Article List

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        {
            "pk": 27994,
            "title": "Is the blocking effect sensitive to causal model? It depends how you ask",
            "subtitle": null,
            "abstract": "Cue competition effects in human contingency learningappear to be sensitive to the causal nature of cue-outcomerelationships. While blocking effects are reliablydemonstrated in scenarios where cues are presented as causesof outcomes, several studies have failed to find blocking inscenarios where cues are presented as effects of outcomes, afinding that is typically taken as evidence for the involvementof controlled reasoning processes in cue competition. Thesestudies typically measure blocking with continuous causalratings about individual cues. Previous studies have foundthat sensitivity to causal model may depend on how the testquestion is phrased. In contrast, the current study tested thesensitivity of blocking to causal scenarios across differentformats of the same test question. Participants completed acausal learning task with instructions suggesting either apredictive (i.e. cue causes outcome) or diagnostic (cue iscaused by outcome) cue-outcome relationship. Participantswere then asked about the likelihood of outcomes occurringby either giving a continuous rating of each outcome or adiscrete choice about the most likely outcome. Whenmeasured by continuous ratings of individual cues, blockingwas evident in predictive, but not diagnostic scenarios.However, when measured by discrete choice or using acompound negation test, blocking was robust and insensitiveto causal scenario. The results suggest that contributions ofpredictive memory and causal reasoning to cue competitioneffects may depend substantially on the type of measure used.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "causal model; cue competition; blocking; testsensitivity"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0f93761v",
            "frozenauthors": [
                {
                    "first_name": "Hilary",
                    "middle_name": "J",
                    "last_name": "Don",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Evan",
                    "middle_name": "J",
                    "last_name": "Livesey",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27994/galley/17633/download/"
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            ]
        },
        {
            "pk": 28323,
            "title": "Is there a forward bias in human profile portraits?",
            "subtitle": null,
            "abstract": "Humans favor pictorial representations of agents with more space in front of them than behind them. This preference hasbeen evidenced in forced choice (Palmer, Gardner, & Wickens, 2008) and drag and drop tasks (Palmer & Langlois, 2017),and has been referred to as a forward bias in aesthetic preferences for spatial composition. It has also been documentedin depictions of animals and referred to as an anterior bias (Bode et al., 2011). We extend the study of this bias bylooking at the evolution of portrait painting in Europe (where classical rules demanded centering). For this we analyzeprofile-oriented portraits from two datasets: one Pan-European subset of the one used in Redies et al. (2007), and a secondone compiled from the London National Portrait Gallerys online collections. We confirm the bias and discuss links withunderlying mechanisms of animacy and agency perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/03n972x2",
            "frozenauthors": [
                {
                    "first_name": "Helena",
                    "middle_name": "",
                    "last_name": "Miton",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Mikoaj",
                    "middle_name": "",
                    "last_name": "Hernik",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                },
                {
                    "first_name": "Dan",
                    "middle_name": "",
                    "last_name": "Sperber",
                    "name_suffix": "",
                    "institution": "Central European University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28323/galley/18014/download/"
                }
            ]
        },
        {
            "pk": 27723,
            "title": "It's Complicated: Children Identify Relevant Information About Casual Complexity",
            "subtitle": null,
            "abstract": "Mechanistic complexity is an important property that affects\nhow we interact with and learn from artifacts. Previous\nresearch finds that children successfully detect complexity\ncontrasts when given information about the functions of simple\nand complex objects. However, do children spontaneously\nfavor relevant information about an object’s causal\nmechanisms and functions when trying to determine an\nobject’s complexity? In Study 1, 7–9-year-olds and adults, but\nnot 5–6-year-olds, favored relevant information (e.g., the\ndifficulty in fixing an object) over irrelevant information (e.g.,\nthe difficulty in spelling an object’s name) for making\ndeterminations of mechanistic complexity. Only in Study 2, in\nwhich the relevance contrasts were extreme, did the youngest\nage group favor relevant over irrelevant information. These\nresults suggest that the ability to detect which object properties\nimply complexity emerges in the early school years; young\nchildren may be misled by features that are not truly diagnostic\nof mechanistic complexity.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Casual complexity"
                },
                {
                    "word": "Relevance"
                },
                {
                    "word": "intuitive theories"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5g48r43m",
            "frozenauthors": [
                {
                    "first_name": "Richard",
                    "middle_name": "E",
                    "last_name": "Ahl",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Erika",
                    "middle_name": "",
                    "last_name": "DeAngelis",
                    "name_suffix": "",
                    "institution": "Amherst College",
                    "department": ""
                },
                {
                    "first_name": "Auburn",
                    "middle_name": "",
                    "last_name": "Stephenson",
                    "name_suffix": "",
                    "institution": "Boston College",
                    "department": ""
                },
                {
                    "first_name": "Sehrang",
                    "middle_name": "",
                    "last_name": "Joo",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                },
                {
                    "first_name": "Frank",
                    "middle_name": "C",
                    "last_name": "Keil",
                    "name_suffix": "",
                    "institution": "Yale University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
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        },
        {
            "pk": 27878,
            "title": "Joint inferences of speakers' beliefs and referents based on how they speak",
            "subtitle": null,
            "abstract": "For almost two decades, the poor performance observed withthe so-called Director task has been interpreted as evidence oflimited use of Theory of Mind in communication. Here wepropose a probabilistic model of common ground in referentialcommunication that derives three inferences from an utterance:what the speaker is talking about in a visual context, what sheknows about the context, and what referential expressions sheprefers. We tested our model by comparing its inferences withthose made by human participants and found that it closelymirrors their judgments, whereas an alternative modelcompromising the hearer’s expectations of cooperativenessand efficiency reveals a worse fit to the human data. Ratherthan assuming that common ground is fixed in a givenexchange and may or may not constrain reference resolution,we show how common ground can be inferred as part of theprocess of reference assignment.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Common ground"
                },
                {
                    "word": "Computational Modeling"
                },
                {
                    "word": "reference resolution"
                },
                {
                    "word": "Theory of mind"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/40754216",
            "frozenauthors": [
                {
                    "first_name": "Paula",
                    "middle_name": "",
                    "last_name": "Rubio-Fernandez",
                    "name_suffix": "",
                    "institution": "University of Oslo",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27878/galley/17516/download/"
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            ]
        },
        {
            "pk": 35957,
            "title": "Keep It R.E.A.L.!: Relevant, Engaging, and Affirming Literacy for Adolescent English Learners by Mary Amanda Stewart",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Book and Media Review",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6tf9w16j",
            "frozenauthors": [
                {
                    "first_name": "Ying",
                    "middle_name": "",
                    "last_name": "Xiong",
                    "name_suffix": "",
                    "institution": "University of Central Florida",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/catesoljournal/article/35957/galley/26811/download/"
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            ]
        },
        {
            "pk": 28344,
            "title": "Kindergarten Predictors of Mathematics: Quantitative, Working Memory andLinguistic Skills",
            "subtitle": null,
            "abstract": "Which cognitive skills predict childrens math ability? Three types of cognitive predictors were identified in the Pathwaysto Mathematics model (LeFevre et al., 2010; Sowinski et al., 2015): quantitative, working memory, and linguistic skills.In the current research, we evaluated the Pathways to Mathematics model concurrently, in Kindergarten (N = 159 children;87 girls; mean age = 5 years, 10 months), as the first testing point in a larger longitudinal study. Quantitative skills wereassessed using subitizing and both non-symbolic and symbolic number comparison. Working memory skills were assessedusing phonological and visuo-spatial span tasks. Linguistic skills were assessed using receptive vocabulary and phono-logical awareness tasks. Consistent with the model, all three factors (quantitative, working memory, and linguistic skills)accounted for significant unique variance in mathematics performance (betas of .21, .28 & .31, respectively, controllingfor age in months). Jointly the factors accounted for 41% of variance in mathematics performance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1c874026",
            "frozenauthors": [
                {
                    "first_name": "Marcie",
                    "middle_name": "",
                    "last_name": "Penner-Wilger",
                    "name_suffix": "",
                    "institution": "King’s University College",
                    "department": ""
                },
                {
                    "first_name": "Rylan",
                    "middle_name": "J.",
                    "last_name": "Waring",
                    "name_suffix": "",
                    "institution": "University of Guelph",
                    "department": ""
                },
                {
                    "first_name": "Nicole",
                    "middle_name": "",
                    "last_name": "Collins",
                    "name_suffix": "",
                    "institution": "King’s University College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28344/galley/18059/download/"
                }
            ]
        },
        {
            "pk": 27975,
            "title": "L2 Speakers’ Reference Resolution in Processing and Production",
            "subtitle": null,
            "abstract": "This study reports one eye-tracking and one sentencecompletion study investigating the antecedent biases ofTurkish-speaking L2 speakers of English, for anaphor it anddeixis this. Our results show L2 speakers displayed native-like sensitivity to the type of antecedents while using it andthis in sentence completion, but this sensitivity was notreplicated in our online reading experiment. This showslimitations in L2 speakers’ use of information in onlinereading, and poor performance in making use of pragmaticchanges in context to track the antecedents of it and this.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "anaphora; demonstratives; processing; reading;non-native"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4cf0h94m",
            "frozenauthors": [
                {
                    "first_name": "Derya",
                    "middle_name": "",
                    "last_name": "Cokal",
                    "name_suffix": "",
                    "institution": "Newcastle University",
                    "department": ""
                },
                {
                    "first_name": "Patrick",
                    "middle_name": "",
                    "last_name": "Sturt",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Fernanda",
                    "middle_name": "",
                    "last_name": "Ferriera",
                    "name_suffix": "",
                    "institution": "UC Davis",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27975/galley/17613/download/"
                }
            ]
        },
        {
            "pk": 28033,
            "title": "Labeling Common and Uncommon Fractions Across Notation and Education",
            "subtitle": null,
            "abstract": "A surge of recent research on fraction representation hasprovided substantial insight into how people think aboutproportional information in written, symbolic form and invisual, non-symbolic form. However, how fractions anddecimals are verbally labeled is an often-overlooked aspect ofproportion representation. In the current study, weinvestigated how adults label fractions and decimals (Study 1)and how children in a range of grades label fractions (Study2), using a novel web-based platform for accessing studentdata from real classrooms (ASSISTments). In both studies,children and adults showed remarkable consistency in thekinds of labels they used. However, there were somedifferences in label preferences across notation and grade-level. Although the relations between fraction labeling andfraction ability remain unclear, these studies provide a firstlook at the kinds of labels that people typically use andprovide some initial hypotheses for future research intosymbolic representations of proportion.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "fractions; decimals; labels; ASSISTments"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3vn6k6ng",
            "frozenauthors": [
                {
                    "first_name": "Michelle",
                    "middle_name": "A",
                    "last_name": "Hurst",
                    "name_suffix": "",
                    "institution": "UChicago",
                    "department": ""
                },
                {
                    "first_name": "Sara",
                    "middle_name": "",
                    "last_name": "Cordes",
                    "name_suffix": "",
                    "institution": "Boston College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28033/galley/17672/download/"
                }
            ]
        },
        {
            "pk": 28355,
            "title": "Language Dynamics in Supreme Court Oral Arguments",
            "subtitle": null,
            "abstract": "During conversations, it is not uncommon to notice that interlocutors start using similar words and grammatical structures.This alignment of language use is thought to help comprehension, as well as lead to an alignment in underlying represen-tations. In the context of negotiations, the degree to which parties exhibit such an alignment can indicate the likelihoodof reaching an agreement. The present study expands this notion to the courts and uses corpus statistics to examine therelationship between the alignment of semantic content during oral arguments and the decision reached by the justices.The analysis demonstrates that lawyers that align their language with that of the justices are more likely to have a decisionin their favor. Additionally, as befits the power dynamic between justices and lawyers, lawyers are more likely to aligntheir language with the justices than the justices are to align their language to that of the lawyers.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5qx3k8xd",
            "frozenauthors": [
                {
                    "first_name": "Eyal",
                    "middle_name": "",
                    "last_name": "Sagi",
                    "name_suffix": "",
                    "institution": "University of St. Francis",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28355/galley/18080/download/"
                }
            ]
        },
        {
            "pk": 27776,
            "title": "Language in Context: Incorporating Demographic Embeddings into Language Understanding",
            "subtitle": null,
            "abstract": "Meaning depends on context. This applies both in obviouscases like deictics or sarcasm as well as more subtle situationslike framing or persuasion. One key characteristic of context isthe identity of the participants in an interaction. Our interpre-tation of an utterance depends on a variety of factors such asour personal history, background knowledge, and our relation-ship to the source. While demographics allow us to capturesome of this variance, the relevance of specific demographicfactors varies across contexts. To address these challenges, weintroduce a method for combining demographics and contextinto situated demographic embeddings—mapping representa-tions onto a continuous space appropriate for the given domain.We further demonstrate how to make use of related externalresources so as to apply this approach in low-resource situa-tions. We show the resulting representations to be interpretableand consider domain-specific similarity. Finally, we show howthese representations can be incorporated to improve modelingof a real-world natural language understanding task.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Demographic representation"
                },
                {
                    "word": "Continuous representations"
                },
                {
                    "word": "Moral reasoning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3v64m0bm",
            "frozenauthors": [
                {
                    "first_name": "Justin",
                    "middle_name": "",
                    "last_name": "Garten",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                },
                {
                    "first_name": "Brendan",
                    "middle_name": "",
                    "last_name": "Kennedy",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                },
                {
                    "first_name": "Joe",
                    "middle_name": "",
                    "last_name": "Hoover",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                },
                {
                    "first_name": "Kenji",
                    "middle_name": "",
                    "last_name": "Sagae",
                    "name_suffix": "",
                    "institution": "UC Davis",
                    "department": ""
                },
                {
                    "first_name": "Morteza",
                    "middle_name": "",
                    "last_name": "Dehghani",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27776/galley/17416/download/"
                }
            ]
        },
        {
            "pk": 28364,
            "title": "Language production: Shaped by phonological interference and motorinterference",
            "subtitle": null,
            "abstract": "Speakers are known to insert optional words when upcoming material is difficult. In three studies, we investigated howphonological interference and motor planning difficulty affect production choices. First, analyses of the spoken COCAcorpus (¿100m words) showed lower use of [optional-that] in relative clauses following a that determiner (that boy [that]we saw) than following other determiners (this boy [that] we saw). Second, a sentence recall study confirmed numericallylower rates of optional-that use and more recall/production errors in the presence of a homophonous that determinercompared with sentences with other determiners. These two studies suggest phonological interference reduces the planningbenefits of optional-that. Third, in a separate sentence recall study, we demonstrated optional-that use increases withmotor planning difficulty (concurrent finger tapping). Together, these results demonstrate that speakers balance multipleconstraints when planning speech, and that both phonological interference and concurrent tasks affect language productionchoices.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8dc881pp",
            "frozenauthors": [
                {
                    "first_name": "Steven",
                    "middle_name": "",
                    "last_name": "Schwering",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Maryellen",
                    "middle_name": "",
                    "last_name": "MacDonald",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Tom",
                    "middle_name": "",
                    "last_name": "Wasow",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28364/galley/18099/download/"
                }
            ]
        },
        {
            "pk": 28068,
            "title": "Language use shapes cultural norms: Large scale evidence from gender",
            "subtitle": null,
            "abstract": "Cultural norms vary dramatically across social groups. Herewe use large scale data to examine the extent to which languageplays a role in shaping one such norm—the gender norm to as-sociate men with careers and women with family. We measurecross-cultural variability in this gender bias using previously-collected estimates from the Implicit Association Task (IAT; N= 663,709). We then try to predict bias variability by the waythat gender is encoded in language semantics and grammar.We quantify gender bias in semantics using word-embeddingmodels trained on different languages. Our data suggest thatthe linguistic encoding of gender predicts the degree of speak-ers’ gender bias in the IAT, pointing to a causal role for lan-guage in shaping gender norms.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cultural Norms"
                },
                {
                    "word": "IAT"
                },
                {
                    "word": "gender"
                },
                {
                    "word": "LINGUISTIC RELATIVITY"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5v32f76n",
            "frozenauthors": [
                {
                    "first_name": "Molly",
                    "middle_name": "",
                    "last_name": "Lewis",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Gary",
                    "middle_name": "",
                    "last_name": "Lupyan",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28068/galley/17707/download/"
                }
            ]
        },
        {
            "pk": 28184,
            "title": "Lateralized imagery for sentence content: Testing grammar, gender and demonstratives",
            "subtitle": null,
