cards as stimuli, AO participants showed regular SNARC effects for both digits and cards, whereas DO participants showed regular SNARC effects for digits but not for cards. These results suggest that the order of cards in DO participants prevents the SNARC effect from occurring, but does not reverse the effect.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Perception; Spatial cognition; Computer-based experiment"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4pp116sh",
            "frozenauthors": [
                {
                    "first_name": "Claudia",
                    "middle_name": "Virginia",
                    "last_name": "Manara",
                    "name_suffix": "",
                    "institution": "University of Trieste",
                    "department": ""
                },
                {
                    "first_name": "Stefano",
                    "middle_name": "",
                    "last_name": "Pileggi",
                    "name_suffix": "",
                    "institution": "Department of Life Sciences, University of Trieste",
                    "department": ""
                },
                {
                    "first_name": "Valter",
                    "middle_name": "",
                    "last_name": "Prpic",
                    "name_suffix": "",
                    "institution": "eCampus University",
                    "department": ""
                },
                {
                    "first_name": "serena",
                    "middle_name": "",
                    "last_name": "mingolo",
                    "name_suffix": "",
                    "institution": "Department of Physics, University of Calabria",
                    "department": ""
                },
                {
                    "first_name": "Krzysztof",
                    "middle_name": "",
                    "last_name": "Cipora",
                    "name_suffix": "",
                    "institution": "Loughborough University",
                    "department": ""
                },
                {
                    "first_name": "Mauro",
                    "middle_name": "",
                    "last_name": "Murgia",
                    "name_suffix": "",
                    "institution": "University of Trieste",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50225/galley/38187/download/"
                }
            ]
        },
        {
            "pk": 50198,
            "title": "Asymmetries in the Production of Regular and Irregular Verbs",
            "subtitle": null,
            "abstract": "Humans, despite limited cognitive capacity, can generate an infinite variety of sentences thanks to regularities in language, though irregularities also exist (e.g., English past tense). We explore the mechanisms underlying the production of regular and irregular verbs and the role of domain-general processes, offering novel insights from a non-Indo-European language and both L1 and L2. Forty-seven adults conjugated verbs in L1 (Turkish) or L2 (English), and reaction time (RT) was analyzed to assess (1) the cost of switching between regulars and irregulars, and (2) whether individual differences in inhibitory control and working memory predict performance. RT for regular production differed depending on the preceding (N-2) trials (irregular-irregular-regular &gt; regular-irregular-regular), indicating the difficulty in retrieving a regular verb after repeated suppression. This pattern was absent for L1 irregulars or L2, suggesting regulars and irregulars rely on asymmetrical, distinct mechanisms, but only in L1. Neither inhibition nor working memory predicted RT.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language Production; Morphology"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0vw784cj",
            "frozenauthors": [
                {
                    "first_name": "Tuba Pelin",
                    "middle_name": "",
                    "last_name": "…ztŸrk",
                    "name_suffix": "",
                    "institution": "Sabancõ University",
                    "department": ""
                },
                {
                    "first_name": "Cansu",
                    "middle_name": "",
                    "last_name": "…zden",
                    "name_suffix": "",
                    "institution": "Sabancõ University",
                    "department": ""
                },
                {
                    "first_name": "Gšksu",
                    "middle_name": "",
                    "last_name": "Gamlõ",
                    "name_suffix": "",
                    "institution": "BoÄŸazi�i University",
                    "department": ""
                },
                {
                    "first_name": "Junko",
                    "middle_name": "",
                    "last_name": "Kanero",
                    "name_suffix": "",
                    "institution": "Sabanci University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50198/galley/38160/download/"
                }
            ]
        },
        {
            "pk": 49437,
            "title": "A Time-Aware Mental State Space for Multimodal Depression Detection on Social Media",
            "subtitle": null,
            "abstract": "Detecting depression from user-generated posts on social media platforms offers significant potential for early intervention on at-risk individuals. Existing works mainly concentrate on text processing, and only a limited number incorporate images posted by users. These image-integrated methods face challenges in modeling the intricate relationships between textual and visual features. Besides, the absence of approaches that explore psychological trajectory of users by analyzing their posts over time leaves a critical gap in capturing the progression of depressive symptoms. In this paper, we propose A Time-Aware Mental State Space (T-M2S) for detecting depression from social media posts. We introduce a Cross-Modal Learning that effectively integrates text and image embeddings into sentiment-oriented unified representations. Additionally, we design a Mental State Space to analyze users' posts over time, offering a nuanced understanding of emotional dynamics. Extensive experiments on Twitter and Reddit datasets demonstrate that T-M2S significantly outperforms state-of-the-art methods. Code and models are available at GitHub.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Emotion Disorder; Neural Networks; Social media analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/04v1h1pq",
            "frozenauthors": [
                {
                    "first_name": "Quang Vinh",
                    "middle_name": "",
                    "last_name": "Nguyen",
                    "name_suffix": "",
                    "institution": "Viettel Post",
                    "department": ""
                },
                {
                    "first_name": "Dong",
                    "middle_name": "Thanh",
                    "last_name": "Nguyen",
                    "name_suffix": "",
                    "institution": "FPT Software Quy Nhon",
                    "department": ""
                },
                {
                    "first_name": "Duc Duy",
                    "middle_name": "",
                    "last_name": "Nguyen",
                    "name_suffix": "",
                    "institution": "Hanoi University of Science and Technology",
                    "department": ""
                },
                {
                    "first_name": "Doan Khai",
                    "middle_name": "",
                    "last_name": "Ta",
                    "name_suffix": "",
                    "institution": "Hanoi University of Science and Technology",
                    "department": ""
                },
                {
                    "first_name": "Hai Binh",
                    "middle_name": "",
                    "last_name": "Nguyen",
                    "name_suffix": "",
                    "institution": "Viettel Post",
                    "department": ""
                },
                {
                    "first_name": "Ji-eun",
                    "middle_name": "",
                    "last_name": "Shin",
                    "name_suffix": "",
                    "institution": "Chonnam National University",
                    "department": ""
                },
                {
                    "first_name": "Seungwon",
                    "middle_name": "",
                    "last_name": "Kim",
                    "name_suffix": "",
                    "institution": "Chonnam National University",
                    "department": ""
                },
                {
                    "first_name": "Hyung-Jeong",
                    "middle_name": "",
                    "last_name": "Yang",
                    "name_suffix": "",
                    "institution": "Chonnam National University",
                    "department": ""
                },
                {
                    "first_name": "Soo-Hyung",
                    "middle_name": "",
                    "last_name": "Kim",
                    "name_suffix": "",
                    "institution": "Chonnam National University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49437/galley/37399/download/"
                }
            ]
        },
        {
            "pk": 50034,
            "title": "Augmented Proof: Examining Structures to Support Geometric Proof Comprehension",
            "subtitle": null,
