API Endpoint for journals.

GET /api/articles/?format=api&offset=19200
HTTP 200 OK
Allow: GET
Content-Type: application/json
Vary: Accept

{
    "count": 38487,
    "next": "https://eartharxiv.org/api/articles/?format=api&limit=100&offset=19300",
    "previous": "https://eartharxiv.org/api/articles/?format=api&limit=100&offset=19100",
    "results": [
        {
            "pk": 27316,
            "title": "Abductive, Causal, and Counterfactual ConditionalsUnder Incomplete Probabilistic Knowledge",
            "subtitle": null,
            "abstract": "We study abductive, causal, and non-causal conditionals inindicative and counterfactual formulations using probabilis-tic truth table tasks under incomplete probabilistic knowledge(N = 80). We frame the task as a probability-logical inferenceproblem. The most frequently observed response type acrossall conditions was a class of conditional event interpretationsof conditionals; it was followed by conjunction interpreta-tions. An interesting minority of participants neglected someof the relevant imprecision involved in the premises when in-ferring lower or upper probability bounds on the target con-ditional/counterfactual (“halfway responses”). We discuss theresults in the light of coherence-based probability logic and thenew paradigm psychology of reasoning",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "abductive conditionals; causal conditionals; coun-terfactuals; indicative conditionals; psychological experiment;uncertain argument form; probabilistic truth table task"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7j66f9kd",
            "frozenauthors": [
                {
                    "first_name": "Niki",
                    "middle_name": "",
                    "last_name": "Pfeifer",
                    "name_suffix": "",
                    "institution": "LMU Munich",
                    "department": ""
                },
                {
                    "first_name": "Leena",
                    "middle_name": "",
                    "last_name": "Tulkki",
                    "name_suffix": "",
                    "institution": "University of Helsinki",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27316/galley/16952/download/"
                }
            ]
        },
        {
            "pk": 26899,
            "title": "A Biologically Constrained Model of Semantic Memory Search",
            "subtitle": null,
            "abstract": "The semantic fluency task has been used to understand the ef-fects of semantic relationships on human memory search. Avariety of computational models have been proposed that ex-plain human behavioral data, yet it remains unclear how mil-lions of spiking neurons work in unison to realize the cogni-tive processes involved in memory search. In this paper, wepresent a biologically constrained neural network model thatperforms the task in a fashion similar to humans. The modelreproduces experimentally observed response timing effects,as well as similarity trends within and across semantic cate-gories derived from responses. Three different sources of theassociation data have been tested by embedding associationsin neural connections, with free association norms providingthe best match.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "semantic memory; associations; semantic search;spiking neural network; neural engineering framework"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1n71300b",
            "frozenauthors": [
                {
                    "first_name": "Ivana",
                    "middle_name": "",
                    "last_name": "Kajic",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Jan",
                    "middle_name": "",
                    "last_name": "Gosmann",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Brent",
                    "middle_name": "",
                    "last_name": "Komer",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Ryan",
                    "middle_name": "W.",
                    "last_name": "Orr",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Terrence",
                    "middle_name": "C.",
                    "last_name": "Stewart",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Eliasmith",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26899/galley/16535/download/"
                }
            ]
        },
        {
            "pk": 36003,
            "title": "Abstracts",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/547160n3",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36003/galley/26855/download/"
                }
            ]
        },
        {
            "pk": 35986,
            "title": "Abstracts",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2vs396js",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": []
        },
        {
            "pk": 26983,
            "title": "A case for systematic sound symbolism in pragmatics:\nThe role of the first phoneme in question prediction in context",
            "subtitle": null,
            "abstract": "Turn-taking in conversation is a cognitively demanding process\nthat proceeds rapidly due to interlocutors utilizing a range of cues\nto aid prediction. In the present study we set out to test recent\nclaims that content question words (also called wh-words) sound\nsimilar within languages as an adaptation to help listeners predict\nthat a question is about to be asked. We test whether upcoming\nquestions can be predicted based on the first phoneme of a turn and\nthe prior context. We analyze the Switchboard corpus of English\nby means of a decision tree to test whether /w/ and /h/ are good\nstatistical cues of upcoming questions in conversation. Based on\nthe results, we perform a controlled experiment to test whether\npeople really use these cues to recognize questions. In both studies\nwe show that both the initial phoneme and the sequential context\nhelp predict questions. This contributes converging evidence that\nelements of languages adapt to pragmatic pressures applied during\nconversation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "questions; wh-words; question words; turn-\ntaking; speech-act recognition; question prediction"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5cb2k68j",
            "frozenauthors": [
                {
                    "first_name": "Anita",
                    "middle_name": "",
                    "last_name": "Slonimska",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Seán",
                    "middle_name": "G.",
                    "last_name": "Roberts",