            "abstract": "We investigated imagery by making participants (n=530)draw stick-figure drawings of sentences containing atransitive action (\"She kisses him\"). Previous findings showthat prominent features of meaning and sentence structure areplaced to the left in drawings, according to reading direction.We replicated three findings: the first mentioned element isplaced on the left more often, the agent is placed on the left,and the grammatical subject is placed on the left. We furthertested hypotheses related to deixis and gender. By addingadverbs (here and there), that work as demonstratives inDanish, we tested whether deictic proximity is translated intoa leftward bias. This hypothesis was not supported. Analysesof gender tested the presence of a gender identification and agender stereotype bias, where either own or male gender isgiven prominence and thus placed on the left. We wereunable to support for either of the gender hypotheses.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Imagery; reading direction; grammar; gender;demonstratives"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1jd9j9s5",
            "frozenauthors": [
                {
                    "first_name": "Mikkel",
                    "middle_name": "",
                    "last_name": "Wallentin",
                    "name_suffix": "",
                    "institution": "Aarhus University",
                    "department": ""
                },
                {
                    "first_name": "Roberta",
                    "middle_name": "",
                    "last_name": "Rocca",
                    "name_suffix": "",
                    "institution": "Aarhus University",
                    "department": ""
                },
                {
                    "first_name": "Sofia",
                    "middle_name": "",
                    "last_name": "Stroustrup",
                    "name_suffix": "",
                    "institution": "Aarhus University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28184/galley/17843/download/"
                }
            ]
        },
        {
            "pk": 28128,
            "title": "Lay Understanding of Illness Probability Distributions",
            "subtitle": null,
            "abstract": "Our central question is: how accurate are laypeople’sstatistical intuitions about probability distributions within thedomain of health? Specifically, can participants produceentire probability distributions for the duration of illnesses?While a large body of decision making research has suggestedthat people use a flawed process to arrive at decisions, weposit that participants may be using an optimal process, butwith flawed information. To this end, we assess accuracy interms of both the mean and form of distributions for bothacute illnesses for which people might have experience, andchronic conditions for which people are less likely to haveexperience. We find that participants can accurately estimatethe mean and form of distributions for acute illnesses.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision-making; Probability; Health; Cognition"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7fn8k0nv",
            "frozenauthors": [
                {
                    "first_name": "Talia",
                    "middle_name": "",
                    "last_name": "Robbins",
                    "name_suffix": "",
                    "institution": "Rutgers",
                    "department": ""
                },
                {
                    "first_name": "Pernille",
                    "middle_name": "",
                    "last_name": "Hemmer",
                    "name_suffix": "",
                    "institution": "Rutgers",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28128/galley/17787/download/"
                }
            ]
        },
        {
            "pk": 28265,
            "title": "Leader-follower Dynamics, Agency, and Anxiety in Joint Action Braking: AFirst-Order Dynamical Systems Model",
            "subtitle": null,
            "abstract": "Joint actions require successful coordination between two or more individuals toward shared goals. Successful motorperformance can be influenced by agency and anxiety; however, these factors could also serve as regulation mechanismsthat enhance coordination in joint action tasks. The current experiment assessed the influence of anxiety and sense ofagency on the dynamics of action coordination between two people during a car-braking task. Both individuals wererequired to contribute toward the braking task to avoid crashing into a stop sign. Using an actor partner interdependencemodel (APIM), results suggested that individuals seated to the right decreased their contribution to braking after individualsseated on the left increased their braking, but the reciprocal relation was not present. Visual feedback appears to influenceaction coordination, however no differences in reported anxiety or agency were found. This leader-follower effect suggeststhat a driver-passenger dynamic might have emerged.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5rr3w6v1",
            "frozenauthors": [
                {
                    "first_name": "Devin",
                    "middle_name": "",
                    "last_name": "Gill",
                    "name_suffix": "",
                    "institution": "University of Utah, Salt Lake City",
                    "department": ""
                },
                {
                    "first_name": "Ian",
                    "middle_name": "",
                    "last_name": "Ruginski",
                    "name_suffix": "",
                    "institution": "University of Utah, Salt Lake City",
                    "department": ""
                },
                {
                    "first_name": "Brandon",
                    "middle_name": "J",
                    "last_name": "Thomas",
                    "name_suffix": "",
                    "institution": "University of Utah, Salt Lake City",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28265/galley/17924/download/"
                }
            ]
        },
        {
            "pk": 27751,
            "title": "Learning about Cyber Deception through Simulations: Predictions of Human Decision Making with Deceptive Signals in Stackelberg Security Games",
            "subtitle": null,
            "abstract": "To improve cyber defense, researchers have developed\nalgorithms to allocate limited defense resources optimally.\nThrough signaling theory, we have learned that it is possible to\ntrick the human mind when using deceptive signals. The\npresent work is an initial step towards developing a\npsychological theory of cyber deception. We use simulations\nto investigate how humans might make decisions under various\nconditions of deceptive signals in cyber-attack scenarios. We\ncreated an Instance-Based Learning (IBL) model of the\nattacker decisions using the ACT-R cognitive architecture. We\nran simulations against the optimal deceptive signaling\nalgorithm and against four alternative deceptive signal\nschemes. Our results show that the optimal deceptive algorithm\nis more effective at reducing the probability of attack and\nprotecting assets compared to other signaling conditions, but it\nis not perfect. These results shed some light on the expected\neffectiveness of deceptive signals for defense. The implications\nof these findings are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cyber deception"
                },
                {
                    "word": "Cognitive Models"
                },
                {
                    "word": "Instance-based learning"
                },
                {
                    "word": "Stackelberg security games"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8pb7r5hw",
            "frozenauthors": [
                {
                    "first_name": "Edward",
                    "middle_name": "A",
                    "last_name": "Cranford",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                },
                {
                    "first_name": "Cleotilde",
                    "middle_name": "",
                    "last_name": "Gonzalez",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                },
                {
                    "first_name": "Sarah",
                    "middle_name": "",
                    "last_name": "Cooney",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Milind",
                    "middle_name": "",
                    "last_name": "Tambe",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27751/galley/17391/download/"
                }
            ]
        },
        {
            "pk": 28166,
            "title": "Learning a face space for experiments on human identity",
            "subtitle": null,
            "abstract": "Generative models of human identity and appearance havebroad applicability to behavioral science and technology, butthe exquisite sensitivity of human face perception means thattheir utility hinges on the alignment of the model’s representa-tion to human psychological representations and the photoreal-ism of the generated images. Meeting these requirements is anexacting task, and existing models of human identity and ap-pearance are often unworkably abstract, artificial, uncanny, orbiased. Here, we use a variational autoencoder with an autore-gressive decoder to learn a face space from a uniquely diversedataset of portraits that control much of the variation irrele-vant to human identity and appearance. Our method generatesphotorealistic portraits of fictive identities with a smooth, navi-gable latent space. We validate our model’s alignment with hu-man sensitivities by introducing a psychophysical Turing testfor images, which humans mostly fail. Lastly, we demonstratean initial application of our model to the problem of fast searchin mental space to obtain detailed “police sketches” in a smallnumber of trials.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "face recognition"
                },
                {
                    "word": "machine learning"
                },
                {
                    "word": "generativemodels"
                },
                {
                    "word": "images"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0q56n0bh",
            "frozenauthors": [
                {
                    "first_name": "Jordan",
                    "middle_name": "W",
                    "last_name": "Suchow",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "C",
                    "last_name": "Peterson",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28166/galley/17825/download/"
                }
            ]
        },
        {
            "pk": 27687,
            "title": "Learning as Program Induction",
            "subtitle": null,
            "abstract": "research could yield benefits to both from cross-pollination",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Program induction; Hypothesis generation; discovery; concept learning; Generalization; Problem solving"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5cn4j0n6",
            "frozenauthors": [
                {
                    "first_name": "Niel",
                    "middle_name": "R",
                    "last_name": "Bramley",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Fei",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California, Berkley",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "B",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "Massachusetts Institure of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27687/galley/17328/download/"
                }
            ]
        },
        {
            "pk": 28050,
            "title": "Learning distributions as they come: Particle filter models for onlinedistributional learning of phonetic categories",
            "subtitle": null,
            "abstract": "Human infants have the remarkable ability to learn any hu-man language. One proposed mechanism for this ability isdistributional learning, where learners infer the underlyingcluster structure from unlabeled input. Computational mod-els of distributional learning have historically been principledbut psychologically-implausible computational-level models,or ad hoc but psychologically plausible algorithmic-level mod-els. Approximate rational models like particle filters can po-tentially bridge this divide, and allow principled, but psycho-logically plausible models of distributional learning to be spec-ified and evaluated. As a proof of concept, I evaluate one suchparticle filter model, applied to learning English voicing cate-gories from distributions of voice-onset times (VOTs). I findthat this model learns well, but behaves somewhat differentlyfrom the standard, unconstrained Gibbs sampler implementa-tion of the underlying rational model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computational modeling; Rational models; Parti-cle filters; Language learning; Distributional learning; Speechperception"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7k03p783",
            "frozenauthors": [
                {
                    "first_name": "Dave",
                    "middle_name": "F",
                    "last_name": "Kleinschmidt",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28050/galley/17689/download/"
                }
            ]
        },
        {
            "pk": 28113,
            "title": "Learning from uncertainty: exploring and manipulating the role of uncertainty on expression production and interpretation",
            "subtitle": null,
            "abstract": "Linguistic devices that mark confidence (uncertainty) havebeen well documented (e.g., choice of modals, hedges, etc),yet there has been surprisingly little empirical work thatexplicitly measures how uncertainty is signaled andinterpreted. We present an initial report on a project designedto investigate how interlocutors communicate uncertainty anduse that information in acquiring new information andintegrating interlocutor based input with their prior beliefs.Experiment 1 establishes that speakers and listeners agree onthe relative degree of uncertainty for a set of phrases.Experiment 2 manipulated how likely it was that a participantwould recognize an object using images that varied inrecoverability, finding that recoverability mapped ontocertainty. Experiment 3 used a word-learning paradigm toestablish that learners take into account the certainty withwhich a speaker labels uses a novel word to label a novelshape.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "language; communication; learning; uncertainty;pragmatics"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3jf8j0pg",
            "frozenauthors": [
                {
                    "first_name": "Amanda",
                    "middle_name": "",
                    "last_name": "Pogue",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "K",
                    "last_name": "Tanenhaus",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28113/galley/17773/download/"
                }
            ]
        },
        {
            "pk": 28106,
            "title": "Learning Hierarchical Visual Representations in Deep Neural NetworksUsing Hierarchical Linguistic Labels",
            "subtitle": null,
            "abstract": "Modern convolutional neural networks (CNNs) are able toachieve human-level object classification accuracy on specifictasks, and currently outperform competing models in explain-ing complex human visual representations. However, the cate-gorization problem is posed differently for these networks thanfor humans: the accuracy of these networks is evaluated bytheir ability to identify single labels assigned to each image.These labels often cut arbitrarily across natural psychologi-cal taxonomies (e.g., dogs are separated into breeds, but neverjointly categorized as “dogs”), and bias the resulting represen-tations. By contrast, it is common for children to hear bothdog and Dalmatian to describe the same stimulus, helping togroup perceptually disparate objects (e.g., breeds) into a com-mon mental class. In this work, we train CNN classifiers withmultiple labels for each image that correspond to different lev-els of abstraction, and use this framework to reproduce classicpatterns that appear in human generalization behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/60d5x5sf",
            "frozenauthors": [
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Peterson",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Soulos",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Aida",
                    "middle_name": "",
                    "last_name": "Nematzadeh",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L",
                    "last_name": "Grifitsh",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28106/galley/17759/download/"
                }
            ]
        },
        {
            "pk": 27998,
            "title": "Learning Inductive Biases with Simple Neural Networks",
            "subtitle": null,
            "abstract": "People use rich prior knowledge about the world in order toefficiently learn new concepts. These priors–also known as“inductive biases”–pertain to the space of internal models con-sidered by a learner, and they help the learner make inferencesthat go beyond the observed data. A recent study found thatdeep neural networks optimized for object recognition developthe shape bias (Ritter et al., 2017), an inductive bias possessedby children that plays an important role in early word learning.However, these networks use unrealistically large quantities oftraining data, and the conditions required for these biases to de-velop are not well understood. Moreover, it is unclear how thelearning dynamics of these networks relate to developmentalprocesses in childhood. We investigate the development andinfluence of the shape bias in neural networks using controlleddatasets of abstract patterns and synthetic images, allowing usto systematically vary the quantity and form of the experienceprovided to the learning algorithms. We find that simple neuralnetworks develop a shape bias after seeing as few as 3 exam-ples of 4 object categories. The development of these biasespredicts the onset of vocabulary acceleration in our networks,consistent with the developmental process in children.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "neural networks; inductive biases; learning-to-learn; word learning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4h95f0r8",
            "frozenauthors": [
                {
                    "first_name": "Reuben",
                    "middle_name": "",
                    "last_name": "Feinman",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "M",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "NYU",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27998/galley/17637/download/"
                }
            ]
        },
        {
            "pk": 28132,
            "title": "Learning list concepts through program induction",
            "subtitle": null,
            "abstract": "Humans master complex systems of interrelated concepts likemathematics and natural language. Previous work suggestslearning these systems relies on iteratively and directly re-vising a language-like conceptual representation. We intro-duce and assess a novel concept learning paradigm calledMartha’s Magical Machines that captures complex relation-ships between concepts. We model human concept learning inthis paradigm as a search in the space of term rewriting sys-tems, previously developed as an abstract model of compu-tation. Our model accurately predicts that participants learnsome transformations more easily than others and that theylearn harder concepts more easily using a bootstrapping cur-riculum focused on their compositional parts. Our results sug-gest that term rewriting systems may be a useful model of hu-man conceptual representations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Concept learning; Program Induction; Induction;Function learning; Curriculum learning; Bootstrap learning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/51s4q6f5",
            "frozenauthors": [
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Rule",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "Harvard",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "T",
                    "last_name": "Piantadosi",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "B",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "MIT",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28132/galley/17791/download/"
                }
            ]
        },
        {
            "pk": 28348,
            "title": "Learning the goal-structure of actions in a connectionist network without inverseplanning",
            "subtitle": null,
            "abstract": "Bayesian inverse planning models have had considerable success in accounting for how humans understand others’ goal-directed behavior. To date, however, this approach has relied on a pre-specified distribution of possible goals, and it isnot clear where knowledge of this goal space comes from. We present an alternative, connectionist model for whichpossible goals are not specified a priori; instead, action predictions is derived from statistical regularities across pastvisual experiences. The model was evaluated by comparing its prediction performance to mouse-tracking data fromhuman subjects in a novel trajectory prediction task. Like humans, the model showed an initial bias for efficient motion,but rapidly adjusted its predictions based on observed trajectories. This pattern of adjustment indicated sensitivity tocontinuously varying ”sub-goals” that were not explicitly provided to the model and could not be attributed to participantsa priori.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0pz4g2wm",
            "frozenauthors": [
                {
                    "first_name": "Robert",
                    "middle_name": "",
                    "last_name": "Powers",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Plaut",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28348/galley/18067/download/"
                }
            ]
        },
        {
            "pk": 27754,
            "title": "Learning to act by integrating mental simulations and physical experiments",
            "subtitle": null,
            "abstract": "People can learn about the effects of their actions either by\nperforming physical experiments or by running mental sim-\nulations. Physical experiments are reliable but risky; mental\nsimulations are unreliable but safe. We investigate how peo-\nple negotiate the balance between these strategies. Participants\nattempted to shoot a ball at a target, and could pay to take\npractice shots (physical experiments). They could also simply\nthink (run mental simulations), but were incentivized to act\nquickly by paying for time. We demonstrate that the amount\nof thinking time and physical experiments is sensitive to trial\ncharacteristics in a way that is consistent with a model that\nintegrates information across simulation and experimentation\nand decides online when to perform each.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "mental simulation"
                },
                {
                    "word": "Intuitive physics"
                },
                {
                    "word": "Sampling"
                },
                {
                    "word": "Metareasoning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/42c7q898",
            "frozenauthors": [
                {
                    "first_name": "Ishita",
                    "middle_name": "",
                    "last_name": "Dasgupta",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "A",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "B",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Samual",
                    "middle_name": "J",
                    "last_name": "Gershman",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27754/galley/17394/download/"
                }
            ]
        },
        {
            "pk": 27703,
            "title": "Learning-to-Learn from Novice to Expertise: New Challenges and Approaches for One of the Oldest Topics of Cognitive Science",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/50b3d647",
            "frozenauthors": [
                {
                    "first_name": "Ray",
                    "middle_name": "",
                    "last_name": "Perez",
                    "name_suffix": "",
                    "institution": "Office of Naval Research",
                    "department": ""
                },
                {
                    "first_name": "Wayne",
                    "middle_name": "D",
                    "last_name": "Gray",
                    "name_suffix": "",
                    "institution": "Rensselaer Polytechnic Institute",
                    "department": ""
                },
                {