            "abstract": "To understand even a modest geometric proof, students must process an interwoven combination of symbolic, diagrammatic, geometric, and logical information. This amount of information density presents a daunting management task that students are known to perform poorly on.\nTo address this challenge, we propose a two-column proof interface that structures the information management task according to diagram configuration schemas (DCS). We evaluated our design by comparing secondary school students' performance on proof comprehension tasks with DCS augmentation to using a typical two-column proof. Students using the DCS-augmented interface demonstrated improved overall reasoning and accuracy in geometric proof tasks compared to the traditional two-column format. They were also significantly better at identifying and correcting mistakes in proofs. These results suggest that managing complex information by integrating it in a coherent schema--like DCS--can support student understanding of proof.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Education; Complex systems; Human-computer interaction"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5bv6z191",
            "frozenauthors": [
                {
                    "first_name": "Hwei-Shin",
                    "middle_name": "",
                    "last_name": "Harriman",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Yuchen",
                    "middle_name": "",
                    "last_name": "Jin",
                    "name_suffix": "",
                    "institution": "University of Wisconsin - Madison",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Cheng",
                    "name_suffix": "",
                    "institution": "University of Sussex",
                    "department": ""
                },
                {
                    "first_name": "Dominik",
                    "middle_name": "",
                    "last_name": "Moritz",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Sunshine",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50034/galley/37996/download/"
                }
            ]
        },
        {
            "pk": 49539,
            "title": "Automatic Detection of Phonestheme-like features in Japanese – Insights for Cognitive Sound Symbolism Research",
            "subtitle": null,
            "abstract": "Sound symbolism is a linguistic feature that may suggest a non-arbitrary link between sound and semantic content that has been shown to play a role in language acquisition, and potentially language evolution. One sound-symbolic structure known as phonesthemes has been identified in many languages. Phonesthemes are sub-morphemic sound patterns associated with specific meanings more frequently than chance. Cognitive approaches to phonesthemes typically rely on a known example. Phonesthemes are not well attested in Japanese, so this approach is not an easy option. This research provides a route for research into the cognitive effects -- in particular language acquisition -- of Japanese sound symbolism. I present a model for identifying phonestheme-like features in Japanese adapted from a model originally used with English and identify two candidates in Japanese. I also outline methods for empirically testing the psychological reality of these clusters based on existing English and Japanese sound symbolism literature.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language acquisition; Language and thought; Natural Language Processing"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/82h5z41d",
            "frozenauthors": [
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Parker",
                    "name_suffix": "",
                    "institution": "San Francisco State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49539/galley/37501/download/"
                }
            ]
        },
        {
            "pk": 49239,
            "title": "A Variational Neural Network Model of Resource-Rational Reward Encoding in Human Planning",
            "subtitle": null,
            "abstract": "Working memory (WM) is essential for planning and decision-making, enabling us to temporarily store and manipulate information about potential future actions and their outcomes. Existing research on WM, however, has primarily considered contexts where stimuli are presented simultaneously and encoded independently. It thus remains unclear how WM dynamically manages information about reward and value during planning, when actions are evaluated sequentially in time and their cumulative values must be integrated to guide choice. To address this gap, we developed an information-theoretic model of WM allocation during planning, implemented using variational recurrent neural networks. In this model, an agent optimizes plan quality while maintaining reward information under WM constraints. To test our model, we designed a task in which participants sequentially observed the rewards available at different future states before executing a sequence of actions, attempting to maximize cumulative rewards. Our results suggest that humans preferentially maintain rewards that are most informative for plan selection, integrating both local and global factors. These findings bridge theories of WM limitations with models of human planning, revealing how cognitive constraints shape decision-making strategies.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Decision making; Memory; Computational Modeling; Neural Networks"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1jh635fd",
            "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": "Roy",
                    "middle_name": "",
                    "last_name": "Fox",
                    "name_suffix": "",
                    "institution": "University of California, Irvine",
                    "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": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49239/galley/37200/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49239/galley/38745/download/"
                }
            ]
        },
        {
            "pk": 49853,
            "title": "A Visual Complexity Measurement Method Based on Monte Carlo Sampling",
            "subtitle": null,
            "abstract": "Conventional visual complexity measurement faces challenges in efficiency, accuracy, and alignment with human perception. To address these, this paper presents a novel Monte Carlo-based method for visual complexity measurement, the random line segment width sampling algorithm (RLSWSA). RLSWSA employs local stochastic sampling for efficient estimation of symbol perimeter complexity. By discarding global scanning in favor of local sampling, RLSWSA significantly enhances computational efficiency while maintaining high accuracy and robustness. Experimental results show rapid convergence with just 24 samples, yielding high consistency with traditional methods (correlation coefficient &gt; 0.9). Furthermore, RLSWSA's Spearman correlation with human subjective ratings is 0.74, demonstrating its strong correlation with human perceptual complexity. This study offers an efficient and reliable solution for rapid symbol visual complexity calculation, with strong potential for applications like symbol recognition and design optimization.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Psychology; Aesthetics; Representation; Computational Modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5kv4h6p0",
            "frozenauthors": [
                {
                    "first_name": "Sihan",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "Jiangnan University",
                    "department": ""
                },
                {
                    "first_name": "Ruimin",
                    "middle_name": "",
                    "last_name": "Lyu",
                    "name_suffix": "",
                    "institution": "Jiangnan University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49853/galley/37815/download/"
                }
            ]
        },
        {
            "pk": 49264,
            "title": "Backwards counterfactuals and the closest possible world",
            "subtitle": null,
            "abstract": "One source of complexity in counterfactual reasoning is the order in which events are presented within the conditional. Counterfactuals with a backwards order of events (aka ‘backtracking' counterfactuals) involve reasoning backward: from the consequent to the antecedent. We extend on prior experimental work (e.g., Rips 2010), and consider the possibilities adults reason over when they backtrack. We find that adults' reasoning strategies tend to be inconsistent when responding to backtracking questions. In scenarios involving a single causal variable, participants do not generally allow for extraneous changes from the actual world. Furthermore, when reasoning forward along a causal chain, participants do not allow for extraneous changes. However, in backtracking scenarios involving multiple causal variables, participants are at chance in choosing worlds with extraneous changes. We provide novel evidence for the changes allowed from the actual world when backtracking, with mixed support for theoretical claims such as Minimal Networks Theory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Causal reasoning; Semantics of language"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0q93p7sc",
            "frozenauthors": [
                {
                    "first_name": "Ioana",
                    "middle_name": "",
                    "last_name": "Grosu",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Dominic",
                    "middle_name": "",
                    "last_name": "Le",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Patricia",
                    "middle_name": "",
                    "last_name": "Ganea",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49264/galley/37225/download/"