                    "name_suffix": "",
                    "institution": "University of Bristol",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26983/galley/16619/download/"
                }
            ]
        },
        {
            "pk": 27318,
            "title": "A categorical (fixed point) foundation for cognition: (adjoint) corecursion",
            "subtitle": null,
            "abstract": "Computationalism has been the pre-eminent framework for models of mind, since the cognitive revolution. However,the plethora of apparently incommensurate approaches seems to undermine hope for a common computational foundation.Category theory provides a mathematically rigorous foundation for computation that includes recursion and corecursion. Weshow that corecursion unifies various cognitive behaviours for comparison and contrast in a principled and novel way. Forinstance, Chomsky’s merge function is a universal morphism, which has a dual, called comerge. One implication of this workis that corecursion appears to be the rule rather than the (human) exception in contrast to Chomsky’s view of recursion.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2hm303dm",
            "frozenauthors": [
                {
                    "first_name": "Steven",
                    "middle_name": "",
                    "last_name": "Phillips",
                    "name_suffix": "",
                    "institution": "National Institute of Advanced Industrial Science and Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27318/galley/16954/download/"
                }
            ]
        },
        {
            "pk": 26965,
            "title": "A cognitive analysis of deception without lying",
            "subtitle": null,
            "abstract": "When the interests of interlocutors are not aligned, either partymay wish to avoid truthful disclosure. A sender wishing toconceal the truth from a receiver may lie by providing falseinformation, mislead by actively encouraging the receiver toreach a false conclusion, or simply be uninformative by provid-ing little or no relevant information. Lying entails moral andother hazards, such as detection and its consequences, and isthus often avoided. We focus here on the latter two strategies,arguably more pernicious and prevalent, but not without theirown drawbacks. We argue and show in two studies that whenchoosing between these options, senders consider the level ofsuspicion likely to be exercised on the part of the receiver andhow much truth must be revealed in order to mislead. Extend-ing Bayesian models of cooperative communication to includehigher level inference regarding the helpfulness of the senderleads to insight into the strategies employed in non-cooperativecontexts.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "deception; Inductive inference; communication;pragmatics"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0x9132dw",
            "frozenauthors": [
                {
                    "first_name": "Keith",
                    "middle_name": "",
                    "last_name": "Ransom",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Wouter",
                    "middle_name": "",
                    "last_name": "Voorspoels",
                    "name_suffix": "",
                    "institution": "University of Leuven",
                    "department": ""
                },
                {
                    "first_name": "Amy",
                    "middle_name": "",
                    "last_name": "Perfors",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "J.",
                    "last_name": "Navarro",
                    "name_suffix": "",
                    "institution": "University of New South Wales",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26965/galley/16601/download/"
                }
            ]
        },
        {
            "pk": 27405,
            "title": "A Cognitive Model of Social Influence",
            "subtitle": null,
            "abstract": "We describe two different cognitive process models of a wellknown experiment on social influence (Salganik, Dodds, &Watts, 2006). One model, the social influence model,reproduced the choices that participants took by modelingboth the cognitive processes the participant engaged in andthe social influences that the participant saw. The secondmodel, the pure cognitive model, used only cognitivecapabilities and did not model any social influences that theparticipant saw. Somewhat surprisingly, the two modelsshowed no difference in quality of fit (the pure cognitivemodel actually fit slightly better than the social influencemodel), suggesting that social influence models should takecognitive functions into account in their theories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Models"
                },
                {
                    "word": "Social Influence"
                },
                {
                    "word": "cognitivearchitectures"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/46c5w744",
            "frozenauthors": [
                {
                    "first_name": "J. Gregory",
                    "middle_name": "",
                    "last_name": "Trafton",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "J. Malcolm",
                    "middle_name": "",
                    "last_name": "McCurry",
                    "name_suffix": "",
                    "institution": "Harris",
                    "department": ""
                },
                {
                    "first_name": "Kevin",
                    "middle_name": "",
                    "last_name": "Zish",
                    "name_suffix": "",
                    "institution": "George Mason University",
                    "department": ""
                },
                {
                    "first_name": "Laura",
                    "middle_name": "M.",
                    "last_name": "Hiatt",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Sangeet",
                    "middle_name": "",
                    "last_name": "Khemlani",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27405/galley/17041/download/"
                }
            ]
        },
        {
            "pk": 26859,
            "title": "A Cognitive Model of Strategic Deliberation and Decision Making",
            "subtitle": null,