                    "first_name": "Jacquelyn",
                    "middle_name": "",
                    "last_name": "Berry",
                    "name_suffix": "",
                    "institution": "Rensselaer Polytechnic Institute",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Posner",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                },
                {
                    "first_name": "Sophia",
                    "middle_name": "",
                    "last_name": "Vinogradov",
                    "name_suffix": "",
                    "institution": "University of Minnesota",
                    "department": ""
                },
                {
                    "first_name": "Michelene",
                    "middle_name": "T.H.",
                    "last_name": "Chi",
                    "name_suffix": "",
                    "institution": "Arizona State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27703/galley/17344/download/"
                }
            ]
        },
        {
            "pk": 28244,
            "title": "Learning to read with a machine teacher: Discovering efficient procedures for training the orth-to-phon relationships in English",
            "subtitle": null,
            "abstract": "Neural network models of reading provide a good account of many aspects of normal and disordered performance, butthe training procedures are unrealistically comprehensive. Unlike models, child learners have limited instructional timeand are explicitly taught only a small subset of the words they will regularly encounter. To address this discrepancy weinvestigated alternative learning procedures in a standard orthography-to-phonology multilayer network, to identify oneswhich involve a small, teachable subset of words that facilitate learning untrained words with less effort. We also asked,for any such set, whether the procedure can be improved by optimizing the training sequence. Candidate training setsand sequences were derived using a model-based procedure and from elementary reading curricula. The results indicatetradeoffs between the size and composition of the training set and generalization. These procedures suggest pedagogicalsolutions to the problem of learning more than there is time to teach.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3v26x71c",
            "frozenauthors": [
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "Cox",
                    "name_suffix": "",
                    "institution": "University of Manchester",
                    "department": ""
                },
                {
                    "first_name": "Matthew",
                    "middle_name": "Cooper",
                    "last_name": "Borkenhagen",
                    "name_suffix": "",
                    "institution": "University of Wisconsin - Madison",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Seidenberg",
                    "name_suffix": "",
                    "institution": "University of Wisconsin - Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28244/galley/17903/download/"
                }
            ]
        },
        {
            "pk": 28052,
            "title": "Learning Variability from Experience",
            "subtitle": null,
            "abstract": "Leading theories of risky choice predict that decision makersare sensitive to the variability of payoff distributions. Yet, lit-tle is known about how experience affects perceived variabil-ity. Existing empirical research on risky choice provides onlyinconclusive evidence about this issue because choices are notonly affected by perceived variability but also perceived valueand (unobserved) risk preferences. In re-analyses of experi-mental data and survey data from two nationally representativepanels, we show that perceived variability strongly depends onsample variability. In a new experiment, we also demonstratethat perceived variability systematically depends on samplesize, a result consistent with the predictions of a recent the-oretical paper by the authors (Konovalova & Le Mens, 2017).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Experience"
                },
                {
                    "word": "learning"
                },
                {
                    "word": "Risky Choice"
                },
                {
                    "word": "Sampling"
                },
                {
                    "word": "variability"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7nj606x3",
            "frozenauthors": [
                {
                    "first_name": "Elizaveta",
                    "middle_name": "",
                    "last_name": "Konovalova",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Gael",
                    "middle_name": "",
                    "last_name": "Le Mens",
                    "name_suffix": "",
                    "institution": "Universitat Pompeu Fabra",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28052/galley/17691/download/"
                }
            ]
        },
        {
            "pk": 27988,
            "title": "Learning word meaning with little means:An investigation into the inferential capacity of paradigmatic information",
            "subtitle": null,
            "abstract": "To what extent can the similarity structure of categories beinferred based on paradigmatic vs syntagmatic information?We explore this question in two studies that aim to captureparadigmatic information directly: first by having participantsgenerate near-neighbors to exemplars from 15 basic categories,and second by having them partially rank the most similar ex-emplars. After constructing neighborhood graphs of the itemsin each category, we derived a local measure (based on di-rect neighbors) and a global measure (including indirect pathsas well) of paradigmatic information. Both measures predictindependently-obtained human pairwise similarities for eachcategory, but incorporating indirect information substantiallyimproves this prediction. In a third study, we contrast thesemeasures with syntagmatic information obtained from a vast se-mantic network derived from 3 million judgments. The paradig-matic graphs are better predictors of similarity despite onlyencoding a fraction of these data. Broad implications for wordlearning and meaning are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "similarity; semantic networks; near neighbors;word associations; mental lexicon"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9n5308fq",
            "frozenauthors": [
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "de Deyne",
                    "name_suffix": "",
                    "institution": "University of Melbourne",
                    "department": ""
                },
                {
                    "first_name": "Amy",
                    "middle_name": "",
                    "last_name": "Perfors",
                    "name_suffix": "",
                    "institution": "University of Melbourne",
                    "department": ""
                },
                {
                    "first_name": "Danielle",
                    "middle_name": "J",
                    "last_name": "Navarro",
                    "name_suffix": "",
                    "institution": "UNSW",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27988/galley/17627/download/"
                }
            ]
        },
        {
            "pk": 28055,
            "title": "Levels of Analysis in Computational Social Science",
            "subtitle": null,
            "abstract": "Marr’s levels of analysis constitute one influential approach tothe central program of cognitive science—the multilevel anal-ysis of cognition as information processing. The distinctiveaspects of Marr’s framework are an emphasis on identifyingthe computational problems and constraints faced in cognition,and conceptual machinery to relate cognitive mechanisms tothat computational level of analysis. Although related ideashave been explored in a range of social science disciplines,Marr’s framework, and particularly its notion of the preciseformulation of computational problems and solutions, has yetto be applied widely in social analysis. In the present workwe develop a formulation of Marr’s levels for social systems,provide examples of this approach, and address potential criti-cisms. The consequence is a computational perspective on thesociological school of structural functionalism, and an appara-tus for conducting multiscale analysis of social systems.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Computational social science; Marr’s levels ofanalysis; structural functionalism; analytical sociology; com-putational social theory"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/103299v4",
            "frozenauthors": [
                {
                    "first_name": "Peter",
                    "middle_name": "M",
                    "last_name": "Krafft",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28055/galley/17694/download/"
                }
            ]
        },
        {
            "pk": 28370,
            "title": "Lexical access in the face of degraded speech: The effects of cognitive adaptation",
            "subtitle": null,
            "abstract": "Spoken language unfolds over time. Listeners cope with this by activating multiple lexical candidates which compete forrecognition (McClelland & Elman, 1986). Competition dynamics change with degraded speech (Brouwer & Bradlow,2016; McMurray, Farris-Trimble, & Rigler, 2017; McQueen & Huettig, 2012) but it is unclear whether this reflects thedegraded input, or functional adaptation. In two visual world paradigm experiments, listeners heard different levels ofdegraded (noise-vocoded) speech. Experiment 1 manipulated degradation level in blocks or interleaved across trials.Interleaving led to processing delays beyond that of degradation alone. We also found switch-costs when degradationlevel differed between trials. This suggests differences in lexical dynamics are not solely due to degradation level. Inexperiment 2, a visual cue indicated the degradation level before each trial. This reduced the delay and switch costs,suggesting adaptation before the input. These experiments support a role for central processing in dealing with degradedspeech.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5kv2r0w6",
            "frozenauthors": [
                {
                    "first_name": "Francis",
                    "middle_name": "",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "University of Iowa",
                    "department": ""
                },
                {
                    "first_name": "Bob",
                    "middle_name": "",
                    "last_name": "McMurray",
                    "name_suffix": "",
                    "institution": "University of Iowa",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28370/galley/18110/download/"
                }
            ]
        },
        {
            "pk": 27706,
            "title": "Lexical evolution, cognition, and compution",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "lexicon"
                },
                {
                    "word": "semantic systems"
                },
                {
                    "word": "polyseny"
                },
                {
                    "word": "language evolution"
                },
                {
                    "word": "cognitive modeling"
                },
                {
                    "word": "language phylogeny"
                }
            ],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9tw340fc",
            "frozenauthors": [
                {
                    "first_name": "Yang",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Barbara",
                    "middle_name": "C",
                    "last_name": "Malt",
                    "name_suffix": "",
                    "institution": "Lehigh University",
                    "department": ""
                },
                {
                    "first_name": "Mahesh",
                    "middle_name": "",
                    "last_name": "Srinivasan",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27706/galley/17347/download/"
                }
            ]
        },
        {
            "pk": 28125,
            "title": "Look at THAT: Deixis reveals developmental changes in verbal prediction",
            "subtitle": null,
            "abstract": "The present study evaluated whether listeners can use spatial deixis (e.g., this, that, these, and those) to predict the pluralityand proximity of speakers’ referents. In an eye-tracking task, adults and 5-year-old children viewed scenes while listeningto deictic sentences (e.g., Look at that beautiful baby) and neutral sentences (e.g., Look at the beautiful baby). We foundthat both adults and children used deixis to predict the plurality of the referent (e.g., using this to anticipate a singularreferent). However, only adults used deixis to predict the proximity of the referent to the speaker (e.g., using this toanticipate referents that were proximal to the speaker, and that to identify distal referents). Thus, the present findings revealspecific developmental changes in prediction during language processing. We argue that, beyond determining whetherlisteners predict, determining how listeners predict is crucial to understand prediction’s role in language processing andlearning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6z16h3sj",
            "frozenauthors": [
                {
                    "first_name": "Tracey",
                    "middle_name": "",
                    "last_name": "Reuter",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Casey",
                    "middle_name": "",
                    "last_name": "Lew-Williams",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": []
        },
        {
            "pk": 27726,
            "title": "Look, I can do it! Young children forego opportunities to teach others to demonstrate their own competence",
            "subtitle": null,
            "abstract": "We not only care about what others think of the world, but\nalso about what others think of us. The ability to understand\nwhat others think of one’s competence is especially important\nfor young children, as they are beginning to learn about them-\nselves and form new relationships with others. Here we ask\nwhether young children can use others’ observations of their\nown failures and successes to infer others’ beliefs about the\nself’s competence, and would even forego an opportunity to\nteach new information in order to demonstrate their compe-\ntence. In Exp. 1 (3, 4, & 5-year-olds), when a confederate had\nobserved the child initially fail but eventually succeed at op-\nerating a toy, children chose to teach her a new toy; however,\nwhen the confederate had observed the initial failures but not\nthe final success, more children chose to show the familiar toy\nagain to demonstrate their competence. In Exp. 2 (3- & 4-\nyear-olds), we replicate this finding. Even in preschool years,\nchildren can reason about what others of their own competence\nand strategically decide whether to communicate information\nabout the self or the world; these results are discussed in light\nof prior work on reputation management and Theory of Mind.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Development"
                },
                {
                    "word": "social cognition"
                },
                {
                    "word": "Theory of mind"
                },
                {
                    "word": "the self"
                },
                {
                    "word": "reputation management"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8fk740dh",
            "frozenauthors": [
                {
                    "first_name": "Mika",
                    "middle_name": "",
                    "last_name": "Asaba",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Hyowon",
                    "middle_name": "",
                    "last_name": "Gweon",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27726/galley/17366/download/"
                }
            ]
        },
        {
            "pk": 27689,
            "title": "Massive Online Experiments in Cognitive Science",
            "subtitle": null,
            "abstract": "This full-day workshop focuses on Massive Online\nExperiments (MOEs). MOEs have transformative potential,\nas they effectively allow researchers to run hundreds of\nexperiments simultaneously (cf. Hartshorne & Germine,\n2015; Reinecke & Gajos, 2014). The goal of the workshop\nis to help a broad cross-section of cognitive scientists begin\nto incorporate MOEs into their research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Online experiments"
                },
                {
                    "word": "experimental design"
                },
                {
                    "word": "Methodology"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/54v1w1bv",
            "frozenauthors": [
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Hartshorne",
                    "name_suffix": "",
                    "institution": "Boston College",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "R",
                    "last_name": "de Leeuw",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Germine",
                    "name_suffix": "",
                    "institution": "Harvard Medical School",
                    "department": ""
                },
                {
                    "first_name": "Katharina",
                    "middle_name": "",
                    "last_name": "Reinecke",
                    "name_suffix": "",
                    "institution": "University of Washington",
                    "department": ""
                },
                {
                    "first_name": "Mariela",
                    "middle_name": "",
                    "last_name": "Jennings",
                    "name_suffix": "",
                    "institution": "Boston College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27689/galley/17330/download/"
                }
            ]
        },
        {
            "pk": 28224,
            "title": "MathByExample: Testing the Worked Example Principle in Elementary School Math",
            "subtitle": null,
            "abstract": "An abundance of empirical evidence has amassed supporting the effectiveness of having students explain why correctproblem solutions are correct (Aleven & Koedinger, 2002; Hilbert, Renkl, Kessler, & Reiss, 2008) as well as why incor-rect problem solutions are incorrect (Durkin & Rittle-Johnson, 2012; Grosse & Renkl, 2006). However, despite strongtheoretical background for the approaches (e.g., Sweller, 1999; Siegler, 2002) and the growing amount of empirical ev-idence collected in real-world classrooms for students in middle school and above (e.g., Adams et al., 2014; Booth etal, 2015) it is yet unknown whether prompting self-explanation of correct and incorrect examples could be effectivelytranslated for elementary school mathematics classroom. In this project, we worked with elementary school teachers andmathematics coaches to construct developmentally appropriate worked-example assignments for 4th graders; the presentstudy tests the effectiveness of these collaboratively developed assignments for different topics in ethnically diverse 4thgrade classrooms.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6f80n2zm",
            "frozenauthors": [
                {
                    "first_name": "Julie",
                    "middle_name": "",
                    "last_name": "Booth",
                    "name_suffix": "",
                    "institution": "Temple University",
                    "department": ""
                },
                {
                    "first_name": "Kelly",
                    "middle_name": "",
                    "last_name": "McGinn",
                    "name_suffix": "",
                    "institution": "Temple University",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "K",
                    "last_name": "Young",
                    "name_suffix": "",
                    "institution": "Temple University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28224/galley/17883/download/"
                }
            ]
        },
        {
            "pk": 28198,
            "title": "Measuring Attention Control Abilities with a Gaze Following Antisaccade Paradigm",
            "subtitle": null,
            "abstract": "Social gaze-following consists of both reflexive and volitionalcontrol mechanisms of saccades, similar to those evaluated inthe antisaccade task. This similarity makes gaze-following anideal medium for studying attention in a social context. Thepresent study seeks to utilize reflexive gaze-following to de-velop a social paradigm for measuring attention control. Weevaluate two gaze-following variations of the antisaccade task.In version 1, participants are cued with still images of a socialpartner looking either left or right. In version 2, participantsare cued with videos of a social partner shifting their gaze tothe left or right. As with the traditional antisaccade task, par-ticipants were required to look in the opposite direction of thetarget stimuli (i.e., gaze cues). Performance on the new gaze-following antisaccade tasks are compared to the traditional an-tisaccade task and the highly related ability of working mem-ory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "gaze-following; social cues; attention control; an-tisaccade; working memory"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/97t4k30n",
            "frozenauthors": [
                {
                    "first_name": "Jade",
                    "middle_name": "",
                    "last_name": "Yonehiro",
                    "name_suffix": "",
                    "institution": "Arizona State",
                    "department": ""
                },
                {
                    "first_name": "Nicholas",
                    "middle_name": "D",
                    "last_name": "Duran",
                    "name_suffix": "",
                    "institution": "Arizona State",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28198/galley/17857/download/"
                }
            ]
        },
        {
            "pk": 27909,
            "title": "Measuring Belief Bias with Ternary Response Sets",
            "subtitle": null,
            "abstract": "Belief bias in syllogistic reasoning refers to the finding thatindividuals are more likely to accept believable than unbeliev-able conclusions independent of their logical validity. Mosttheories argue that belief bias is driven by differences in rea-soning processes between believable and unbelievable syllo-gisms. In contrast, Dube, Rotello, and Heit (2010) proposedthat belief bias is solely an effect of response processes. Weinvestigated belief bias without having to rely on response biasmanipulations (Klauer, Musch, and Naumer, 2000) or confi-dence ratings (Dube et al., 2010). Instead, we added a thirdresponse (“I don’t know”) to the usual binary response set(“Yes”/“No”). This allowed us to test belief bias with a fullyidentified multinomial processing tree model, in a hierarchicalBayesian framework. We found evidence that the belief biasis driven by differences in response processes. Evidence for adifference in reasoning processes was inconclusive.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "belief bias; syllogisms; multinomial processing tree models"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/895205x6",
            "frozenauthors": [
                {
                    "first_name": "Samuel",
                    "middle_name": "",
                    "last_name": "Winiger",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "Henrik",
                    "middle_name": "",
                    "last_name": "Singmann",
                    "name_suffix": "",
                    "institution": "University of Zurich",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Kellen",
                    "name_suffix": "",
                    "institution": "Syracuse",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27909/galley/17547/download/"
                }
            ]
        },
        {
            "pk": 28041,
            "title": "Measuring individual differences in cognitive effort avoidance",
            "subtitle": null,