                }
            ]
        },
        {
            "pk": 49478,
            "title": "Balancing Conventional Pairings and Semantic Fit: Classifier Production in Mandarin-Speaking Children",
            "subtitle": null,
            "abstract": "This study examined how classifier-noun conventions and classifier semantic compatibility influence the selection of classifiers in Mandarin- speaking children aged five to seven. Results indicated that children's classifier use was shaped not only by conventional associations between classifiers and noun categories but also by semantic congruence, particularly in the absence of explicit noun labels. Older children demonstrated greater sensitivity to labels in guiding classifier selection than younger children. Furthermore, explicit noun labels most strongly boosted children's choice of conventional classifiers for non‑prototypical stimuli, while having a much smaller impact on prototypical stimuli. Overall, these results highlight the interplay between memorization and semantic compatibility in classifier acquisition and underscore the importance of semantic and perceptual features in shaping language learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive development; Language acquisition; Language Production; Semantics of language"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3jw368q6",
            "frozenauthors": [
                {
                    "first_name": "Erjing",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Ying",
                    "middle_name": "",
                    "last_name": "Hao",
                    "name_suffix": "",
                    "institution": "Nanjing Normal University",
                    "department": ""
                },
                {
                    "first_name": "Catherine",
                    "middle_name": "",
                    "last_name": "Sandhofer",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49478/galley/37440/download/"
                }
            ]
        },
        {
            "pk": 49565,
            "title": "Balancing Rigor and Utility: Mitigating Cognitive Biases in Large Language Models for Multiple-Choice Questions",
            "subtitle": null,
            "abstract": "This paper examines the role of cognitive biases in the decision-making processes of large language models (LLMs), challenging the conventional goal of eliminating all biases. When properly balanced, we show that certain cognitive biases can enhance decision-making efficiency through rational deviations and heuristic shortcuts. By introducing heuristic moderation and an abstention option, which allows LLMs to withhold responses when uncertain, we reduce error rates, improve decision accuracy, and optimize decision rates. Using the Balance Rigor and Utility (BRU) dataset, developed through expert collaboration, our findings demonstrate that targeted inspection of cognitive biases aligns LLM decisions more closely with human reasoning, enhancing reliability and suggesting strategies for future improvements. This approach offers a novel way to leverage cognitive biases to improve the practical utility of LLMs across various applications.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Decision making; Natural Language Processing"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2vr690cx",
            "frozenauthors": [
                {
                    "first_name": "hanyang",
                    "middle_name": "",
                    "last_name": "zhong",
                    "name_suffix": "",
                    "institution": "University of York",
                    "department": ""
                },
                {
                    "first_name": "Liman",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "University of York",
                    "department": ""
                },
                {
                    "first_name": "WENTING",
                    "middle_name": "",
                    "last_name": "CAO",
                    "name_suffix": "",
                    "institution": "Jena University Hospital",
                    "department": ""
                },
                {
                    "first_name": "ZEYUAN",
                    "middle_name": "",
                    "last_name": "SUN",
                    "name_suffix": "",
                    "institution": "King's College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49565/galley/37527/download/"
                }
            ]
        },
        {
            "pk": 49470,
            "title": "Base Rate Neglect in Linguistic Category Learning",
            "subtitle": null,
            "abstract": "This paper presents a categorization experiment supporting the hypothesis that base-rate-neglect occurs in linguistic category learning (and, thus, is a cross-domain phenomenon), and that it is more likely for those learners who engage in explicit problem-solving, rather than implicit learning. We find that among those participants who were able to verbalize the cue that was probabilistically associated with category-membership (correct-staters) in a phonological learning task, about a third respond in a way consistent with base-rate-neglect. On the other hand, non-staters are more likely to respond randomly or by probability matching the base-rates. These results suggest that explicit learning is associated with base-rate-neglect to a greater extent. We found that no learners integrate the two probabilistic patterns present in the experiment into a single Bayesian estimate. Rather, some of them focus on the base-rates, others focus on category-internal cues, and others simply fail to learn anything.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Concepts and categories; Decision making; Phonology"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6nf8q6dp",
            "frozenauthors": [
                {
                    "first_name": "Katya",
                    "middle_name": "",
                    "last_name": "Pertsova",
                    "name_suffix": "",
                    "institution": "University of North Carolina, Chapel Hill",
                    "department": ""
                },
                {
                    "first_name": "Elliott",
                    "middle_name": "",
                    "last_name": "Moreton",
                    "name_suffix": "",
                    "institution": "UNC, Chapel Hill",
                    "department": ""
                },
                {
                    "first_name": "Josh",
                    "middle_name": "",
                    "last_name": "Fennell",
                    "name_suffix": "",
                    "institution": "Fizz Studio",
                    "department": ""
                },
                {
                    "first_name": "Brandon",
                    "middle_name": "",
                    "last_name": "Prickett",
                    "name_suffix": "",
                    "institution": "UMass",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49470/galley/37432/download/"
                }
            ]
        },
        {
            "pk": 50289,
            "title": "Bayes-Adaptive Information Gathering",
            "subtitle": null,
            "abstract": "Problem-solving often requires both acting on and gathering information from the environment. Prior work in psychology proposes that people are intrinsically motivated to seek information (Ryan and Deci, 2000; Ruggeri et al., 2021). However, in realistic settings most available information has no utility, so optimal performance requires estimating its value. We introduce a model that applies the Bayesian framework of Lidayan et al. (2024), which formalizes the value of information as the resulting increase in expected rewards. Our model calculates the utility of information-gathering actions and treats humans as noisy utility-maximizers. We design a novel task in which information sources vary in their likelihood of enabling downstream rewards. Preliminary results suggest our model predicts human behavior more accurately than intrinsic motivation models, suggesting that humans learn to estimate the value of information from experience, and use it to make better decisions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision making; Learning; Bayesian modeling; Computational Modeling; Quantitative Behavior"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9gn7s8j6",
            "frozenauthors": [
                {
                    "first_name": "Aly",
                    "middle_name": "",
                    "last_name": "Lidayan",
                    "name_suffix": "",
                    "institution": "UC Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Luigi",
                    "middle_name": "",
                    "last_name": "Acerbi",
                    "name_suffix": "",
                    "institution": "University of Helsinki",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50289/galley/38251/download/"
                }
            ]
        },
        {
            "pk": 50107,
            "title": "Bayesian Model of Goal Direction Inference in Animacy Perception from Moving Dots",
            "subtitle": null,