            "abstract": "When given the chance to choose between two tasks, one willmore likely choose the easier, less demanding task. Thiseffect has been shown in various domains and referred to asthe law of minimum effort or demand avoidance. Themeasure of demand avoidance that is currently used is theproportion of low-demand choices. We show that the currentmeasure is not appropriate for accurately assessing individualdifferences in demand avoidance, because the process ofdemand selection is contingent upon the process of demanddetection. Subsequently, we suggest a new measure ofdemand avoidance that combines demand detection anddemand selection. We show that the new measure of demandavoidance correlates in the expected direction (i.e.,negatively) with established measures of willingness andability to carry out cognitively demanding tasks. We proposea novel, performance-based measure of cognitive effortavoidance that can be used to enhance the validity of researchin cognition, perception, and neurosciences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Law of minimum effort; cognitive demanddetection; cognitive demand selection"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4wd242hv",
            "frozenauthors": [
                {
                    "first_name": "Ion",
                    "middle_name": "",
                    "last_name": "Juvina",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Jeff",
                    "middle_name": "",
                    "last_name": "Nador",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Othalia",
                    "middle_name": "",
                    "last_name": "Larue",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Randall",
                    "middle_name": "",
                    "last_name": "Green",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Assaf",
                    "middle_name": "",
                    "last_name": "Harel",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Brandon",
                    "middle_name": "",
                    "last_name": "Minnery",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28041/galley/17680/download/"
                }
            ]
        },
        {
            "pk": 28187,
            "title": "Measuring Individual Differences in Visual and Verbal Thinking Styles",
            "subtitle": null,
            "abstract": "Do people have dispositions towards visual or verbal think-ing styles, i.e., a tendency towards one default representationalmodality versus the other? The problem in trying to answerthis question is that visual/verbal thinking styles are challeng-ing to measure. Subjective, introspective measures are themost common but often show poor reliability and validity; neu-roimaging studies can provide objective evidence but are in-trusive and resource-intensive. In previous work, we observedthat in order for a purely behavioral testing method to be ableto objectively evaluate a person’s visual/verbal thinking style,1) the task must be solvable equally well using either visualor verbal mental representations, and 2) it must offer a sec-ondary behavioral marker, in addition to primary performancemeasures, that indicates which modality is being used. Wecollected four such tasks from the psychology literature andconducted a small pilot study with adult participants to see theextent to which visual/verbal thinking styles can be differenti-ated using an individual’s results on these tasks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive styles; mental representation; process-ing style; representational modality"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2rz169d9",
            "frozenauthors": [
                {
                    "first_name": "Noel",
                    "middle_name": "",
                    "last_name": "Warford",
                    "name_suffix": "",
                    "institution": "Vanderbilt",
                    "department": ""
                },
                {
                    "first_name": "Maithilee",
                    "middle_name": "",
                    "last_name": "Kunda",
                    "name_suffix": "",
                    "institution": "Vanderbilt",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28187/galley/17846/download/"
                }
            ]
        },
        {
            "pk": 28312,
            "title": "Measuring representational similarity across neural networks",
            "subtitle": null,
            "abstract": "Shared structure in neural responses across people can be obscured because these neural responses sit on different ”co-ordinate systems”; hyperalignment can recover this shared structure by placing different people’s brain responses intoa common functional space (Chen et al., 2015; Haxby et al., 2011). Here, we apply this framework to understand thehidden representations of neural networks. Different neural networks can represent the same input-output mapping usingvery different weights. We show that hyperalignment can construct a shared representational space that recovers sharedrepresentation structure across neural networks. We formally connect representational similarity analysis and hyperalign-ment and use simulations to demonstrate the robustness of hyperalignment against several types of transformations thatpreserve the representation geometry of the network. We also empirically tested our method on some supervised learningbenchmarks (CIFAR10, MNIST) for both standard and convolutional networks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5675t040",
            "frozenauthors": [
                {
                    "first_name": "Qihong",
                    "middle_name": "",
                    "last_name": "Lu",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Ramadge",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Kenneth",
                    "middle_name": "",
                    "last_name": "Norman",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Uri",
                    "middle_name": "",
                    "last_name": "Hasson",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28312/galley/17990/download/"
                }
            ]
        },
        {
            "pk": 28218,
            "title": "Measuring strategy adaptivity",
            "subtitle": null,
            "abstract": "Adapting ones strategy involves two steps: assessing and then modifying a strategy in a problem-solving environmentbased on performance. Schunn and Reder demonstrated a positive correlation between working memory and strategyadaptivity measured with the Air Traffic Control Task, though Schunn, Lovett, and Reder found no relationship betweenworking memory and adaptivity measured with the Building Sticks Task (BST). We explored this discrepancy by admin-istering a battery of individual differences measures, including BST adaptivity, fluid intelligence, working memory span,and a new measure of set effects based on the BST, administered to 109 Mississippi State undergraduate participants. FluidIntelligence and BST adaptivity were positively correlated, though the relationship was weak. Our measure of set-effectadaptivity exhibited internal consistency and obvious individual differences, but was uncorrelated with other tasks. Thusstrategy adaptivity may not rely heavily upon working memory and may draw upon distinct cognitive resources, dependingon the underlying task",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/15p936jx",
            "frozenauthors": [
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "Barnes",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Aaron",
                    "middle_name": "",
                    "last_name": "Wong",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Gary",
                    "middle_name": "",
                    "last_name": "Bradshaw",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Jarrod",
                    "middle_name": "",
                    "last_name": "Moss",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28218/galley/17877/download/"
                }
            ]
        },
        {
            "pk": 28246,
            "title": "Measuring the vigor of trolley problem lever pulling",
            "subtitle": null,
            "abstract": "Previous research has shown that most people find it morally acceptable to pull a switch-track lever that will sacrificeone life in order to save five lives. People, however, judge as less morally acceptable the decision to save five lives bypulling a lever that will open a trap-door to sacrifice an individual standing on it (Greene et al., 2009). We measuredthe force participants exert pulling a lever when considering the switch-track and trap-door trolley problem scenarios.We counterbalanced the presentation order of scenarios and only analyzed the movement force of participants who haddecided to pull the lever in both scenarios. We observed in our preliminary results (n=29) more vigorous lever pullingduring the more morally acceptable switch-track scenario relative to the less morally acceptable trap-door scenario.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/10w943dq",
            "frozenauthors": [
                {
                    "first_name": "Zach",
                    "middle_name": "",
                    "last_name": "Catron",
                    "name_suffix": "",
                    "institution": "Indiana University East",
                    "department": ""
                },
                {
                    "first_name": "Gregory",
                    "middle_name": "",
                    "last_name": "Dam",
                    "name_suffix": "",
                    "institution": "Indiana University East",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28246/galley/17905/download/"
                }
            ]
        },
        {
            "pk": 27970,
            "title": "Mechanistic Knowledge Generalizes Differentially",
            "subtitle": null,
            "abstract": "Abstract: When inferring the extent of others’ knowledgefrom samples of what they know, certain kinds of samplesimply richer content. One candidate kind is knowledge ofcausal mechanism. In the current study, we investigatewhether children and adults think that knowledge aboutmechanism generalizes more broadly than non-mechanisticfactual knowledge. We find an early-emerging assumptionthat mechanistic knowledge about a basic level categoryimplies greater knowledge about a superordinate category,compared to factual knowledge about the same basic levelcategory. Even young children have a sophisticated sense ofhow causal mechanisms generalize across categories, despitepossessing little mechanistic knowledge themselves. Theseintuitions likely support the epistemic inferences we makefrom early childhood onward.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "mechanism"
                },
                {
                    "word": "Casual reasoning"
                },
                {
                    "word": "Knowledge"
                },
                {
                    "word": "category learning"
                },
                {
                    "word": "epistemic inference"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3jk3849c",
            "frozenauthors": [
                {
                    "first_name": "Aaron",
                    "middle_name": "",
                    "last_name": "Chuey",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Sheskin",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                },
                {
                    "first_name": "Frank",
                    "middle_name": "",
                    "last_name": "Keil",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27970/galley/17608/download/"
                }
            ]
        },
        {
            "pk": 28347,
            "title": "Memory for Serial Recall explains Center Embedded Structure",
            "subtitle": null,
            "abstract": "A defining characteristic of human language is hierarchical recursion. Recursive loops (i.e. relative clauses) in sentencescan either be embedded in a sentence or cross each other. It is still unknown why center-embedded (CE) recursion isubiquitous among natural languages as in The boy A1 the dog A2 chases B2 falls B1 (A1A2B2B1), whereas crossed-dependent (CD) orderings of recursion hardly ever occur (A1A2B1B2). Our account of the preponderance of CE is basedon retrieval mechanisms, especially mechanisms of serial recall. It explains that, under conditions that are characteristicfor sentence comprehension, backward retrieval (retrieving dog(A2) first, and boy(A1) next, as required by CE) optimizesmemory performance as compared to forward retrieval (boy( A1) first, and dog (A2) next, as required by CD). We test thisaccount with independent serial recall data. Our analysis suggests that CE is better molded to human memory for serialrecall than CD.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7bc6p0q7",
            "frozenauthors": [
                {
                    "first_name": "Fenna",
                    "middle_name": "",
                    "last_name": "Poletiek",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28347/galley/18066/download/"
                }
            ]
        },
        {
            "pk": 27770,
            "title": "Metaphor Framing in Multiple Communication Modalities",
            "subtitle": null,
            "abstract": "Metaphors can shape how people reason about complex issues,but most studies of metaphor framing rely exclusively onwritten materials. This is a significant limitation, as peopleregularly encounter linguistic metaphors in a variety ofdifferent communicative settings (e.g., read in the newspaper,heard on the radio, or viewed on television). Because researchfinds that variations in communication modality can influencemessage comprehension, retention, and persuasiveness, weexplored the relative power of metaphor framing in differentcommunication modalities. Across two experiments,participants read, heard, or watched a person describe fourdifferent metaphorically framed issues. They had to answer atarget question about each issue by selecting from two responseoptions, one of which was congruent with the metaphor frame.Results revealed a significant, similarly-sized effect ofmetaphor framing in every communication modality,suggesting that communication modality does not moderate theefficacy of metaphor framing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Metaphor framing"
                },
                {
                    "word": "Reasoning"
                },
                {
                    "word": "Persuasion"
                },
                {
                    "word": "Communication Modality"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/35t418v3",
            "frozenauthors": [
                {
                    "first_name": "Stephen",
                    "middle_name": "J",
                    "last_name": "Flusberg",
                    "name_suffix": "",
                    "institution": "SUNY Purchase College",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Lauria",
                    "name_suffix": "",
                    "institution": "SUNY purchase College",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "H",
                    "last_name": "Thibodeau",
                    "name_suffix": "",
                    "institution": "Oberlin College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27770/galley/17410/download/"
                }
            ]
        },
        {
            "pk": 28039,
            "title": "Midpoints and Endpoints in Event Percept",
            "subtitle": null,
            "abstract": "Events unfold over time, i.e., they have a beginning and\nendpoint. Previous studies have illustrated the importance of\nendpoints for event perception and memory (Lakusta &\nLandau, 2005, 2012; Papafragou, 2010; Strickland & Keil,\n2011; Zacks & Swallow, 2007). However, this work has not\ncompared endpoints to other potentially salient points in the\ninternal temporal profile of events (e.g., midpoints) and has\nonly discussed events with a self-evident endpoint. In the\npresent study, we explored sensitivity to event endpoints and\nmidpoints in events of different types. Our results show that\npeople are more disturbed by interruptions at the end\ncompared to interruptions in the middle of an event – but\nonly when perceiving a bounded event (i.e., an event with an\ninherent endpoint). This finding reveals complex tracking of\nthe abstract internal temporal structure of events during\nevent perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "endpoint"
                },
                {
                    "word": "boundedness"
                },
                {
                    "word": "event percep"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2jr4839f",
            "frozenauthors": [
                {
                    "first_name": "Yue",
                    "middle_name": "",
                    "last_name": "Ji",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                },
                {
                    "first_name": "Anna",
                    "middle_name": "",
                    "last_name": "Papafragou",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28039/galley/17678/download/"
                }
            ]
        },
        {
            "pk": 28260,
            "title": "Mind wandering during conversations affects subjective but not objective outcomes",
            "subtitle": null,
            "abstract": "How much do we mind wander during conversations, and how does that affect objective outcomes and subjective per-ceptions of the conversation? We studied computed-mediated dyadic negotiations during which participants (N = 144)discreetly reported whenever they were thinking about something else, and whenever they thought their partner was not at-tending. Participants mind wandered around 19% of the time. Surprisingly, the number of times that a participant thoughtthat their counterpart was not attending correlated almost perfectly with the first participants own number of mind wander-ing reports (r-partial = .941), but very poorly with the other participants number of reports (r-partial = .004) (controlled fortime until agreement). Mind wandering negatively affected subjective (F(1, 57) = 6.48, p = .014) but not objective (F(1,57) = .089, p = .766) outcomes. These findings suggest that mind wandering, and the attribution of mind wandering toothers, leads to worse social psychological outcomes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/99d8d7vj",
            "frozenauthors": [
                {
                    "first_name": "Myrthe",
                    "middle_name": "",
                    "last_name": "Faber",
                    "name_suffix": "",
                    "institution": "Donders Centre for Cognitive Neuroimaging",
                    "department": ""
                },
                {
                    "first_name": "McKenzie",
                    "middle_name": "",
                    "last_name": "Rees",
                    "name_suffix": "",
                    "institution": "Southern Methodist University",
                    "department": ""
                },
                {
                    "first_name": "Sidney",
                    "middle_name": "",
                    "last_name": "D'Mello",
                    "name_suffix": "",
                    "institution": "University of Colorado Boulder",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28260/galley/17919/download/"
                }
            ]
        },
        {
            "pk": 28308,
            "title": "Modeling dynamics of suspense and surprise",
            "subtitle": null,
            "abstract": "Activities such as watching a sports match and reading a novel often provoke suspense and surprise (S&S). Computation-ally, we hypothesize that these feelings derive from the dynamics of our beliefs. In our experiment, participants watch realvideotaped volleyball games or play a card game, where their belief dynamics (e.g. chance of winning) can be affected byboth the stimuli and background information (e.g. game rules and prior beliefs about the teams / the card deck). FollowingEly et al (2015) we formalize instantaneous suspense as a function of expected variance in future belief, and surprise asrelated to the magnitude of belief changes. Through probabilistic model we generate point-by-point predictions of S&S.We find that ratings of S&S for the same games depend on experimentally manipulated in qualitative agreement with ourmodel, but we also identify several situations where the model fails.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/30p2d194",
            "frozenauthors": [
                {
                    "first_name": "Zhiwei",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Neil",
                    "middle_name": "",
                    "last_name": "Bramley",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Todd",
                    "middle_name": "",
                    "last_name": "Gureckis",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28308/galley/17981/download/"
                }
            ]
        },
        {
            "pk": 28176,
            "title": "Modeling garden path effects without explicit hierarchical syntax",
            "subtitle": null,
            "abstract": "The disambiguation of syntactically ambiguous sentences canlead to reading difficulty, often referred to as a garden path ef-fect. The surprisal hypothesis suggests that this difficulty canbe accounted for using word predictability. We tested this hy-pothesis using predictability estimates derived from two fam-ilies of language models: grammar-based models, which ex-plicitly encode the syntax of the language; and recurrent neuralnetwork (RNN) models, which do not. Both classes of mod-els correctly predicted increased difficulty in ambiguous sen-tences compared to controls, suggesting that the syntactic rep-resentations induced by RNNs are sufficient for this purpose.At the same time, surprisal estimates derived from all mod-els systematically underestimated the magnitude of the effect,and failed to predict the difference between easier (NP/S) andharder (NP/Z) ambiguities. This suggests that it may not bepossible to reduce garden path effects to predictability",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "self-paced reading; garden path; neural networks"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7mg5442r",
            "frozenauthors": [
                {
                    "first_name": "Marten",
                    "middle_name": "",
                    "last_name": "van Schijndel",
                    "name_suffix": "",
                    "institution": "John Hopkins",
                    "department": ""
                },
                {
                    "first_name": "Tal",
                    "middle_name": "",
                    "last_name": "Linzen",
                    "name_suffix": "",
                    "institution": "John Hopkins",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28176/galley/17835/download/"
                }
            ]
        },
        {
            "pk": 28089,
            "title": "Modeling Human Inference of Others’ Intentions in Complex Situations with Plan Predictability Bias",
            "subtitle": null,
            "abstract": "A recent approach based on Bayesian inverse planning for the“theory of mind” has shown good performance in modelinghuman cognition. However, perfect inverse planning differsfrom human cognition during one kind of complex tasks dueto human bounded rationality. One example is an environmentin which there are many available plans for achieving a specificgoal. We propose a “plan predictability oriented model” as amodel of inferring other peoples’ goals in complex environ-ments. This model adds the bias that people prefer predictableplans. This bias is calculated with simple plan prediction. Wetested this model with a behavioral experiment in which hu-mans observed the partial path of goal-directed actions. Ourmodel had a higher correlation with human inference. We alsoconfirmed the robustness of our model with complex tasks anddetermined that it can be improved by taking account of indi-vidual differences in “bounded rationality”.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Bayesian Modeling; Theory of Mind; HierarchicalModel; Bounded Rationality."
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/67779372",
            "frozenauthors": [
                {
                    "first_name": "Ryo",
                    "middle_name": "",
                    "last_name": "Nakahashi",
                    "name_suffix": "",
                    "institution": "The graduate University for Advanced Studies",
                    "department": ""
                },
                {
                    "first_name": "Seiji",
                    "middle_name": "",
                    "last_name": "Yamada",
                    "name_suffix": "",
                    "institution": "The graduate University for Advanced Studies",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28089/galley/17728/download/"
                }
            ]
        },
        {
            "pk": 28191,
            "title": "Modeling morphological affixation with interpretable recurrent networks: sequential rebinding controlled by hierarchical attention",
            "subtitle": null,
            "abstract": "This paper proposes a recurrent neural network model thatlearns to perform morphological affixation, a fundamental op-eration of linguistic cognition, and has interpretable relationsto descriptions of morphology at the computational and algo-rithmic levels. The model represents morphological sequences(stems and affixes) with distributed representations that sup-port binding of symbols to ordinal positions and position-basedunbinding. Construction of an affixed form is controlled at theimplementation level by shifting attention between morphemesand across positions within each morpheme. The model suc-cessfully learns patterns of prefixation, suffixation, and infixa-tion, unifying these at all levels of description around the theo-retical notion of a pivot. Connections of the present proposal toneural coding of ordinal position, and to computational modelsof serial recall, are noted.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "morphology; distributed representations; recur-rent networks; neural attention; multi-level descriptions"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3wt1272g",
            "frozenauthors": [
                {
                    "first_name": "Colin",
                    "middle_name": "",
                    "last_name": "Wilson",
                    "name_suffix": "",
                    "institution": "John Hopkins",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28191/galley/17850/download/"
                }
            ]
        },
        {
            "pk": 27790,
            "title": "Modeling reference production using the simultaneity approach: A new look at referential success",
            "subtitle": null,
            "abstract": "When a speaker produces a referring expression, their\noverarching goal is to get the addressee to identify a particular\nobject in the context. This goal leads to the expectation that\nspeakers will use a referring expression tailored to the\nperspective of the addressee. While research in\npsycholinguistics has indeed found that speakers tailor their\nreferring expressions to the addressee’s perspective, they also\nfind egocentric tendencies; namely, a sensitivity to the\nspeaker’s own perspective. Mozuraitis, Stevenson and Heller\n(2018) make the novel proposal that “mixing” perspectives is\na design feature of the production system, modelling data from\nan experiment where knowledge mismatch concerned object\nfunction. Here we further test this model on the more common\nknowledge mismatch of visual perspective, modelling data\nfrom Vanlangendonck, Willems, Menenti and Hagoort (2016).\nThe modelling results shed new light on concept of “referential\nsuccess” that has been assumed to guide reference production.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language Production"
                },
                {
                    "word": "Reference"
                },
                {
                    "word": "Pragmatics"
                },
                {
                    "word": "Audience design"
                },
                {
                    "word": "Computational Modeling"
                },
                {
                    "word": "Common ground"
                },
                {
                    "word": "perspective-taking"
                },
                {
                    "word": "Probabilistic models"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/48m668cr",
            "frozenauthors": [
                {
                    "first_name": "Daphne",
                    "middle_name": "",
                    "last_name": "Heller",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Suzanne",
                    "middle_name": "",
                    "last_name": "Stevenson",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27790/galley/17430/download/"
                }
            ]
        },
        {
            "pk": 27802,
            "title": "Modeling the Dunning-Kruger Effect: A Rational Account of Inaccurate Self-Assessment",
            "subtitle": null,
            "abstract": "Self-assessment, or the evaluation of one’s ability on a task, is\nwidely perceived as a fundamental skill, yet in most studies,\npeople are found to be poorly calibrated to their own abilities.\nSome results seem to show poorer calibration for low perform-\ners than for high performers. This effect has been explained\nin multiple ways: it could indicate worse metacognitive abil-\nity among the low performers (the “Dunning-Kruger” effect),\nor simply regression to the mean. To tease apart these expla-\nnations we develop a Bayesian model of self-assessment and\nevaluate its predictions in two experiments. Our results suggest\nthat poor self-assessment is caused by the influence of prior be-\nliefs and imperfect skill at determining whether a problem was\nsolved correctly or not, and offer only weak support for of a\nrelationship between metacognitive ability and performance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "self-assessment"
                },
                {
                    "word": "Logical reasoning"
                },
                {
                    "word": "metacognition"
                },
                {
                    "word": "Bayesian modeling"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5fh7m0zt",
            "frozenauthors": [
                {
                    "first_name": "Rachel",
                    "middle_name": "A",
                    "last_name": "Jansen",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                },
                {
                    "first_name": "Anna",
                    "middle_name": "N",
                    "last_name": "Rafferty",
                    "name_suffix": "",
                    "institution": "Carleton College",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "UC Berkley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27802/galley/17442/download/"
                }
            ]
        },
        {
            "pk": 27699,
            "title": "Models of Human Scientific Discovery",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "scientific discovery; computational modeling; philosophy of science; reasoning; simulations; cognitive development"
                }
            ],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/44g0x62m",
            "frozenauthors": [
                {
                    "first_name": "Robert",
                    "middle_name": "L",
                    "last_name": "Goldstone",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Allison",
                    "middle_name": "",
                    "last_name": "Gopnik",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Thagard",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Tomer",
                    "middle_name": "D",
                    "last_name": "Ulman",
                    "name_suffix": "",
                    "institution": "Massachusetts Institure of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27699/galley/17340/download/"
                }
            ]
        },
        {
            "pk": 27892,
            "title": "Monotonicity and the Complexity of Reasoning with Quantifiers",
            "subtitle": null,
            "abstract": "We present a natural logic for reasoning with quanti-fiers that can predict human performance in appro-priate reasoning tasks. The model is an extension ofthat in (Geurts, 2003) but allows for better fit withdata on syllogistic reasoning and is extended to ac-count for reasoning with iterated quantifiers. Weassign weights to inference rules and operationalizethe complexity of a reasoning pattern as weightedlength of proof in our logic – this results in a measureof complexity that outperforms other models in theirpredictive capacity and allows for the derivation ofempirically testable hypotheses.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Reasoning"
                },
                {
                    "word": "Quantifiers"
                },
                {
                    "word": "Natural Logic"
                },
                {
                    "word": "psychology"
                },
                {
                    "word": "syllogisms"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1w7871t8",
            "frozenauthors": [
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Sippel",
                    "name_suffix": "",
                    "institution": "U of Amersterdam",
                    "department": ""
                },
                {
                    "first_name": "Jakub",
                    "middle_name": "",
                    "last_name": "Szymanik",
                    "name_suffix": "",
                    "institution": "U of Amersterdam",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27892/galley/17530/download/"
                }
            ]
        },
        {
            "pk": 28372,
            "title": "Moral Dynamics: A Computational Model of Moral Judgment",
            "subtitle": null,
            "abstract": "Previous work on morality has proposed psychophysical and/or qualitative models for moral judgment. While thesemodels capture the data found in their respective studies, we believe they miss the underlying concepts on which peoplebase their moral judgments. Here, we propose a quantitative model of morality grounded in our current understanding ofintuitive theories of physics, psychology, and causality.We detail how peoples intuitions of physics and causality can be used to infer the desire and intent of an agent to bring aboutor prevent harm and how this process can qualitatively predict empirical findings of previous work on moral judgment andquantitatively predict results in new scenarios involving an agent harming or helping another.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/92q0x310",
            "frozenauthors": [
                {
                    "first_name": "Felix",
                    "middle_name": "",
                    "last_name": "Sosa",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Tomer",
                    "middle_name": "",
                    "last_name": "Ullman",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Samuel",
                    "middle_name": "",
                    "last_name": "Gershman",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Josh",
                    "middle_name": "",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Tobias",
                    "middle_name": "",
                    "last_name": "Gerstenberg",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28372/galley/18115/download/"
                }
            ]
        },
        {
            "pk": 28175,
            "title": "More like a bee, less like a spider, and not like a tomato:Ecologically-valid enrichment experiences promote changes in how young childrendifferentiate biological categories",
            "subtitle": null,
            "abstract": "Knowledge about categories supports learning andgeneralization, and this knowledge is particularly importantearly in development. Although most theories of categoryknowledge posit a role for experience in acquiring thisknowledge, the current evidence for the presumed role ofexperience in category knowledge acquisition remains limitedto correlational evidence, indirect measures of categoryknowledge, and computational studies. Here we providedirect evidence that repeated experience with a biologicaldomain in an ecologically-valid setting changed children’scategory representations, with increased differentiation ofitems within that domain and relative to a second domain. Theimplications of these results for understanding the role ofexperience in category acquisition, and the contribution ofenrichment experiences to school readiness are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "categories; differentiation; learning; development"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7xz9r5bz",
            "frozenauthors": [
                {
                    "first_name": "Catarina",
                    "middle_name": "",
                    "last_name": "Vales",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                },
                {
                    "first_name": "Sarah",
                    "middle_name": "L",
                    "last_name": "States",
                    "name_suffix": "",
                    "institution": "Phipps Conservatory and Botanical Gardens",
                    "department": ""
                },
                {
                    "first_name": "Anna",
                    "middle_name": "V",
                    "last_name": "Fisher",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28175/galley/17834/download/"
                }
            ]
        },
        {
            "pk": 27779,
            "title": "More than just new evidence: How category learning fosters belief revision",
            "subtitle": null,
            "abstract": "Causal judgments are stubborn. If people learn about twocorrelated variables B and C, and judge that B causes C, theytypically stick to that judgment even when contradictoryevidence comes to light. One form of contradictory evidenceis that a third variable A causes both B and C, explaining thecorrelation. This paper extends prior work showing thatsimply presenting statistical evidence that A is the commoncause of both B and C does not lead to belief change about B.However, if first subjects learn to categorize phenomena bytheir underlying causal relationships (i.e., as exemplars of acommon cause category), then they can transfer their categoryknowledge to properly interpret the evidence. They recognizethat A is the common cause of B and C and revise their beliefabout B. These results suggest that teaching abstract causalcategories is a promising strategy to help revise false beliefs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "belief revision"
                },
                {
                    "word": "Categories and concepts"
                },
                {
                    "word": "analogy"
                },
                {
                    "word": "Casual learning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2hq1774d",
            "frozenauthors": [
                {
                    "first_name": "Micah",
                    "middle_name": "B",
                    "last_name": "Goldwater",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Monica",
                    "middle_name": "",
                    "last_name": "Bollen",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Josue",
                    "middle_name": "",
                    "last_name": "Giron",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27779/galley/17419/download/"
                }
            ]
        },
        {
            "pk": 28159,
            "title": "Motivated Manipulators? A NLP Analysis of Psychopathic Speech",
            "subtitle": null,
            "abstract": "Psychopaths have long been associated with a unique abilityto manipulate others (Hare, 1999). According to the“bottleneck” hypothesis of psychopathy (Newman & Baskin-Sommers, 2012), psychopaths’ cognitive abilities are directlyrelated to goal-directed behavior. To shed more light onlanguage production in psychopathy, two languageproduction studies were completed contrasting content andfluency under different motivational and difficulty conditions.Individuals high in psychopathy (HP) were less fluent butmaintained a more complex lexicon than their lowpsychopathy (LP) counterparts when under high cognitiveload and low motivation. Yet when HP individuals were underlow cognitive load and high motivation, they were morefluent, but used a less complex lexicon. Furthermore, the HPgroup produced more emotional language in both conditions.The results suggest that HP individuals’ language productionis inherently related to motivation and they attempt to balancefluency and complexity when cognitive load is increased.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Psycholinguistics"
                },
                {
                    "word": "psychopathy"
                },
                {
                    "word": "speechproduction"
                },
                {
                    "word": "NLP"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2610f77n",
            "frozenauthors": [
                {
                    "first_name": "Mikhail",
                    "middle_name": "",
                    "last_name": "Sokolov",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "John",
                    "middle_name": "",
                    "last_name": "Logan",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28159/galley/17818/download/"
                }
            ]
        },
        {
            "pk": 27877,
            "title": "Movement as a message: inferring communicative intent from actions",
            "subtitle": null,
            "abstract": "Humans often communicate through seemingly arbitraryactions, like winks, waves, and nods. While these non-iconicgestures derive their meanings from cultural consensus,people, and especially children, must be able to identify thesemovements as gestures. Here we propose that people expectthat communicative actions will be shaped to reveal that theyhave no external goal. In Experiment 1, we show that peoplejudge inefficient actions as more likely to be communicative.In Experiment 2, we show that these judgments are trulydriven by efficiency, rather than a movement’s visualcomplexity. Finally, in Experiment 3, we show that repetition– which unambiguously reveals that the goal of the action isthe movement itself – has a strong influence on inferencesabout communicativeness, independent of the motion’sefficiency. Our findings show how expectations about non-iconic communicative actions can be folded into a generalgoal inference framework structured around an expectationfor efficiency.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Action understanding"
                },
                {
                    "word": "Gesture"
                },
                {
                    "word": "social cognition"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0p36v9b3",
            "frozenauthors": [
                {
                    "first_name": "Amanda",
                    "middle_name": "",
                    "last_name": "Royka",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                },
                {
                    "first_name": "Rosie",
                    "middle_name": "",
                    "last_name": "Aboody",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "",
                    "last_name": "Jara-Ettinger",
                    "name_suffix": "",
                    "institution": "Yale",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27877/galley/17515/download/"
                }
            ]
        },
        {
            "pk": 28164,
            "title": "Movement Speed Affects Speed Language Comprehension",
            "subtitle": null,
            "abstract": "Comprehending action language recruits the action system.\nTo what extent do action simulations reflect the fine-grained\nparameters of real world action? We investigate whether\naction simulations are sensitive to speed of an action. In two\nexperiments participants completed a motor task where they\nmoved slowly or quickly, followed by a sentence sensibility\ntask. We found an overall action effect for sentences\ndescribing hand actions: moving slowly increased accuracy\n(Exp.1) and reduced response time (Exp. 2). For sentences\ndescribing full-body actions, responses were more accurate\nwhen movement speed matched the speed implied in the\nsentence, in Experiment 1 only. This study demonstrates\nonline action simulation and provides evidence that speed of\naction can be simulated during sentence comprehension.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "embodiment; mental simulation; action; speed"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9528m0h2",
            "frozenauthors": [
                {
                    "first_name": "Laura",
                    "middle_name": "J",
                    "last_name": "Speed",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Wessel",
                    "middle_name": "O",
                    "last_name": "van Dam",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                },
                {
                    "first_name": "Gabriella",
                    "middle_name": "",
                    "last_name": "Vigliocco",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Rutvik",
                    "middle_name": "H",
                    "last_name": "Desai",
                    "name_suffix": "",
                    "institution": "USC",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28164/galley/17823/download/"
                }
            ]
        },
        {
            "pk": 27739,
            "title": "Multifunctionality in embodied agents: Three levels of neural reuse",
            "subtitle": null,
            "abstract": "The brain in conjunction with the body is able to adapt to new\nenvironments and perform multiple behaviors through reuse of\nneural resources and transfer of existing behavioral traits. Al-\nthough mechanisms that underlie this ability are not well un-\nderstood, they are largely attributed to neuromodulation. In\nthis work, we demonstrate that an agent can be multifunctional\nusing the same sensory and motor systems across behaviors,\nin the absence of modulatory mechanisms. Further, we lay out\nthe different levels at which neural reuse can occur through\na dynamical filtering of the brain-body-environment system’s\noperation: structural network, autonomous dynamics, and tran-\nsient dynamics. Notably, transient dynamics reuse could only\nbe explained by studying the brain-body-environment system\nas a whole and not just the brain. The multifunctional agent we\npresent here demonstrates neural reuse at all three levels.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "multifunctionality"
                },
                {
                    "word": "neural reuse"
                },
                {
                    "word": "Neural Networks"
                },
                {
                    "word": "dynamical system theory"
                },
                {
                    "word": "brain-body-environment systems"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2fb1d1fv",
            "frozenauthors": [
                {
                    "first_name": "Madhavun",
                    "middle_name": "",
                    "last_name": "Candadai",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Eduardo",
                    "middle_name": "J",
                    "last_name": "Izquierdo",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27739/galley/17379/download/"
                }
            ]
        },
        {
            "pk": 28190,
            "title": "Multilayer Context Reasoning in a Neurobiologically Inspired Working Memory Model for Cognitive Robots",
            "subtitle": null,
            "abstract": "The brain’s working memory system relies heavily on themesolimbic dopamine system and the delivery of reward sig-nals. The interaction between the prefrontal cortex (PFC) andthe basal ganglia are the main components simulated in work-ing memory models. The Working Memory Toolkit (WMtk) isa framework that allows the incorporation of working memoryinto robotic/artificial systems. The HWMtk is built on top ofWMtk by using holographic reduced representations for con-cept encoding. This allows end users to adopt the frameworkwithout the need to understand details of the algorithms in-volved. While the HWMtk captures human and animal per-formance on some cognitive tasks, tasks with multiple con-text layers are still problematic. We extended the HWMtkframework by adding a multilayer context reasoning work-ing memory system. We tested our system on the AX-CPTtask, 1-2-AX-CPT task and a 2-layer context task that is par-tially observable. Our results show that our model is capableof learning after a reasonable number of trials, thus making itamenable for comparison with human and animal performancedata.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "artificial cognition; cognitive robotics; workingmemory; prefrontal cortex; dopamine; reinforcement learning"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/95c1379g",
            "frozenauthors": [
                {
                    "first_name": "Arthur",
                    "middle_name": "S",
                    "last_name": "Williams",
                    "name_suffix": "",
                    "institution": "Middle Tennessee State University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "L",
                    "last_name": "Phillips",
                    "name_suffix": "",
                    "institution": "Middle Tennessee State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28190/galley/17849/download/"