            "abstract": "The phenomenon of perceiving lifelikeness in the movements of non-living objects is referred to as animacy perception. This study hypothesized that when humans infer intentionality from motion information, they initially estimate the direction of the goal of the movement in a Bayesian manner. The magnitude of change in this estimated direction reflects the strength of intentionality and self-propelledness, which are correlated with the perceived strength of animacy. We tested this hypothesis through an experiment in which participants evaluated animacy, intentionality, and self-propelledness for dots moving on a screen. The results revealed that although the magnitude of motion direction changes did not directly influence intentionality and self-propelledness, both the magnitude of goal direction changes and variance had a significant impact. These findings suggest that animacy perception may be realized through hierarchical Bayesian estimation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Perception; Predictive Processing; Theory of Mind; Bayesian modeling; Mathematical modeling"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5mg8j48g",
            "frozenauthors": [
                {
                    "first_name": "Keisuke",
                    "middle_name": "",
                    "last_name": "Sato",
                    "name_suffix": "",
                    "institution": "The University of Tokyo",
                    "department": ""
                },
                {
                    "first_name": "Kazuhiro",
                    "middle_name": "",
                    "last_name": "Ueda",
                    "name_suffix": "",
                    "institution": "The University of Tokyo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50107/galley/38069/download/"
                }
            ]
        },
        {
            "pk": 50089,
            "title": "BDARec: Balancing Diversity and Accuracy of Recommendation Model with Graph Neural Networks",
            "subtitle": null,
            "abstract": "Based on research in cognitive psychology, humans typically seek a balance between their preference for familiar things and the exploration of new ones during decision-making. Therefore, studying the relationship between accuracy and diversity in recommendation systems is particularly meaningful. In recent years, recommendation systems based on Graph Neural Networks (GNNs) have garnered significant attention for enhancing recommendation accuracy or diversity. However, existing works often improve accuracy or diversity at the expense of the other aspect, which is inconsistent with the complex needs of users. In this paper, we propose a novel Recommendation model that Balances Diversity and Accuracy with GNNs, called BDARec. Firstly, BDARec proposes a balanced neighborhood aggregation strategy to select diverse and accurate neighbor nodes for updating node embeddings in user-item bipartite heterogeneous graph. Secondly, to accelerate the convergence of BDARec, an enhanced category-boosted negative sampling strategy is proposed to select negative samples from the same category positive samples with a certain probability. Thirdly, we put forward a dynamic feature for each item to measure the importance of items in training phase. Finally, we conduct extensive experiments on three real-world datasets. Experimental results show that our model can even improve recall by 22.04%, hit_ratio by 16.46%, and coverage by 10.27% when compared to the state-of-the-art comparison algorithm, which verifies that the proposed model can achieve the best balance between diversity and accuracy.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Big data; Knowledge representation; Neural Networks"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5h13q643",
            "frozenauthors": [
                {
                    "first_name": "Mengmeng",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Xinhai",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Hongmei",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Zhenyu",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Academy of Military Science",
                    "department": ""
                },
                {
                    "first_name": "Xianglong",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "Academy of Military Sciences",
                    "department": ""
                },
                {
                    "first_name": "Jinlong",
                    "middle_name": "",
                    "last_name": "Tian",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Kejia",
                    "middle_name": "",
                    "last_name": "Wan",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                },
                {
                    "first_name": "Qiyuan",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "National University of Defense Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50089/galley/38051/download/"
                }
            ]
        },
        {
            "pk": 50403,
            "title": "Be concrete and specific: how speakers introduce novel topics in naturalistic language",
            "subtitle": null,
            "abstract": "We asked whether the concreteness and specificity of the language used by conversation participants change depending upon the familiarity and the presence/absence of an object discussed. Additionally, we explored whether interlocutors engaged in distinct abstraction processes (analogical comparison; superordinate categorization) and whether they focused more on object's features or on their own experience.  \n\nWe used the ECOLANG corpus (Gu et al., 2025), a semi-naturalistic dataset of interactions in which 31 knowledgeable \"speakers\" describe novel/known objects to an \"addressee\" when the object is physically present or absent. We analyzed 22,581 sentences produced by the \"speaker\" and measured the concreteness and specificity of 1,612 nouns used.   \n\nResults showed that more concrete and specific nouns were used for novel objects suggesting a need for precise information.  Additionally, abstraction processes were more likely when the object was present and novel. Finally, when the object was present and known, interlocutors focused more on personal experience.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Concepts and categories; Language and thought; Pragmatics; Representation; Situated cognition; Social cognition; Corpus studies; Quantitative Behavior"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9r16h9gt",
            "frozenauthors": [
                {
                    "first_name": "Tommaso",
                    "middle_name": "",
                    "last_name": "Lamarra",
                    "name_suffix": "",
                    "institution": "University of Bologna",
                    "department": ""
                },
                {
                    "first_name": "Andrea Amelio",
                    "middle_name": "",
                    "last_name": "Ravelli",
                    "name_suffix": "",
                    "institution": "Università di Bologna",
                    "department": ""
                },
                {
                    "first_name": "Marianna",
                    "middle_name": "M",
                    "last_name": "Bolognesi",
                    "name_suffix": "",
                    "institution": "Modern Languages Dep",
                    "department": ""
                },
                {
                    "first_name": "Gabriella",
                    "middle_name": "",
                    "last_name": "Vigliocco",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50403/galley/38365/download/"
                }
            ]
        },
        {
            "pk": 49164,
            "title": "Behavioral Characteristics of Learning Phases: How Individual Differences Shape Learning Trajectories in a Virtual Environment",
            "subtitle": null,
            "abstract": "Procedural learning occurs in three phases—cognitive, associative, and autonomous—enabling skill acquisition across domains like medicine and sports. However, learning efficiency varies due to individual differences. While factors like cognitive abilities and learning environments influence this variability, their effects across learning phases remain understudied, particularly in Virtual Reality (VR). This study examines how cognitive abilities (memory span, mental rotation) and VR-related factors (familiarity, cybersickness) impact performance in a 3D assembly task within an immersive VR environment. Results reveal that lower VR familiarity prolongs task completion in early phases, highlighting interaction-related challenges. Higher mental rotation ability enhances performance in the autonomous phase, whereas cybersickness hinders efficiency. These findings suggest that adapting VR-based learning scenarios to individual profiles—such as early guidance for VR novices and phase-specific challenge adjustments—could optimize learning outcomes. Additionally, considering cybersickness effects in advanced phases supports the use of distributed learning approaches to mitigate discomfort.",
            "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/8m1519vw",
            "frozenauthors": [
                {
                    "first_name": "Ana•s",
                    "middle_name": "",
                    "last_name": "Raison",
                    "name_suffix": "",
                    "institution": "UBO",
                    "department": ""
                },
                {
                    "first_name": "LEBIGOT",
                    "middle_name": "",
                    "last_name": "Nathalie",
                    "name_suffix": "",
                    "institution": "UBO",
                    "department": ""
                },
                {
                    "first_name": "Olivier",
                    "middle_name": "",
                    "last_name": "Augereau",
                    "name_suffix": "",
                    "institution": "ENIB",
                    "department": ""
                },
                {
                    "first_name": "Franck",