                }
            ]
        },
        {
            "pk": 27724,
            "title": "Multimodal Surprisal in the N400 and the Index of Cognitive Activity",
            "subtitle": null,
            "abstract": "A word’s predictability or surprisal, as determined by cloze\nprobabilities or language models (e.g. Frank, Otten, Galli, &\nVigliocco, 2015) is related to processing effort, in that less ex-\npected words take more effort to process (e.g. Hale, 2001). A\nwords surprisal, however, may also be influenced by the non-\nlinguistic context, such as visual cues: In the visual world\nparadigm (VWP), for example, anticipatory eye movements\nsuggest that comprehenders exploit the scene to predict what\nwill be mentioned next (Altmann & Kamide, 1999). How vi-\nsual context affects word surprisal and processing effort, how-\never, remains unclear. Here, we present evidence that visually-\ndetermined probabilistic expectations for a spoken target word\npredict graded processing effort for that word, in both pupil-\nlometric (ICA) and ERP (N400) measures. These findings\ndemonstrate that the non-linguistic context can immediately\ninfluence both lexical expectations, and surprisal-based pro-\ncessing effort.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "N400"
                },
                {
                    "word": "Language Processing"
                },
                {
                    "word": "EEG"
                },
                {
                    "word": "Index of cognitive activity"
                },
                {
                    "word": "prediction"
                },
                {
                    "word": "eye-tracking"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5930b5fd",
            "frozenauthors": [
                {
                    "first_name": "Christine",
                    "middle_name": "S",
                    "last_name": "Ankener",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Heiner",
                    "middle_name": "",
                    "last_name": "Dernhaus",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Mathew",
                    "middle_name": "W",
                    "last_name": "Crocker",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Maria",
                    "middle_name": "",
                    "last_name": "Staudte",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27724/galley/17364/download/"
                }
            ]
        },
        {
            "pk": 27984,
            "title": "Multinomial Processing Models for Syllogistic Reasoning: A Comparison",
            "subtitle": null,
            "abstract": "To this day, a great variety of psychological theories of reason-ing exist aimed at explaining the underlying cognitive mecha-nisms. The high number of different theories makes a rigorouscomparison of cognitive theories necessary. The present articleproposes to use Multinomial Processing Trees to compare twoof the most prominent theories of syllogistic reasoning: theMental Models Theory and the Probability Heuristics Model.For this, we reanalyzed data from a meta-analysis on six stud-ies about syllogistic reasoning. We evaluate both models withrespect to their overall fit to the data by means of G2, AIC,BIC, and FIA, and on a parametric level. Our comparison in-dicates that a MMT-variant, though having more parameters, isslightly better on all criteria except of the BIC. Yet, none of thetwo models, realized as MPTs, is clearly superior. We outlinethe impact of the different theoretical principles and discussimplications for modeling syllogistic reasoning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Syllogistic Reasoning; Mental Models Theory;Probability Heuristics Model; Multinomial Processing Trees"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3wt6r6ng",
            "frozenauthors": [
                {
                    "first_name": "Hannah",
                    "middle_name": "",
                    "last_name": "Dames",
                    "name_suffix": "",
                    "institution": "University of Freiburg",
                    "department": ""
                },
                {
                    "first_name": "Jan",
                    "middle_name": "Ole",
                    "last_name": "van Hartz",
                    "name_suffix": "",
                    "institution": "U of Freiburg",
                    "department": ""
                },
                {
                    "first_name": "Mario",
                    "middle_name": "",
                    "last_name": "Kantz",
                    "name_suffix": "",
                    "institution": "U of Freiburg",
                    "department": ""
                },
                {
                    "first_name": "Nicolas",
                    "middle_name": "",
                    "last_name": "Riesterer",
                    "name_suffix": "",
                    "institution": "U of Freiburg",
                    "department": ""
                },
                {
                    "first_name": "Marco",
                    "middle_name": "",
                    "last_name": "Ragni",
                    "name_suffix": "",
                    "institution": "U of Freiburg",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27984/galley/17623/download/"
                }
            ]
        },
        {
            "pk": 27971,
            "title": "Multiple anchors and the MOLE: Benefits for elicitation",
            "subtitle": null,
            "abstract": "Anchoring is a well-known, robust effect causing estimates tobe biased towards previously seen values – regardless of theirrelevance. Reducing anchoring bias is important for optimizingestimation. Herein, we tested the MOLE (More-Or-LessElicitation) tool’s ability to limit the impact of anchors onestimates. In a direct elicitation task, 62 participants’ bestestimates correlated with anchor values at 0.27 whereas, whenusing the MOLE, this relationship disappeared (r = .02).Results also showed, however, that expertise reduces theimpact of anchoring (r = -0.46). We conclude that use of theMOLE assists in avoiding anchoring and that this will be mosthelpful in areas of high uncertainty.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "anchoring; elicitation; accuracy; expertise; decision making; repeated judgment; MOLE"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/102659rh",
            "frozenauthors": [
                {
                    "first_name": "Marianne",
                    "middle_name": "H",
                    "last_name": "Clausen",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Mathew",
                    "middle_name": "B",
                    "last_name": "Welsh",
                    "name_suffix": "",
                    "institution": "U of Adelaide",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27971/galley/17609/download/"
                }
            ]
        },
        {
            "pk": 28021,
            "title": "Multiple heads outsmart one: A computational modelfor distributed decision making",
            "subtitle": null,
            "abstract": "Distributed cognition and decision making has been a topic ofintense research in the recent years. In this paper, a computa-tional model of distributed decision making using a commu-nity of predictive coding agents is developed. The agents areembodied multimodal entities and situated in a shared envi-ronment. They have different visibility of the environment dueto unique sensory and generative models. We show that com-munication between agents helps each of them reach a shareddecision in a way that cannot be reached by brain processes ina single agent. Using a simulated environment, we show thatsensory limitations may lead to incorrect or delayed causal in-ferences giving rise to conflicts in the mind of a predictive cod-ing agent, and communication helps to resolve such conflictsand overcome the limitations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "distributed cognition"
                },
                {
                    "word": "predictive coding"
                },
                {
                    "word": "agent"
                },
                {
                    "word": "Embodiment"
                },
                {
                    "word": "Communication"
                },
                {
                    "word": "Free Energy"
                },
                {
                    "word": "active inference"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6x84v2pv",
            "frozenauthors": [
                {
                    "first_name": "Masoumeh",
                    "middle_name": "Heidari",
                    "last_name": "Kapourchali",
                    "name_suffix": "",
                    "institution": "University of Memphis",
                    "department": ""
                },
                {
                    "first_name": "Bonny",
                    "middle_name": "",
                    "last_name": "Banerjee",
                    "name_suffix": "",
                    "institution": "University of Memphis",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28021/galley/17660/download/"
                }
            ]
        },
        {
            "pk": 28163,
            "title": "Music and Odor in Harmony: A Case of Music-Odor Synaesthesia",
            "subtitle": null,
            "abstract": "We report an individual with music-odor synaesthesia who\nexperiences automatic and vivid odor sensations when she\nhears music. S’s odor associations were recorded on two\ndays, and compared with those of two control participants.\nOverall, S produced longer descriptions, and her associations\nwere of multiple odors at once, in comparison to controls who\ntypically reported a single odor. Although odor associations\nwere qualitatively different between S and controls, ratings of\nthe consistency of their descriptions did not differ. This\ndemonstrates that crossmodal associations between music and\nodor exist in non-synaesthetes too. We also found that S is\nbetter at discriminating between odors than control\nparticipants, and is more likely to experience emotion,\nmemories and evaluations triggered by odors, demonstrating\nthe broader impact of her synaesthesia.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "synaesthesia; odor; music; crossmodal\nassociations"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5jc155vd",
            "frozenauthors": [
                {
                    "first_name": "Laura",
                    "middle_name": "J",
                    "last_name": "Speed",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Asifa",
                    "middle_name": "",
                    "last_name": "Majid",
                    "name_suffix": "",
                    "institution": "Radboud University; Max Planck Institute for Psycholinguistics; Donders Institute for Brain, Cognition, and Bahavior",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28163/galley/17822/download/"
                }
            ]
        },
        {
            "pk": 28274,
            "title": "Music, language, and gesture: Neural oscillations and relational cognition",
            "subtitle": null,
            "abstract": "Music, language, and action involve the ability to combine and flexibly recombine sequences of discrete elements intohierarchical structures. Can structures in one domain influence the other? Does this sequential structure building processrely on shared neural resources or shared types of computation? Initially, we tracked a neural correlate of this sequentialstructure-building process in each domain individually using steady-state evoked potentials (SSEPs). We then exploredthe behavioral effect on sentence comprehension of mismatching linguistic phrase structures with metrical musical ones.We interpret our findings in terms of the Shared Syntactic Integration Resource Hypothesis. We extend the purview ofthis theory beyond harmonic syntax in music to considerations of how the mental organisation of musical elements in time(meter) can be considered syntactic. Our findings suggest fresh parallels between language and music, and how certainprocesses may be shared by more domain-general aspects of our cognitive architecture.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1vw854t9",
            "frozenauthors": [
                {
                    "first_name": "Courtney",
                    "middle_name": "",
                    "last_name": "Hilton",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Micah",
                    "middle_name": "",
                    "last_name": "Goldwater",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Jacobson",
                    "name_suffix": "",
                    "institution": "University of Sydney",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28274/galley/17933/download/"
                }
            ]
        },
        {
            "pk": 35967,
            "title": "Native and Nonnative English-Speaking Teachers’ Expectations of Teacher’s Manuals Accompanying General English and Pronunciation Skills Books",
            "subtitle": null,
            "abstract": "This study explores native and nonnative English-speaking teachers’ expectations of teacher’s manuals accompanying general English skills books and pronunciation teaching books, as well as their impressionistic evaluation of a printed and online teacher’s manual. The study has a mixed-methods design incorporating an online survey and 2 interviews. Findings showed that teachers expected a teacher’s manual to provide additional guidance on which pronunciation features to teach and how to present them effectively. The online teacher’s manual was preferred over the printed one by most of the teachers because of its technological design features. This study suggests that both native and nonnative English-speaking teachers welcome online manuals because of their increased accessibility and practicality. Additionally, greater amounts of guidance can be given in an online teacher’s manual and this guidance can be presented in different modalities, such as in printable text, audio, or video.",
            "language": "eng",
            "license": null,
            "keywords": [
                {
                    "word": "pronunciation teaching"
                },
                {
                    "word": "teacher’s manual"
                },
                {
                    "word": "teachers’ expectations"
                },
                {
                    "word": "native English-speaking teacher (NEST)"
                },
                {
                    "word": "nonnative English-speaking teacher (NNEST)"
                }
            ],
            "section": "Theme Section - Feature Articles",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1cw798hx",
            "frozenauthors": [
                {
                    "first_name": "Sinem",
                    "middle_name": "",
                    "last_name": "Sonsaat",
                    "name_suffix": "",
                    "institution": "Iowa State University, Ames",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/35967/galley/26821/download/"
                }
            ]
        },
        {
            "pk": 28316,
            "title": "Natural Human Exploration under Approach and Avoidance Motivation in aReal-Life Spatial Environment",
            "subtitle": null,
            "abstract": "Open-ended exploration and learning of novel environments is an activity of crucial evolutionary significance. Extantliterature studying these behaviors in human subjects, however, remains sparse. Our study examined spontaneous humanexploration (characterized using video) and subsequent memory of an art exhibit - a complex, real-life environment - asa function of approach vs. avoidance motivation contexts and individual differences. Building on our prior findings thatmotivational context and individual differences may interact to predict memory, but not exploration time, the present workuses computer vision approaches to extract more nuanced measures of exploration from video data, such as path lengthand curvilinearity. Preliminary analysis suggested that locomotor activity may be greater under approach vs. avoidancemotivation, consistent with models linking approach motivation to dopaminergic function and associated motor activity.This and other results are discussed in the larger context of research characterizing exploration, locomotion, and memoryencoding processes in motivated behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7bt1n89q",
            "frozenauthors": [
                {
                    "first_name": "Deeksha",
                    "middle_name": "",
                    "last_name": "Malhotra",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Kimberly",
                    "middle_name": "",
                    "last_name": "Chiew",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Mai-Anh",
                    "middle_name": "",
                    "last_name": "Vu",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Nicole",
                    "middle_name": "",
                    "last_name": "Heller",
                    "name_suffix": "",
                    "institution": "Carnegie Museum of Natural History",
                    "department": ""
                },
                {
                    "first_name": "Guillermo",
                    "middle_name": "",
                    "last_name": "Sapiro",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                },
                {
                    "first_name": "Alison",
                    "middle_name": "",
                    "last_name": "Adcock",
                    "name_suffix": "",
                    "institution": "Duke University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28316/galley/17998/download/"
                }
            ]
        },
        {
            "pk": 28394,
            "title": "Navigating uncertainty through information search",
            "subtitle": null,
            "abstract": "Selecting informative queries is a crucial component of learning and decision-making, where models of information searchhave been widely used to provide normative guidance. Yet a typical requirement of these models is complete informationabout the underlying probabilistic structure of the environment, which is seldom met in real-world situations. Thus,information search models are blind to the epistemic uncertainty that comes with learning through experience, and do notdistinguish between probabilities estimated from a sample of two and a sample of one million. We develop a learningparadigm where a successful strategy needs to balance the exploration of queries with high epistemic uncertainty, with theexploitation of queries already known to be useful. We show that a Bayesian sampling variant of traditional informationsearch models learns faster and performs better, but most surprisingly, that a simple take-the-difference heuristic (TTD)performs competitively using only the absolute difference between observed frequencies.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6j7732td",
            "frozenauthors": [
                {
                    "first_name": "Charley",
                    "middle_name": "M.",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Bjoern",
                    "middle_name": "",
                    "last_name": "Meder",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "D.",
                    "last_name": "Nelson",
                    "name_suffix": "",
                    "institution": "University of Surrey",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28394/galley/18160/download/"
                }
            ]
        },
        {
            "pk": 28112,
            "title": "Neural Coupling Between Infants and Adults Supports Successful Communication",
            "subtitle": null,
            "abstract": "Infancy is the foundational period for learning from adults, and the dynamics of the social environment have long beenproposed as central to childrens development. Here we reveal a novel, naturalistic approach for studying live interactionsbetween infants and adults. Using functional near-infrared spectroscopy (fNIRS), we simultaneously and continuouslymeasured the brains of infants (9-15 months) and an adult while they communicated and played with each other in realtime. We found that time-locked neural synchrony within dyads was significantly greater when they interacted witheach other than with control individuals. In addition, we found that both infant and adult brains continuously trackedthe moment-to-moment fluctuations of mutual gaze and infant emotion with high temporal precision. This investigationmarks a new means of understanding how the brains and behaviors of infants both shape and reflect those of their caregiversduring real-life communication.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0k6109w8",
            "frozenauthors": [
                {
                    "first_name": "Elise",
                    "middle_name": "",
                    "last_name": "Piazza",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Liat",
                    "middle_name": "",
                    "last_name": "Hasenfratz",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Uri",
                    "middle_name": "",
                    "last_name": "Hasson",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Casey",
                    "middle_name": "",
                    "last_name": "Lew-Williams",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28112/galley/17772/download/"
                }
            ]
        },
        {
            "pk": 27906,
            "title": "Neural measures of sensitivity to a culturally evolved space-time language: shared biases and conventionalization",
            "subtitle": null,
            "abstract": "When asked to convey temporal concepts such as ‘yesterday’and ‘tomorrow’ via movements of a dot on a vertical bar,American undergraduates utilize analogical mappingsbetween spatial and temporal concepts. Previous work hasrevealed two different strategies, hypothesized to requirediffering amounts of artificial language exposure to learn.Different pairs of participants, when interacting about thesetime concepts, all settled on the same association betweenspatial magnitude and temporal duration, with largermovements used to convey temporal intervals of greaterduration. However, the association between particular spatiallocations and temporal concepts such as ‘past’ and ‘future’,elicited much more arbitrary solutions, where the mappingsdiffered across pairs of participants. These findings suggestedthat the duration mapping might be driven by mostly shared,initial cognitive biases, while contrasting mappings forpast/future result more clearly from extensive linguisticinteraction. Here we tested whether the brain respondsdifferently to duration mappings as compared to directionmappings by recording participants’ EEG as they learn amini-language that includes both kinds. ERPs time locked toEnglish words elicited larger amplitude N400 and P600 whenthey did not match the preceding signal than when they didmatch. The P600 results were larger and more robust for theduration than the direction stimuli, suggesting participantswere more sensitive to violations of the duration mappingscheme. These data support our hypothesis that people have acognitive bias for the duration mappings that supports theirearly emergence in the development of a semiotic system.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "analogy; artificial language learning; iterated learning; language comprehension; language evolution; metaphor; N400; P600"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8ck4z1dk",
            "frozenauthors": [
                {
                    "first_name": "Tessa",
                    "middle_name": "",
                    "last_name": "Verhoef",
                    "name_suffix": "",
                    "institution": "Leiden Institute of Advanced Computer Science",
                    "department": ""
                },
                {
                    "first_name": "Esther",
                    "middle_name": "",
                    "last_name": "Walker",
                    "name_suffix": "",
                    "institution": "UCSD",
                    "department": ""
                },
                {
                    "first_name": "Tyler",
                    "middle_name": "",
                    "last_name": "Marghetis",
                    "name_suffix": "",
                    "institution": "University of Indiana, Bloomington",
                    "department": ""
                },
                {
                    "first_name": "Seana",
                    "middle_name": "",
                    "last_name": "Coulson",
                    "name_suffix": "",
                    "institution": "UCSD",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27906/galley/17544/download/"
                }
            ]
        },
        {
            "pk": 28240,
            "title": "No Changes in Speed and Selectivity in Mobile Dating Choices Over Time",
            "subtitle": null,
            "abstract": "In speed-dating, the selectivity of liking a partner is relatively constant across events, but individuals change to faster, non-compensatory decision-making strategies to evaluate partners. Online, individuals have more romantic options, whichcan also lead the use of non-compensatory decision-making strategies. Some studies have also found lower selectivity inlarger choice sets. These patterns should accelerate as cognitive load increases over the course of the experiment, with lesstime and lower selectivity for partner choice as search continues. We tested this hypothesis using a popular, mobile-baseddating application. Forty users spent five minutes evaluating and liking or disliking a sequential stream of real profileswithin the application. We compared the ratio of likes to dislikes and time spent evaluating individual profiles and foundthat users spent nearly identical amounts of time evaluating individual profiles and similar levels of selectivity over thecourse of the experiment. We compare our results to speed-dating.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3v4040kr",