                    "middle_name": "",
                    "last_name": "Ganier",
                    "name_suffix": "",
                    "institution": "UBO",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49164/galley/37125/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49164/galley/38670/download/"
                }
            ]
        },
        {
            "pk": 49522,
            "title": "Behavioral Evidence is Still Insufficient to Identify Consciousness",
            "subtitle": null,
            "abstract": "Researchers have started seriously considering the epistemic\nissue of whether and when we can claim an artificial intelli-\ngence (AI) has developed machine consciousness. Most cog-\nnitive theories of consciousness employ a functional character-\nization of the property of consciousness. That is, they are com-\nmitted to an account of consciousness as a rule-governed pro-\ncess over mental states. Some cognitive scientists concerned\nwith AI advocate an epistemically behaviorist approach to ma-\nchine consciousness; however, such approaches taken ontolog-\nically, systematically fail to satisfy reasonable intuitions about\nin what consciousness ought to consist, and taken epistemi-\ncally, fail to provide sufficient evidence to individuate any in-\nternal property, including consciousness, in non-human sub-\njects. Therefore, in order to assess consciousness in ways that\nadequately account for reasonable intuitions as to its proper\ndefinition, such that we can reasonably assert the presence of\nmachine consciousness in some AI, it is necessary to propose,\ntest, and revise, functional theories of consciousness.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Philosophy; Psychology; Behavioral Science; Consciousness"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/71c0v672",
            "frozenauthors": [
                {
                    "first_name": "Maria",
                    "middle_name": "",
                    "last_name": "Vorobeva",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "Eilene",
                    "middle_name": "",
                    "last_name": "Tomkins Flanagan",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "Mary",
                    "middle_name": "Alexandria",
                    "last_name": "Kelly",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49522/galley/37484/download/"
                }
            ]
        },
        {
            "pk": 49124,
            "title": "Behavioral Network Science",
            "subtitle": null,
            "abstract": "Structure matters in cognitive science. Whether we are asking about memory retrieval, semantic representations, categorization, language acquisition, learning from complex information, aging, or creativity, cognitive scientists often find themselves forced to reckon with structure. Network science offers a quantitative approach for doing this by allowing us to ask questions about the relationships between various entities at scales ranging from dyads, to communities, to entire systems. In this case, the entities are the nodes in the network and the relationships are the edges between them. Exploring how this plays out in actual practice is incredibly varied, aesthetically and intellectually beautiful, and deeply rewarding, allowing us to develop and test hypotheses about cognition that are not otherwise possible. As a metric ruler measures length, allowing us to compare human height with the Burj Khalifa, network science measures structure, allowing us to compare the structure of our environments with the structure of our cognitive representations, how those representations change across the lifespan, and how different processes interacting with those structures generate behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Workshop",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7mj2m933",
            "frozenauthors": [
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Hills",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49124/galley/37085/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49124/galley/38630/download/"
                }
            ]
        },
        {
            "pk": 49535,
            "title": "Behavioral signatures of temporal context retrieval during continuous recognition",
            "subtitle": null,
            "abstract": "An influential mathematical model of memory, the temporal\ncontext model (TCM), posits that we encode items and their\nassociations with temporal context (Howard &amp; Kahana, 2002).\nTemporal context is conceived of as a recency-weighted av-\nerage of past experiences. Critically, the model assumes that\nwhen an item is retrieved later, the associated temporal con-\ntext is also obligatorily retrieved. Existing evidence for the\nidea of retrieved temporal context primarily comes from free-\nrecall studies. However, free recall introduces some critical\nconfounds that are difficult to resolve (Folkerts et al., 2018)\nand also encourages memory strategies that may mimic tem-\nporal context effects (Hintzman, 2011). To address these con-\nfounds, we investigate temporal context using an image recog-\nnition task. Schwartz et al. (2005) examined temporal con-\ntext in an image recognition task using a short-list-based ex-\nperimental design, and found that temporal context influenced\nrecognition performance. Building on this, we use the Natural\nScenes Dataset (NSD) to show that reinstating temporal con-\ntext enhances recognition accuracy even across substantially\nlonger timescales. We demonstrate that images that were tem-\nporally closer during encoding facilitated the recognition of\neach other. Critically, we show that this influence falls off with\ntemporal distance at encoding only when the temporal context\nis successfully retrieved, as predicted by TCM. Furthermore,\nthe slope of this temporal gradient increases as a function of\nthe strength of the influence of the retrieved temporal context.\nThese findings extend our understanding of temporal context\neffects in episodic memory by showing that temporal context\nis retrieved even in tasks that do not encourage linking between\nitems as a memory strategy.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Neuroscience; Behavioral Science; Memory; Mathematical modeling"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/21q2s8n1",
            "frozenauthors": [
                {
                    "first_name": "Atharva",
                    "middle_name": "",
                    "last_name": "Joshi",
                    "name_suffix": "",
                    "institution": "International Institute of Information Technology, Hyderabad",
                    "department": ""
                },
                {
                    "first_name": "Kamalaker",
                    "middle_name": "",
                    "last_name": "Dadi",
                    "name_suffix": "",
                    "institution": "International Institute of Information Technology Hyderabad",
                    "department": ""
                },
                {
                    "first_name": "Vishnu",
                    "middle_name": "",
                    "last_name": "Sreekumar",
                    "name_suffix": "",
                    "institution": "International Institute of Information Technology, Hyderabad",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49535/galley/37497/download/"
                }
            ]
        },
        {
            "pk": 49345,
            "title": "Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality",
            "subtitle": null,
            "abstract": "A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that agents may hold about the world and the rich language we can use to express them, which specific beliefs are people inclined to attribute to others? In this paper, we investigate the hypothesis that people prefer to attribute beliefs that are good explanations for the behavior they observe. We develop a computational model that quantifies the explanatory strength of a (natural language) statement about an agent's beliefs via three factors: accuracy, informativity, and causal relevance to actions, each of which can be computed from a probabilistic generative model of belief-driven behavior. Using this model, we study the role of each factor in how people selectively attribute beliefs to other agents. We investigate this via an experiment where participants watch an agent collect keys hidden in boxes in order to reach a goal, then rank a set of statements describing the agent's beliefs about the boxes' contents. We find that accuracy and informativity perform reasonably well at predicting these rankings when combined, but that causal relevance is the single factor that best explains participants' responses.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Linguistics; Psychology; Language and thought; Language understanding; Social cognition; Theory of Mind; Bayesian modeling"
                }
            ],
            "section": "Abstracts with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/72p643f8",
            "frozenauthors": [
                {
                    "first_name": "Lance",
                    "middle_name": "",
                    "last_name": "Ying",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Almog",
                    "middle_name": "",
                    "last_name": "Hilel",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Ryan",
                    "middle_name": "",
                    "last_name": "Truong",
                    "name_suffix": "",
                    "institution": "University of Texas at Austin",
                    "department": ""
                },
                {