            "frozenauthors": [
                {
                    "first_name": "Samantha",
                    "middle_name": "",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Todd",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28240/galley/17899/download/"
                }
            ]
        },
        {
            "pk": 27715,
            "title": "No Coherent Evidence for Bilingual Advantages in Executive Functioning",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "executive functions"
                },
                {
                    "word": "selective attention"
                },
                {
                    "word": "bilingualism"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/53w7v4rb",
            "frozenauthors": [
                {
                    "first_name": "Kenneth",
                    "middle_name": "R",
                    "last_name": "Paap",
                    "name_suffix": "",
                    "institution": "University of California, San Francisco",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27715/galley/17355/download/"
                }
            ]
        },
        {
            "pk": 27789,
            "title": "Noisy Time Preference",
            "subtitle": null,
            "abstract": "People’s desire to be patient or impatient can fluctuate from\nmoment to moment, yet little is known about the effects of\nvariability in time preference on intertemporal choice\nbehavior. We examine this issue through the lens of an\nexponential discounting model with noisy discount factors. We\nshow that such a model can generate decreasing patience over\ntime, accounting for behavioral patterns typically attributed to\nhyperbolic discounting, while also making reasonable\npredictions regarding violations of intertemporal dominance.\nAdditionally, two experiments reveal that many participants do\ndisplay noise in their discount factors, and that a noisy discount\nfactor model outperforms hyperbolic models in terms of\nquantitative fit. Ultimately the majority of participants are best\ndescribed by some type of exponential discounting model\n(with or without noisy discount factors). These results indicate\nthat it may not be necessary to assume alternate forms of non-\nexponential discounting, as long as the discount factors in an\nexponential model are permitted to vary at random. These\nresults also highlight the importance of allowing for different\nsources of noise in choice modeling.People’s desire to be patient or impatient can fluctuate from\nmoment to moment, yet little is known about the effects of\nvariability in time preference on intertemporal choice\nbehavior. We examine this issue through the lens of an\nexponential discounting model with noisy discount factors. We\nshow that such a model can generate decreasing patience over\ntime, accounting for behavioral patterns typically attributed to\nhyperbolic discounting, while also making reasonable\npredictions regarding violations of intertemporal dominance.\nAdditionally, two experiments reveal that many participants do\ndisplay noise in their discount factors, and that a noisy discount\nfactor model outperforms hyperbolic models in terms of\nquantitative fit. Ultimately the majority of participants are best\ndescribed by some type of exponential discounting model\n(with or without noisy discount factors). These results indicate\nthat it may not be necessary to assume alternate forms of non-\nexponential discounting, as long as the discount factors in an\nexponential model are permitted to vary at random. These\nresults also highlight the importance of allowing for different\nsources of noise in choice modeling.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "decision making"
                },
                {
                    "word": "intertemporal choice"
                },
                {
                    "word": "Noise"
                },
                {
                    "word": "variability"
                },
                {
                    "word": "Computational Modeling"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4d85z8pr",
            "frozenauthors": [
                {
                    "first_name": "Lisheng",
                    "middle_name": "",
                    "last_name": "He",
                    "name_suffix": "",
                    "institution": "UPenn",
                    "department": ""
                },
                {
                    "first_name": "Sudeep",
                    "middle_name": "",
                    "last_name": "Bhatia",
                    "name_suffix": "",
                    "institution": "UPenn",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27789/galley/17429/download/"
                }
            ]
        },
        {
            "pk": 28322,
            "title": "Non-Symbolic Ratio Sense Supports Symbolic Fraction Success",
            "subtitle": null,
            "abstract": "Non-symbolic ratio processing and symbolic fraction processing both involve thinking about relations between two partsand relational thinking. Despite the close connections between non-symbolic ratio and symbolic fractions, previous re-search on non-symbolic ratio processing and symbolic fraction learning have proceeded separately. The current researchinvestigated whether children’s non-symbolic ratio sense support their symbolic fraction success. Using sample of 151children, we found that non-symbolic ratio sense significantly predicted fraction knowledge assessment scores and sym-bolic fraction comparison performance, but not for fraction number line estimation performance. The implications of thesefindings for theories of numerical development and for improving mathematics learning are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7m89321c",
            "frozenauthors": [
                {
                    "first_name": "Rui",
                    "middle_name": "",
                    "last_name": "Meng",
                    "name_suffix": "",
                    "institution": "University of Wisconsin Madison",
                    "department": ""
                },
                {
                    "first_name": "Percival",
                    "middle_name": "",
                    "last_name": "Matthews",
                    "name_suffix": "",
                    "institution": "University of Wisconsin Madison",
                    "department": ""
                },
                {
                    "first_name": "Edward",
                    "middle_name": "",
                    "last_name": "Hubbard",
                    "name_suffix": "",
                    "institution": "University of Wisconsin Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28322/galley/18011/download/"
                }
            ]
        },
        {
            "pk": 27963,
            "title": "Not all Active Learning is Equal: Predicting and Explaining Improves Transfer Relative to Answering Practice Questions",
            "subtitle": null,
            "abstract": "We compared students’ exam performance following one oftwo different types of active learning assignments. In oneversion students read text describing experimental evidence forthe principle being studied. In the other version, studentsinstead created a hypothesis and explanation, and then studiedand explained the results. The content was matched acrossconditions. Students performed better in exams requiringgeneralization to novel situations, after providing hypothesesand explanations than after reading the text and answeringquestions about it. These results suggest that prediction andexplanation cycles might be a better active learning approachto promote generalization and transfer than practice questions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "predict-observe-explain; active learning; retrieval practice"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/63k2d5fg",
            "frozenauthors": [
                {
                    "first_name": "Paulo",
                    "middle_name": "F",
                    "last_name": "Carvalho",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                },
                {
                    "first_name": "Kody",
                    "middle_name": "J",
                    "last_name": "Manke",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                },
                {
                    "first_name": "Kenneth",
                    "middle_name": "R",
                    "last_name": "Koedinger",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27963/galley/17601/download/"
                }
            ]
        },
        {
            "pk": 27713,
            "title": "Not Just a Window: Why Young Children Learn More from In-Person Events than Video-Mediated Events",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Transfer deficit"
                },
                {
                    "word": "video deficit"
                },
                {
                    "word": "development"
                },
                {
                    "word": "early childhood"
                },
                {
                    "word": "symbol use"
                },
                {
                    "word": "spactial memory"
                },
                {
                    "word": "object search"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4mx7q929",
            "frozenauthors": [
                {
                    "first_name": "Heather",
                    "middle_name": "L",
                    "last_name": "Kirkorian",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": []
        },
        {
            "pk": 27898,
            "title": "Not unreasonable: Carving vague dimensions with contraries and contradictions",
            "subtitle": null,
            "abstract": "Language provides multiple ways of conveying the opposite:A person not happy can be unhappy, sad, or perhaps neither,just not happy. Rather than being redundant, we hypothesizethat uncertainty about the meaning of negation markers allowslisteners to derive fine-grained distinctions among these vari-ous alternatives. We formalize this hypothesis in a probabilis-tic model of gradable adjectives (e.g., happy), and use this toaddress an outstanding puzzle: how to interpret double nega-tions (e.g., not unhappy). Our model makes surprising addi-tional predictions about a putative difference between morpho-logical antonyms (unhappy) and negated positives (not happy):Listeners should judge unhappy as more sad than not happyonly when confronted with alternatives in context; when inter-preted in isolation, we predict no difference in understanding.Two behavioral experiments confirm consistent orderings ofinterpretations that interact with the presentational context inthe way predicted. These findings support the hypothesis thatlisteners represent uncertainty even about the most logical ele-ments of language.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "semantics; pragmatics; negation; Bayesian cognitive model; Rational Speech Act"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7p2130hr",
            "frozenauthors": [
                {
                    "first_name": "Michael",
                    "middle_name": "Henry",
                    "last_name": "Tessler",
                    "name_suffix": "",
                    "institution": "Stanford",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Franke",
                    "name_suffix": "",
                    "institution": "University of Tubingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27898/galley/17536/download/"
                }
            ]
        },
        {
            "pk": 28227,
            "title": "Novel methods for measuring the cost of cognitive control in a patchforagingtaskand a demand selection task with Stroop",
            "subtitle": null,
            "abstract": "Evidence suggests exerting cognitive control carries an intrinsic cost and that individual differences in subjective costs mayaccount for differences in everyday control allocation. We developed two novel methods for quantifying an individualssubjective control cost and examined their relationship. We modified a standard patch foraging task so that subjects(N=18) had to complete a control-demanding task (N-Back) to travel between patches. We predicted subjects would acceptdiminishing rewards in a patch to avoid control demands, and used the Marginal Value Theorem to quantify the amount ofreward forfeited. In a second task, we estimated how many word-reading Stroop trials subjects would complete to avoid a(control-demanding) color-naming trial. We found that most subjects treated control as costly (i.e., made demand-avoidantchoices) in both tasks, and that there was a significant positive correlation between the estimated costs across tasks withina subject.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0bw6k13x",
            "frozenauthors": [
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Bustamante",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Augustus",
                    "middle_name": "",
                    "last_name": "Baker",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                },
                {
                    "first_name": "Allison",
                    "middle_name": "",
                    "last_name": "Burton",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Amitai",
                    "middle_name": "",
                    "last_name": "Shenhav",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Chloe",
                    "middle_name": "",
                    "last_name": "Hoeber",
                    "name_suffix": "",
                    "institution": "Occidental College",
                    "department": ""
                },
                {
                    "first_name": "Nathaniel",
                    "middle_name": "",
                    "last_name": "Daw",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Princeton",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28227/galley/17886/download/"
                }
            ]
        },
        {
            "pk": 27808,
            "title": "n-task Learning: Solving Multiple or Unknown Numbers of Reinforcement Learning Problems",
            "subtitle": null,
            "abstract": "Temporal difference (TD) learning models can perform poorlywhen optimal policy cannot be determined solely by sensoryinput. Converging evidence from studies of working memorysuggest that humans form abstract mental representations thatalign with significant features of a task, allowing such condi-tions to be overcome. The n-task learning algorithm (nTL) ex-tends TD models by utilizing abstract representations to formmultiple policies based around a common set of external in-puts. These external inputs are combined conjunctively withan abstract input that comes to represent attention to a task.nTL is used to solve a dynamic categorization problem that ismarked by frequently alternating tasks. The correct number oftasks is learned, as well as when to switch from one task repre-sentation to another, even when inputs are identical across alltasks. Task performance is shown to be optimal only when anappropriate number of abstract representations is used.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Reinforcement Learning"
                },
                {
                    "word": "Temporal-difference learning"
                },
                {
                    "word": "task switching"
                },
                {
                    "word": "Input abstraction"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7rg1b91f",
            "frozenauthors": [
                {
                    "first_name": "Mike",
                    "middle_name": "",
                    "last_name": "Jovanovich",
                    "name_suffix": "",
                    "institution": "Middle Tennessee State University",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "L",
                    "last_name": "Phillips",
                    "name_suffix": "",
                    "institution": "Middle Tennessee State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27808/galley/17448/download/"
                }
            ]
        },
        {
            "pk": 28328,
            "title": "Object-based attention in multiple frames of reference",
            "subtitle": null,
            "abstract": "Object-based attention acts as people paying more attention to the stimulus within an object. There are various definitionsof the object, from the original definition at the lower processing level (e.g., the frame), to the high semantic level (e.g.,the Chinese word), to the learned level (e.g., learned object). However, few studies examined the object at the middlerepresentational level - frame of reference (FOR). Here, we modified the classical two-object task to induce two FORswith different salience by four cues in four experiments. Results consistently showed that shorter response time (RT) andlower error rates (ER) in the valid cue condition than that in the invalid cue condition. Whats more, RT was longer andER was lower in the invalid cue within the FOR of high salience condition than that in the invalid cue within the FOR oflow salience condition. Our study verified the existence of object-based attention in FORs at the representational level andoffered a new insight of the mechanism of the FOR-object-based attention.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4rr0w024",
            "frozenauthors": [
                {
                    "first_name": "Weizhi",
                    "middle_name": "",
                    "last_name": "Nan",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                },
                {
                    "first_name": "Lizhu",
                    "middle_name": "",
                    "last_name": "Yan",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                },
                {
                    "first_name": "Jiamin",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                },
                {
                    "first_name": "Ya",
                    "middle_name": "",
                    "last_name": "Fan",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                },
                {
                    "first_name": "Hong",
                    "middle_name": "",
                    "last_name": "Lu",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                },
                {
                    "first_name": "Shimin",
                    "middle_name": "",
                    "last_name": "Fu",
                    "name_suffix": "",
                    "institution": "Guangzhou University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28328/galley/18024/download/"
                }
            ]
        },
        {
            "pk": 27786,
            "title": "Object Recognition when Features Arrive Dynamically",
            "subtitle": null,
            "abstract": "We report a model for object identification based on an exper-\niment that varies the arrival times of different features of the\nobjects. A single object, a circle with four spokes extending\nin different directions, is presented and must be classified as\neither one of four well trained target stimuli, or one of four\nwell trained foil stimuli. The features (spokes) are presented\neither simultaneously or successively at intervals of 16, 33, or\n50 ms., with target diagnostic features arriving first or last. All\ndurations are short enough that the display appears simultane-\nous. The data show that individual decisions vary with both\ntiming and diagnosticity. We apply a dynamic model based on\none reported in (Cox & Shiffrin, 2017) for episodic recognition\nmemory. Our model assumes features are perceived at vary-\ning times following presentation, possibly in error. At each\nmoment the current features are compared to the well learned\nmemory representations of the eight stimuli, producing a like-\nlihood ratio for target vs foil. A decision is made when the log\nlikelihood first exceeds a target decision boundary or falls be-\nlow a foil decision boundary. The model implements a form of\nBayesian optimal decision making given the assumptions con-\ncerning feature perception. It predicts the key findings quite\nwell.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Response time modeling"
                },
                {
                    "word": "Dynamic stimuli"
                },
                {
                    "word": "visual search"
                },
                {
                    "word": "object recognition"
                },
                {
                    "word": "Feature sampling"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9qs4q11n",
            "frozenauthors": [
                {
                    "first_name": "Samuel",
                    "middle_name": "M",
                    "last_name": "Harding",
                    "name_suffix": "",
                    "institution": "Indiana",
                    "department": ""
                },
                {
                    "first_name": "Richard",
                    "middle_name": "M",
                    "last_name": "Shiffrin",
                    "name_suffix": "",
                    "institution": "Indiana",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27786/galley/17426/download/"
                }
            ]
        },
        {
            "pk": 27796,
            "title": "On the instrumental value of hypothetical and counterfactual thought",
            "subtitle": null,
            "abstract": "People often engage in “offline simulation”, considering what\nwould happen if they performed certain actions in the future,\nor had performed different actions in the past. Prior research\nshows that these simulations are biased towards actions a per-\nson considers to be good—i.e., likely to pay off. We ask\nwhether, and why, this bias might be adaptive. Through com-\nputational experiments we compare five agents who differ only\nin the way they engage in offline simulation, across a variety\nof different environment types. Broadly speaking, our exper-\niments reveal that simulating actions one already regards as\ngood does in fact confer an advantage in downstream decision\nmaking, although this general pattern interacts with features\nof the environment in important ways. We contrast this bias\nwith alternatives such as simulating actions whose outcomes\nare instead uncertain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6nf1p85w",
            "frozenauthors": [
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Icard",
                    "name_suffix": "",
                    "institution": "Stanford",
                    "department": ""
                },
                {
                    "first_name": "Fiery",
                    "middle_name": "",
                    "last_name": "Chushman",
                    "name_suffix": "",
                    "institution": "Harvard",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27796/galley/17436/download/"
                }
            ]
        },
        {
            "pk": 28356,
            "title": "On the Role of Semantic Map in a Socially-Emotional Cognitive Architecture forCreative Assistants",
            "subtitle": null,
            "abstract": "Future intelligent virtual co-robots, or cobots, will work as extensions of the human mind and body in creative cognitivetasks, such as design, invention, or creation of art. Because these tasks depend on emotional attitudes, the cobot needsto maintain a social-emotional contact with the user. This can be achieved based on a cognitive architecture, in whichthe current emotional state of the user is represented in a two-dimensional weak semantic map. Cobot action selectionis determined by this state, the action appraisal, and the currently active M-schema. Main results include a significantlyhigher quality of the outcome, compared to the control condition, without a semantic map. It is remarkable that one andthe same cognitive model proves useful in various domains, including creative assistants of a choreographer, a composer,a designer, and an insight problem solver. The work yields preliminary results that suggest many potential practicalapplications. This research is supported by the Russian Science Foundation Grant # 18-11-00336.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8m93b7hd",
            "frozenauthors": [
                {
                    "first_name": "Alexei",
                    "middle_name": "",
                    "last_name": "Samsonovich",
                    "name_suffix": "",
                    "institution": "National Research Nuclear University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28356/galley/18082/download/"
                }
            ]
        },
        {
            "pk": 27966,
            "title": "Optimal face recognition performance involves a balance between global and local information processing: Evidence from cultural difference",
            "subtitle": null,
            "abstract": "In face recognition, eye gaze to the eye region is reported to\nbe associated with better performance than to the center of a\nface. Nevertheless, Caucasians and Asians differ in how much\nthey look at the eyes when they scan a face, but have\ncomparable identification performance. To resolve this issue,\nhere we test the hypothesis that optimal face recognition\nperformance involves a balance between global and local face\nprocessing. Thus, Asians may benefit from enhancement of\nlocal processing and vice versa for Caucasians. We showed\nthat local attention priming using hierarchical letter stimuli\nled to more eye-focused eye movement patterns compared to\nglobal attention priming in both Asians and Caucasians.\nHowever, Asians had better performance after local priming\nthan global priming, whereas Caucasian showed the opposite\neffect. These results suggest that engagement of global/local\nattention leads to face-center/eye biased eye movements\nrespectively, and optimal recognition performance involves\nboth global and local processing/gaze transitions between the\nface center and eyes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "eye movement"
                },
                {
                    "word": "face recognition"
                },
                {
                    "word": "cultural difference"
                },
                {
                    "word": "hidden Markov mdoel"
                },
                {
                    "word": "EMHMM"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/75g8k2cd",
            "frozenauthors": [
                {
                    "first_name": "Zhijie",
                    "middle_name": "",
                    "last_name": "Cheng",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "William",
                    "middle_name": "G",
                    "last_name": "Hayward",
                    "name_suffix": "",
                    "institution": "U of Hong Kong; University of Auckland",
                    "department": ""
                },
                {
                    "first_name": "Antoni",
                    "middle_name": "B",
                    "last_name": "Chan",
                    "name_suffix": "",
                    "institution": "U of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Janet",
                    "middle_name": "H",
                    "last_name": "Hsiao",
                    "name_suffix": "",
                    "institution": "U of Hong Kong",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27966/galley/17604/download/"
                }
            ]
        },
        {
            "pk": 27990,
            "title": "Optimized behavior in a robot model of sequential action",
            "subtitle": null,
            "abstract": "People learn and use complex sequential actions on a daily basis, despite living in a high-dimensional environment andbody. Sequential action learning is sometimes studied in cognitive psychology using button-pressing tasks such as Nissenand Bullemers (1987) serial respone time (SRT) task. However, the SRT task only measures the speed of button presses,neglecting the richand difficult to controltrajectory of the arm, which can show predictive movements and other contextualeffects. In this study, we evolve neural networks to carry out a mouse-based SRT task under conditions of differingprediction uncertainty. We replicate behaviors found in a recent human experiment, and explore ramifications for humansequence learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3tq5j9m3",
            "frozenauthors": [
                {
                    "first_name": "Roy",
                    "middle_name": "",
                    "last_name": "de Kleijn",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                },
                {
                    "first_name": "George",
                    "middle_name": "",
                    "last_name": "Kachergis",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Bernhard",
                    "middle_name": "",
                    "last_name": "Hommel",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27990/galley/17629/download/"
                }
            ]
        },
        {
            "pk": 28129,
            "title": "Optimizing Cue Use in Student Restudy Decisions",
            "subtitle": null,
            "abstract": "It is believed that decisions about what information needs\nadditional study before an upcoming exam are dependent\nupon metacognitive processes. While a great deal of research\nhas explored these processes, far less work has explored how\nto optimize restudy decisions. In the present study we\nexamined both what cues are most predictive of future\nretrieval and test two potential ways of nudging learners to\nuse these cues when making their restudy decisions. All\nmethods and analyses were pre-registered on the Open\nScience Framework. Assessment of cue-utilization revealed\nthat pre-judgment recall accuracy and pre-judgment retrieval\nlatency, but not stimulus font size, predicted future retrieval.\nAdditionally, both feedback about pre-judgment retrieval\naccuracy and having participants make retrospective\nconfidence judgments led learners to more heavily weigh\nprejudgment retrieval accuracy when making their restudy\ndecisions. This increase in relevant cue use, however, did not\ncarry over into more accurate restudy decisions. These\nfindings suggest that subtle manipulations can push learners\nto utilize more appropriate cues when making their restudy\ndecisions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Self-guided learning; Restudy Decisions;\nMetacognitive Judgments; Cue Use"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/360015qg",
            "frozenauthors": [
                {
                    "first_name": "Alison",
                    "middle_name": "",
                    "last_name": "Robey",
                    "name_suffix": "",
                    "institution": "University of Maryland",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Dougherty",
                    "name_suffix": "",
                    "institution": "University of Maryland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28129/galley/17788/download/"
                }
            ]
        },
        {
            "pk": 28031,
            "title": "Order matters: Distributional properties of speech to young children bootstrapslearning of semantic representations",
            "subtitle": null,
            "abstract": "Some researchers claim that language acquisition is critically dependent on experiencing linguistic input in order of in-creasing complexity. We tested this hypothesis using a simple recurrent neural network (SRN) trained to predict wordsequences in CHILDES, a 5-million-word corpus of speech directed to children. First, we demonstrated that age-orderedCHILDES exhibits a gradual increase in linguistic complexity. Next, we compared the performance of two groups ofSRNs trained on CHILDES which had either been age-ordered or not. Specifically, we assessed learning of grammaticaland semantic structure and showed that training on age-ordered input facilitates learning of semantic, but not of sequentialstructure. Follow-up analyses suggest that higher noun-density in speech to younger children combined with weight en-trenchment could account for this effect. The persistent learning improvement is consistent with the neural commitmenthypothesis in the second language acquisition literature, which asserts that L1 representation reduces neural resourcesavailable for L2 learning. Similarly, exposure to noun-rich input first but not last (age-ordered CHILDES), may induce arepresentational advantage for lexical semantic acquisition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9pz9s6jm",
            "frozenauthors": [
                {
                    "first_name": "Philip",
                    "middle_name": "",
                    "last_name": "Huebner",
                    "name_suffix": "",
                    "institution": "UC Riverside",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28031/galley/17670/download/"
                }
            ]
        },
        {
            "pk": 28171,
            "title": "Ordinal ranking as a method for assessing real-world proportional representations",
            "subtitle": null,
            "abstract": "Across two experiments, we use ordinal ranking to examinethe processing and representations involved in the estimationof large-scale, real-world proportions. Specifically, in twoexperiments people estimated two kinds of important real-world proportions: the demographic makeup of theircommunities, and spending by the U.S. Federal government.Our goal was to assess the metric scaling properties thatcharacterize perceptions of these quantities. In particular,previous work in numerical proportions has positedlogarithmic or linear representations (Opfer & Siegler, 2007),or linear representations with task-dependent rescaling (Barth& Paladino, 2011; Cohen & Blanc-Goldhammer, 2011). Thecurrent context differs markedly from this prior work in thatthe values we are examining are not explicitly presented toparticipants, nor directly experienced, but must be estimatedon the basis of masses of complex experiences. Ordinalranking of the quantities, combined with a Thurstonianmodeling approach, allows a unique means for estimating theinternal scale properties of numerical structures. We find thatpeople largely rely on mixed representations that emphasizelog-odds transformations of these vaguely known, butsocially important values. While the budget data explored inExperiment 1 were unable to distinguish log and log-oddstransformed internal models, the demographic proportionsexplored in Experiment 2 favored log-odds models.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "numerical reasoning; proportion estimation;probability weighting; mathematical cognition"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3d6132hd",
            "frozenauthors": [
                {
                    "first_name": "Crystal",
                    "middle_name": "",
                    "last_name": "Trueborn",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Landy",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28171/galley/17830/download/"
                }
            ]
        },
        {
            "pk": 28327,
            "title": "Out of the mouth comes evil: a exploration of an anchoring effect of minimumpayment information under ”affect rich” and ”affect poor” situation.",
            "subtitle": null,
            "abstract": "Stewart (2009) found evidences for anchoring effect of minimum payment information that decisions about repaymentsare anchored (Tversky & Kahneman, 1974) upon minimum payment information and people would repay less than theyotherwise would and incur greater interest charges. On the basis of Stewarts (2009) study, this study examined whetheranchoring effect of minimum payment information would differ between affect rich and affect poor situation (e. g.,Rottenstreich & Hsee, 2001). To accomplish these, this study required participants to answer payment value for donationto save stray dogs under conditions where the affect rich/poor situations were manipulated by presentation of picturesof the dogs. Results showed that the manipulations in the experiment significantly affected participants payment prices,indicating that anchoring effect of minimum prices was enhanced under the ”affect rich” situation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/55c2z7s2",
            "frozenauthors": [
                {
                    "first_name": "Kuninori",
                    "middle_name": "",
                    "last_name": "Nakamura",
                    "name_suffix": "",
                    "institution": "Faculty of Social Innovation Seijo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28327/galley/18022/download/"
                }
            ]
        },
        {
            "pk": 27737,
            "title": "Outputs as inputs: Sequential Models of the Products of Infant 'Statistical Learning' of Language",
            "subtitle": null,
            "abstract": "To explore whether current notions of statistically-based\nlanguage learning could successfully scale to infants’\nlinguistic experiences “in the wild”, we implemented a\nstatistical-clustering word-segmentation model (Saffran et al.,\n1997) and sent its outputs to an implementation of a “frame”\nbased form class tagger (Mintz, 2003) and, separately, to a\nsimple word-order heuristic parser (Gervain et al., 2008). We\ntested this pipeline model on various input types, ranging\nfrom quite idealized (orthographic words) to more naturalistic\nresyllabified corpora. We ask how these modeled capacities\nwork together when they receive the noisy outputs of\nupstream word finding processes as input, which more closely\nresembles the scenario infants face in language acquisition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Language Acquisition"
                },
                {
                    "word": "Distributional analysis"
                },
                {
                    "word": "Word segmentation"
                },
                {
                    "word": "word class acquisition"
                },
                {
                    "word": "Word order acquisition"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8vk888x0",
            "frozenauthors": [
                {
                    "first_name": "Angelica",
                    "middle_name": "",
                    "last_name": "Buerkin-Pontrelli",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Joseph",
                    "middle_name": "",
                    "last_name": "Coffey",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Swingley",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27737/galley/17377/download/"
                }
            ]
        },
        {
            "pk": 28137,
            "title": "Over-representation of Extreme Events in Decision-Making: A Rational Metacognitive Account",
            "subtitle": null,
            "abstract": "The Availability bias, manifested in the over-representation ofextreme eventualities, is a well-known cognitive bias, and isgenerally taken as evidence of human irrationality. In thiswork, we present the first rational, metacognitive account ofthe Availability bias, formally articulated at Marr’s algorith-mic level of analysis. Concretely, we present a normative,metacognitive model of how a cognitive system should over-represent extreme eventualities, depending on the amount oftime available for decision-making. Our Sample-based Ex-pected Utility model also accounts for two well-known fram-ing effects in human decision-making under risk—the fourfoldpattern of risk preferences in outcome probability (Tversky& Kahneman, 1992) and in outcome magnitude (Markovitz,1952)—thereby providing the first metacognitively-rationalbasis for the aforementioned effects. Empirical evidence con-firms an important prediction of our model. Surprisingly, ourmodel is strikingly robust with respect to its focal parameter.We discuss the implications of our work for studies on hu-man decision-making, and conclude by presenting a counter-intuitive prediction of our model, which, if confirmed, wouldhave intriguing implications for human decision-making un-der risk. To our knowledge, our model is the first metacog-nitive, resource-rational process model of cognitive biases indecision-making. Notably, our work also contributes to thefields of artificial intelligence and computational statistics, bypresenting a previously unknown proposal distribution, withfirm rational grounds, broadly applicable to the influential sub-field of importance sampling Monte Carlo methods.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Availability bias; Decision-making under uncer-tainty and risk; Metacognitively rational models; Fourfold pat-tern of risk preferences"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/85p7246k",
            "frozenauthors": [
                {
                    "first_name": "Ardavan",
                    "middle_name": "S",
                    "last_name": "Nobandegani",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "da Silva",
                    "last_name": "Castanheira",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "A. Ross",
                    "middle_name": "",
                    "last_name": "Otto",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "R",
                    "last_name": "Schultz",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28137/galley/17796/download/"
                }
            ]
        },
        {
            "pk": 28136,
            "title": "Over-representation of Extreme Events in Decision-Making:A Rational Metacognitive Account",
            "subtitle": null,
            "abstract": "The Availability bias, manifested in the over-representation ofextreme eventualities, is a well-known cognitive bias, and isgenerally taken as evidence of human irrationality. In thiswork, we present the first rational, metacognitive account ofthe Availability bias, formally articulated at Marr’s algorith-mic level of analysis. Concretely, we present a normative,metacognitive model of how a cognitive system should over-represent extreme eventualities, depending on the amount oftime available for decision-making. Our Sample-based Ex-pected Utility model also accounts for two well-known fram-ing effects in human decision-making under risk—the fourfoldpattern of risk preferences in outcome probability (Tversky& Kahneman, 1992) and in outcome magnitude (Markovitz,1952)—thereby providing the first metacognitively-rationalbasis for the aforementioned effects. Empirical evidence con-firms an important prediction of our model. Surprisingly, ourmodel is strikingly robust with respect to its focal parameter.We discuss the implications of our work for studies on hu-man decision-making, and conclude by presenting a counter-intuitive prediction of our model, which, if confirmed, wouldhave intriguing implications for human decision-making un-der risk. To our knowledge, our model is the first metacog-nitive, resource-rational process model of cognitive biases indecision-making. Notably, our work also contributes to thefields of artificial intelligence and computational statistics, bypresenting a previously unknown proposal distribution, withfirm rational grounds, broadly applicable to the influential sub-field of importance sampling Monte Carlo methods.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Availability bias; Decision-making under uncer-tainty and risk; Metacognitively rational models; Fourfold pat-tern of risk preferences"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/03n9t8ts",
            "frozenauthors": [
                {
                    "first_name": "Ardavan",
                    "middle_name": "S",
                    "last_name": "Nobandegani",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "da Silva",
                    "last_name": "Castanheira",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "A Ross",
                    "middle_name": "",
                    "last_name": "Otto",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "R",
                    "last_name": "Schultz",
                    "name_suffix": "",
                    "institution": "McGill",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28136/galley/17795/download/"
                }
            ]
        },
        {
            "pk": 27929,
            "title": "Parafoveal-on-Foveal Effects in High-Skill Spellers: Disambiguating Preview Influence Ambiguous Word Recognition",
            "subtitle": null,
            "abstract": "Parafoveal-on-foveal (POF) effects occur when reading time\non a fixated word in the fovea is influenced by the upcoming\nword in the parafovea. Evidence for POF effects have been\ninconsistent and met with methodological scrutiny (Drieghe,\n2011), but recent research suggests that skill differences in\nspelling may impact POF effects (Veldre & Andrews, 2014).\nTo extend this literature, the current study examines the\ninfluence of spelling ability on POF effects by leveraging\nsemantic ambiguity. Participants read sentences containing an\nambiguous target immediately followed by a disambiguating\nword as their eye movements were recorded. Disambiguating\nwords were manipulated to be either consistent or inconsistent\nwith the likely interpretation of the ambiguous word. Results\nindicate that high-skilled spellers have longer reading times on\nthe target word when the disambiguating word is inconsistent.\nThese findings suggest that POF effects may be possible,\nparticularly within a highly-skilled subset of skilled readers.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "parafoveal-on-foveal effects; word skipping; parafoveal preview"
                },
                {
                    "word": "semantic ambiguity; eye movement control; spelling; individual differences"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/66c1d5v4",
            "frozenauthors": [
                {
                    "first_name": "Ashley",
                    "middle_name": "N",
                    "last_name": "Abraham",
                    "name_suffix": "",
                    "institution": "Kent State",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "A",
                    "last_name": "Eskenazi",
                    "name_suffix": "",
                    "institution": "Stetson University",
                    "department": ""
                },
                {
                    "first_name": "Jennifer",
                    "middle_name": "M",
                    "last_name": "Roche",
                    "name_suffix": "",
                    "institution": "Kent State",
                    "department": ""
                },
                {
                    "first_name": "Jocelyn",
                    "middle_name": "R",
                    "last_name": "Folk",
                    "name_suffix": "",
                    "institution": "Kent State",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27929/galley/17567/download/"
                }
            ]
        },
        {
            "pk": 28393,
            "title": "Partial awareness of strategies used in a complex decision making task",
            "subtitle": null,
            "abstract": "There are individual differences in complex task performance that can be attributed to the strategies people use and howthey adapt their strategies to task demands (Schunn & Reder, 2001). It is unclear if people are aware of the strategythey use and how this affects adaptation of their strategy. The present study assessed participants awareness of their ownstrategy while performing a complex task. Part of the task required participants to select which objects to sort based ondifferent object features that affect their score. Using a participants selections, their selection strategy was inferred usingautomated techniques and compared to their reported strategy. Participants reported using more of the object featuresin their strategies than what was inferred based on their choices. The features in the inferred strategy only partiallyoverlapped with the features participants reported. In addition, greater awareness of ones strategy was associated withbetter task performance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Abstracts-Posters",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3t63j0hp",
            "frozenauthors": [
                {
                    "first_name": "Aaron",
                    "middle_name": "",
                    "last_name": "Wong",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "Barnes",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Gary",
                    "middle_name": "",
                    "last_name": "Bradshaw",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                },
                {
                    "first_name": "Jarrod",
                    "middle_name": "",
                    "last_name": "Moss",
                    "name_suffix": "",
                    "institution": "Mississippi State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28393/galley/18158/download/"
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            ]
        },
        {
            "pk": 27832,
            "title": "Partial source dependence and reliability revision: the impact of shared backgrounds",
            "subtitle": null,
            "abstract": "The paper explores how people revise their belief in ahypothesis and the reliability of sources given independenceof sources or partial dependence (e.g. the sources share abackground). Specifically, we test a formal model ofreliability revision.The study provides support for Bovens and Hartmann’smodel of reliability revision. If a source provides a positivereport for an unlikely hypothesis, participants initially revisethe reliability of the source negatively. However, as additionalpositive reports emerge, they increase their estimate of thereliability of the source. Further, if it becomes known thesources are partially dependent (here, taught the same schoolof thought), the reliability of the source decreases again. Bothof these findings are in line with the Bayesian approach toreliability revision.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Bayesian reasoning"
                },
                {
                    "word": "Reliability revision"
                },
                {
                    "word": "Sequential testimonies"
                }
            ],
            "section": "Publication-based-Talks",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8t96w1mk",
            "frozenauthors": [
                {
                    "first_name": "Jens",
                    "middle_name": "Koed",
                    "last_name": "Madsen",
                    "name_suffix": "",
                    "institution": "Oxford",
                    "department": ""
                },
                {
                    "first_name": "Ulrike",
                    "middle_name": "",
                    "last_name": "Hahn",
                    "name_suffix": "",
                    "institution": "University of London",
                    "department": ""
                },
                {
                    "first_name": "Toby",
                    "middle_name": "D",
                    "last_name": "Pilditch",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2018-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27832/galley/17471/download/"
                }
            ]
        }
    ]
}