                    "first_name": "Vikash",
                    "middle_name": "",
                    "last_name": "Mansinghka",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "B.",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Tan",
                    "middle_name": "",
                    "last_name": "Zhi-Xuan",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49345/galley/37306/download/"
                }
            ]
        },
        {
            "pk": 50032,
            "title": "Benchmarking LLMs for Mimicking Child-Caregiver Language in Interaction",
            "subtitle": null,
            "abstract": "Child-directed speech (CDS) is characterized by its adaptive nature: Caregivers not only talk to children, but engage in dy- namic interactions with them. The adaptive/interactive nature of this type of language is understudied in computational mod- eling research, particularly given the limited availability of nat- uralistic data. While recent advances in large language models (LLMs) have demonstrated potential for generating viable syn- thetic dialogue data in various domains, their ability to capture the dynamics of child-caregiver communication remains un- explored. This paper introduces a systematic framework for evaluating LLMs' capacity to generate developmentally ap- propriate CDS in interaction, examining both static linguistic features and dynamic conversational patterns. We evaluated state-of-the-art LLMs (GPT-4o and Llama 3) against natural interactions from the CHILDES dataset using both single- and multi-turn testing approaches. In single-turn evaluation, mod- els generated responses to individual child utterances, enabling direct comparison with actual caregiver responses. Multi-turn testing assessed sustained interaction capabilities through sim- ulated child-caregiver dialogues. Our results show that while LLMs can successfully approximate surface-level linguistic patterns after few-shot prompting, they struggle with higher- level communicative aspects, with excessive alignment and re- duced diversity compared to natural interactions. Our bench- marking framework elucidates both the potential and limita- tions of LLMs in generating data that preserves the essential properties of child-caregiver language in interactions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Linguistics; Language acquisition; Natural Language Processing; Pragmatics"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/36c9w8qn",
            "frozenauthors": [
                {
                    "first_name": "Jing",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "ENS",
                    "department": ""
                },
                {
                    "first_name": "Abdellah",
                    "middle_name": "",
                    "last_name": "Fourtassi",
                    "name_suffix": "",
                    "institution": "Aix-Marseille University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50032/galley/37994/download/"
                }
            ]
        },
        {
            "pk": 49249,
            "title": "Beyond Crosslinguistic Influence: Mandarin Speakers with Exposure to Null-subject Languages Nonetheless Use Fewer Null Pronouns in Mandarin",
            "subtitle": null,
            "abstract": "We explore the impact of crosslinguistic influence in first language (L1) attrition, changes in an individual's L1 due to exposure to additional languages. We report an experiment examining reference production in Mandarin in a picture description task by native Chinese speakers residing in Italy or Spain. Mandarin allows null subjects, where subjects can be expressed with a null or overt pronoun; previous work shows that L1 Mandarin speakers exposed to English use more overt pronouns in Mandarin than their more-monolingual peers. In the study reported here, despite exposure to two languages (Italian and Spanish) that, unlike English, allow null subjects, our multilingual speakers used fewer null pronouns and more overt pronouns than their more-monolingual Chinese peers. These findings contribute to attrition research by disentangling the impact of crosslinguistic influence in L1 attrition, and provide insights into the effect of bi- and multilingualism on linguistic systems.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Behavioral Science; Language Production; Pragmatics; Cross-linguistic analysis"
                }
            ],
            "section": "Papers with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4h69k203",
            "frozenauthors": [
                {
                    "first_name": "Yajun",
                    "middle_name": "",
                    "last_name": "Liu",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Antonella",
                    "middle_name": "",
                    "last_name": "Sorace",
                    "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": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49249/galley/37210/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49249/galley/38755/download/"
                }
            ]
        },
        {
            "pk": 50141,
            "title": "Beyond East and West: Cognitive Preferences in English, Chinese and Japanese Event Description",
            "subtitle": null,
            "abstract": "This study challenges traditional East-West dichotomies in cross-linguistic cognition by examining event construal preferences across English, Chinese, and Japanese speakers. We investigated how 90 participants (30 per language group) described visual stimuli depicting agent-patient interactions with varying animacy types. Statistical analysis revealed that Chinese speakers' construal patterns aligned with English speakers (p&gt;.05), contrasting sharply with Japanese speakers despite China's cultural proximity to Japan. Both English and Chinese groups demonstrated greater flexibility in perspective-taking across all agent types (human&gt;animal&gt;object), while Japanese speakers showed significantly stronger constraints with inanimate agents (p&lt;.0001). These findings suggest that grammatical flexibility in encoding perspectives, rather than cultural grouping, shapes cognitive preferences in event description. Our results indicate that linguistic structures may influence cognition independently of cultural boundaries, revealing a more complex relationship among language structure, cognitive preferences, and traditional cultural categorizations than previously assumed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistics; Psychology; Language and thought; Cross-cultural analysis; Cross-linguistic analysis"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9048k7md",
            "frozenauthors": [
                {
                    "first_name": "Siyu",
                    "middle_name": "",
                    "last_name": "Luo",
                    "name_suffix": "",
                    "institution": "University of Tokyo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50141/galley/38103/download/"
                }
            ]
        },
        {
            "pk": 50055,
            "title": "Beyond Emotion: Unraveling the Limited Role of Sentiment in Extended-Format Communication",
            "subtitle": null,
            "abstract": "Human communication is shaped by various factors, including linguistic structure, social context, and cognitive capacity. Among these, emotion plays a pivotal role in significantly influencing message delivery and reception. While emotional impact is prominent in social media posts, its effect in extended-format, information-rich communication, such as TED Talks, is less understood. This study focuses on six basic emotions (anger, disgust, fear, joy, sadness, and surprise) and examines their effects on TED Talk popularity using the NRC Emotion Lexicon and a BERT-based sentiment analysis model. Our findings reveal a stark contrast between social media and TED Talks: most emotions, including high-arousal emotions, have no significant effect on TED Talk viewership, and in some cases, intense emotional expressions negatively impact views. This study highlights the limited role of emotions in extended-format communication and underscores the importance of appropriate emotional expressions, shaped by context and audience expectations. By integrating transparent dictionary-based methods with contextually aware deep learning approaches, we provide a comprehensive framework for analyzing emotion-driven engagement in diverse communication settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Humanities; Linguistics; Discourse; Emotion; Social media analysis"
                }
            ],
            "section": "Abstracts with Poster Presentation (accepted as Abstracts)",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9027m2dc",
            "frozenauthors": [
                {
                    "first_name": "Jingyi",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Zhejiang University",
                    "department": ""
                },
                {
                    "first_name": "Shuhao",
                    "middle_name": "",
                    "last_name": "Fu",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Rick",
                    "middle_name": "",
                    "last_name": "Dale",
                    "name_suffix": "",
                    "institution": "UCLA",
                    "department": ""
                },
                {
                    "first_name": "Tao",
                    "middle_name": "",
                    "last_name": "Gao",
                    "name_suffix": "",
                    "institution": "University of California - Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Junying",
                    "middle_name": "",
                    "last_name": "Liang",
                    "name_suffix": "",
                    "institution": "Zhejiang University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50055/galley/38017/download/"
                }
            ]
        },
        {
            "pk": 50397,
            "title": "Beyond Interpolation: Enhancing Large Language Models (LLMs) with Mental Models",
            "subtitle": null,
            "abstract": "Large Language Models (LLMs) demonstrate high performance across various tasks, yet they struggle with those requiring complex comprehension and reasoning. LLMs are not solely reliant on memorization: responses can be generated to novel prompts by interpolating between learned data points in a continuous vector space. However, they exhibit limitations in their inherent reasoning capabilities.\nDespite efforts to enhance their reasoning abilities, such as Chain-of-Thought prompting and test-time inference techniques, LLMs still face challenges in this domain. In contrast, humans utilize mental models—internal representations of situations and concepts—to adapt and solve novel situations.\nIntegrating external modules that emulate the construction and utilization of mental models could offer a promising avenue for enhancing the reasoning abilities of LLMs. This approach could bridge the gap between current LLM capabilities and human-like reasoning, potentially leading to more robust and reliable LLMs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Artificial Intelligence; Psychology; Neural Networks"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5k8295z6",
            "frozenauthors": [
                {
                    "first_name": "SalomŽ",
                    "middle_name": "",
                    "last_name": "Cojean",
                    "name_suffix": "",
                    "institution": "Univ. Grenoble Alpes",
                    "department": ""
                },
                {
                    "first_name": "Nicolas",
                    "middle_name": "",
                    "last_name": "Martin",
                    "name_suffix": "",
                    "institution": "LIG",
                    "department": ""
                },
                {
                    "first_name": "Petra",
                    "middle_name": "",
                    "last_name": "Galuscakova",
                    "name_suffix": "",
                    "institution": "University of Stavanger",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50397/galley/38359/download/"
                }
            ]
        },
        {
            "pk": 49330,
            "title": "Beyond Muller-Lyer: Culture shapes ‘universal' visual phenomenology in multiple illusions across a rural-urban gradient",
            "subtitle": null,
            "abstract": "How cultural experience affects visual perception is a question of outstanding interest to debates regarding universality and cultural-specificity in human cognition. Yet, work comparing visual perception in 'typical' urban, industrialized samples with groups living in rural environments, typical for 99% of our species' history is strikingly limited (Deregowski, 2017). Here we more than double the total number of paradigms (visual illusions) in this literature, reporting data from 1) a 'typical' UK/US urban sample 2) a developing Namibian town 3) rural Namibian villages. Results reveal profound differences in visual processing, including aspects previously assumed to be universal (e.g. amodal completion in Gestalt shapes, line perception in the Cafe wall illusion). In contrast to recent arguments for the limited role of cultural experience in visual perception (Amir &amp; Firestone, 2025), the present work indicates that a major research program in CCVS is warranted to capture the ways culture shapes visual perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Culture; Vision; Cross-cultural analysis"
                }
            ],
            "section": "Abstracts with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/90b3p03b",
            "frozenauthors": [
                {
                    "first_name": "Ivan",
                    "middle_name": "",
                    "last_name": "Kroupin",
                    "name_suffix": "",
                    "institution": "London School of Economics and Political Science",
                    "department": ""
                },
                {
                    "first_name": "Helen Elizabeth",
                    "middle_name": "",
                    "last_name": "Davis",
                    "name_suffix": "",
                    "institution": "Arizona State University",
                    "department": ""
                },
                {
                    "first_name": "Aparicio Jose Paredes",
                    "middle_name": "",
                    "last_name": "Lopes",
                    "name_suffix": "",
                    "institution": "London School of Economics and Political Science",
                    "department": ""
                },
                {
                    "first_name": "Talia",
                    "middle_name": "",
                    "last_name": "Konkle",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Muthukrishna",
                    "name_suffix": "",
                    "institution": "London School of Economics and Political Science",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49330/galley/37291/download/"
                }
            ]
        },
        {
            "pk": 50449,
            "title": "Beyond Rewards: How Information Value and Time Horizon Shape Exploration",
            "subtitle": null,
            "abstract": "Prior research has shown that American children (ages 3 to 8) explore uncertain options at strikingly high rates — even when it comes at a cost to reward maximization, when explicitly instructed to seek rewards, and whether they are choosing for themselves or others. In contrast, adults explore significantly less, showing greater sensitivity to cost. What drives this developmental difference? In a series of studies, we test whether children's exploration is motivated by information value rather than reward value and whether adults also incorporate information value into their decisions. We also examine the role of time horizon in the explore-exploit tradeoff. Our findings reveal that both children and adults consider information value and time horizon when deciding whether to explore or exploit.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Decision making; Development; Reasoning"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0qc3s1h6",
            "frozenauthors": [
                {
                    "first_name": "Annya",
                    "middle_name": "",
                    "last_name": "Dahmani",
                    "name_suffix": "",
                    "institution": "UC Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Dorsa",
                    "middle_name": "",
                    "last_name": "Amir",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Alison",
                    "middle_name": "",
                    "last_name": "Gopnik",
                    "name_suffix": "",
                    "institution": "University of California at Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50449/galley/38411/download/"
                }
            ]
        },
        {
            "pk": 50406,
            "title": "Beyond Word Meaning Mappings: The Role of Low-Informative Events in Conceptual Alignment",
            "subtitle": null,
            "abstract": "Word meanings are rarely transparent from their extralinguistic contexts. How children learn words from an input with \"low-informative\" (LI) events is of interest because even adults struggle to learn from LI events (Gleitman &amp; Trueswell, 2020; Medina et al., 2011). This study revisited LI events' contribution to learning by probing what can be gleaned from LI events even if they don't yield exact meanings. Adults (N = 120) learned words (e.g., \"modi\") that had English meanings (e.g., \"apple\") from LI events. Participants then both guessed the word's exact meaning and rated several candidate meanings. Although LI events failed to yield accurate mappings of meanings, they led to representations (derived via the ratings) that were semantically aligned with those of the true meanings. These results highlight the potential for LI events to get learning off the ground and the implications of viewing word learning as more than a mapping problem.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Language acquisition; Learning; Knowledge representation"
                }
            ],
            "section": "Member Abstracts with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0z65s1q1",
            "frozenauthors": [
                {
                    "first_name": "Menghan",
                    "middle_name": "",
                    "last_name": "Yang",
                    "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": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/50406/galley/38368/download/"
                }
            ]
        },
        {
            "pk": 49795,
            "title": "Beyond words and actions: what implicit measures reveal in preschoolers' performance on the RMTS task",
            "subtitle": null,
            "abstract": "This study investigates relational reasoning in preschoolers using the Relational-Match-To-Sample (RMTS) task, which tests their ability to match \"same\" and \"different\" relations. We investigate (1) whether 4-year-old children can succeed in the RMTS task and (2) whether verbal justifications of relational language predict success. Forty-nine children participated (Mage=54.97 months), and their performance was measured both behaviourally and through eye-tracking. Results show children identified relational matches above chance. Children who used relational language selected relational matches more often. Eye-tracking data revealed distinct temporal looking patterns during relational and non-relational choice trials, with children preferring relational matches after a brief comparison phase. A cluster-based analysis confirmed that children looked longer at relational than non-relational matches. These findings suggest that relational reasoning in preschoolers involves a dynamic comparison process, and eye-tracking provides valuable insight into this implicit cognitive process.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Cognitive development; Language and thought; Eye tracking"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1m86f5g8",
            "frozenauthors": [
                {
                    "first_name": "Antonia",
                    "middle_name": "",
                    "last_name": "Goetz",
                    "name_suffix": "",
                    "institution": "Western Sydney University",
                    "department": ""
                },
                {
                    "first_name": "Genevieve",
                    "middle_name": "L",
                    "last_name": "Quek",
                    "name_suffix": "",
                    "institution": "Western Sydney University",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "Kathleen",
                    "last_name": "Fimmano",
                    "name_suffix": "",
                    "institution": "Western Sydney University",
                    "department": ""
                },
                {
                    "first_name": "Zoe-Vasilia",
                    "middle_name": "",
                    "last_name": "Fountotos",
                    "name_suffix": "",
                    "institution": "MARCS Institute",
                    "department": ""
                },
                {
                    "first_name": "Susan",
                    "middle_name": "",
                    "last_name": "Hespos",
                    "name_suffix": "",
                    "institution": "Western Sydney Univeristy",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49795/galley/37757/download/"
                }
            ]
        },
        {
            "pk": 49456,
            "title": "Bilinguals exhibit semantic convergence while maintaining near-optimal efficiency",
            "subtitle": null,
            "abstract": "Systems of semantic categories vary across languages, but this\nvariation appears to be constrained by pressure for optimizing\na complexity-accuracy tradeoff known as the Information Bottleneck\n(IB) principle. This finding, however, has been based\nprimarily on individual languages and it remains largely unknown\nhow bilinguals navigate the category systems of two\ndifferent languages, particularly when these languages' category\nboundaries do not overlap. Here, we address this gap\nin the literature by combining theory-driven experiments with\nan extension of the IB framework to bilinguals. Specifically,\nwe investigate bilingual vs. monolingual category boundaries\nin English and Mandarin via a two-alternative forced-choice\n(2AFC) labeling task on six continua that interpolate between\ntwo distinct everyday objects (e.g., plate and bowl). We find\nthat: (1) bilinguals do not maintain two monolingual-like systems\nbut rather exhibit a converged semantic system influenced\nequally by both languages; and (2) this departure from monolinguals\nis nonetheless constrained by the same pressure for\nefficiency that operates in monolinguals. These findings provide\nnew insight into how bilinguals navigate cross-linguistic\nsemantic variation and suggest that despite having to accommodate\nmyriad sociolinguistic factors, a drive for efficiency is\nalso a key factor that shapes bilingual category systems.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psychology; Concepts and categories; Language understanding; Computational Modeling; Cross-linguistic analysis"
                }
            ],
            "section": "Papers with Poster Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4128j529",
            "frozenauthors": [
                {
                    "first_name": "Maya",
                    "middle_name": "",
                    "last_name": "Taliaferro",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Nathaniel",
                    "middle_name": "",
                    "last_name": "Imel",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Esti",
                    "middle_name": "",
                    "last_name": "Blanco-Elorrieta",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Noga",
                    "middle_name": "",
                    "last_name": "Zaslavsky",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49456/galley/37418/download/"
                }
            ]
        },
        {
            "pk": 49184,
            "title": "Blending Boundaries: A Computational Approach to How Bilinguals Reconcile Cross-Linguistic Categorization",
            "subtitle": null,
            "abstract": "We categorize the world using labels that aid memory, recognition, and generalization. While some concepts have clear boundaries, others are more fluid, leading to cross-linguistic differences. How bilinguals manage these differences remains unclear. We investigate this by comparing English monolinguals, Mandarin monolinguals, and Mandarin-English bilinguals in a 2AFC task to test whether bilinguals' categorization aligns with monolingual norms or forms an integrated system. Additionally, we develop a neural network model to simulate category boundary formation under varying language exposure. Our model closely mirrors behavioral data, supporting the idea that bilinguals develop a shared categorization system shaped by dominant language exposure. This combined behavioral and computational approach offers new insights into how bilinguals resolve cross-linguistic conflict and the cognitive mechanisms underlying multilingual concept organization.",
            "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/07t9r6vj",
            "frozenauthors": [
                {
                    "first_name": "Aditi",
                    "middle_name": "",
                    "last_name": "Singh",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Maya",
                    "middle_name": "",
                    "last_name": "Taliaferro",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Grace",
                    "middle_name": "",
                    "last_name": "Lindsay",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Esti",
                    "middle_name": "",
                    "last_name": "Blanco-Elorrieta",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49184/galley/37145/download/"
                },
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49184/galley/38690/download/"
                }
            ]
        },
        {
            "pk": 49344,
            "title": "Blind Speakers' Path Gestures Are More Precise Than Those of Sighted and Blindfolded Speakers",
            "subtitle": null,
            "abstract": "Co-speech gestures arise from an interaction between visuospatial experience and speech formulation. Congenitally blind speakers produce gestures, but less than sighted speakers when describing spatial events. This study explores whether visual experience influences gesture kinematics to better understand the cognitive processes underlying gesture production. We conducted an auditory task where all participants listened to sounds of motion events (e.g., someone walking from a door). We analyzed co-speech path gestures (depicting the trajectory of the motion) spontaneously produced by 20 blind, 21 blindfolded, and 21 sighted Turkish speakers. We compared the alignment of speakers' path gestures with the actual spatial trajectory of the motions, along with other kinematic features—duration, size, and speed. Blind speakers took longer to produce larger gestures than sighted speakers. Blind speakers' gestures also reflected better precision than those of non-blind speakers—aligning with spatial cognition research. Thus, altered spatial cognition shapes gestures during event description.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computer Science; Language Production; Spatial cognition; Gesture analysis"
                }
            ],
            "section": "Abstracts with Oral Presentation",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4r15282x",
            "frozenauthors": [
                {
                    "first_name": "Ezgi",
                    "middle_name": "",
                    "last_name": "Mamus",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Psycholinguistics",
                    "department": ""
                },
                {
                    "first_name": "Mounika",
                    "middle_name": "",
                    "last_name": "Kanakanti",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Psycholinguistics",
                    "department": ""
                },
                {
                    "first_name": "Asli",
                    "middle_name": "",
                    "last_name": "Özyürek",
                    "name_suffix": "",
                    "institution": "Max Planck Institute",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2025-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49344/galley/37305/download/"
                }
            ]
        }
    ]
}