            "abstract": "We study game theoretic decision making using a\nbidirectional evidence accumulation model. Our model\nrepresents both preferences for the strategies available to the\ndecision maker, as well as beliefs regarding the opponent’s\nchoices. Through sequential sampling and accumulation, the\nmodel is able to intelligently reason through two-player\nstrategic games, while also generating specific violations of\nNash equilibrium typically observed in these games. The\nmain ingredients of accumulator models, stochastic sampling\nand dynamic accumulation, play a critical role in explaining\nthese behavioral patterns as well as generating novel\npredictions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision making; Game theory; Sequential\nsampling; Preference accumulation"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9rq1h35s",
            "frozenauthors": [
                {
                    "first_name": "Russell",
                    "middle_name": "",
                    "last_name": "Golman",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Sudeep",
                    "middle_name": "",
                    "last_name": "Bhatia",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26859/galley/16495/download/"
                }
            ]
        },
        {
            "pk": 26848,
            "title": "A Cognitive-Pharmacokinetic Computational Model of the Effect of Toluene onPerformance",
            "subtitle": null,
            "abstract": "We developed a cognitive-pharmacokinetic computational(CPC) model to understand how pharmacoactive substances,such as caffeine and toluene, modulate cognition. In this in-tegrated model, dynamic physiological mechanisms are sim-ulated to predict concentrations of the solvent toluene in thebrain, which modulates specific cognitive systems in a dose-response fashion over multiple hours. We used our CPC modelto reanalyze the results from prior research that documented anincrease in reaction time following exposure to toluene in sev-eral laboratory tasks with no change in accuracy. Our analysisprovides tentative evidence that toluene affects motor execu-tion, rather than attention or declarative memory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "ACT-R; Toluene; Pharmacokinetic; Computa-tional Models"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1mh7619k",
            "frozenauthors": [
                {
                    "first_name": "Christopher",
                    "middle_name": "R.",
                    "last_name": "Fisher",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "Myers",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "Reem",
                    "middle_name": "",
                    "last_name": "Hassan",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "",
                    "last_name": "Stevens",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "C. Eric",
                    "middle_name": "",
                    "last_name": "Hack",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "Jeffery",
                    "middle_name": "",
                    "last_name": "Gearhart",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                },
                {
                    "first_name": "Glenn",
                    "middle_name": "",
                    "last_name": "Gunzelmann",
                    "name_suffix": "",
                    "institution": "Air Force Research Laboratory, Wright-Patterson Air Force Base",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26848/galley/16484/download/"
                }
            ]
        },
        {
            "pk": 26993,
            "title": "A Common Neural Component for Finger Gnosis and Magnitude Comparison",
            "subtitle": null,
            "abstract": "Finger gnosis (the ability to identify which finger has beentouched) and magnitude comparison (the ability to determinewhich of two numbers is larger) are surprisingly correlated.We present a spiking neuron model of a common componentthat could be used in both tasks: an array of pointers. Weshow that if the model's single tuned parameter is set to matchhuman accuracy performance in one task, then it also matcheson the other task (with the exception of one data point). Thisprovides a novel explanation of the relation, and proposes acommon component that could be used across cognitive tasks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "finger gnosis; magnitude comparison; spikingneurons; neural engineering framework"
                },
                {
                    "word": "numerical cognition"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/24q1d9ks",
            "frozenauthors": [
                {
                    "first_name": "Terrence",
                    "middle_name": "C.",
                    "last_name": "Stewart",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Marcie",
                    "middle_name": "",
                    "last_name": "Penner-Wilger",
                    "name_suffix": "",
                    "institution": "University College at Western University",
                    "department": ""
                },
                {
                    "first_name": "Rylan",
                    "middle_name": "J.",
                    "last_name": "Waring",
                    "name_suffix": "",
                    "institution": "University of Guelph",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "L.",
                    "last_name": "Anderson",
                    "name_suffix": "",
                    "institution": "University of Maryland",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26993/galley/16629/download/"
                }
            ]
        },
        {
            "pk": 27477,
            "title": "A comparative assessment of embodied and computational topic extraction",
            "subtitle": null,
            "abstract": "Word embedding algorithms like word2vec (Mikolov et al., 2013) have enabled advances in topic modelling bytraining shallow neural networks on the co-occurrence of words in corpuses of sentences. However, it is not clear how thisprocess reflects human cognition. This poster will compare the results of document classification using the word2vec skipgrammodel and the 20k sensorimotor word norms collected by the presenter and colleagues (Lynott & Connell 2013; Carney et al.,in prep.) (These latter norms establish how concepts are processed by way of perceptual and motor schemes, and thus offer auseful proxy for human conceptual classification.) The results of the comparison will generate insights into the different waysin which higher-order concepts are inferred, and allow systematic biases in concept formation to be identified. It will also allowfor machine learning processes to be finessed so as to more accurately reflect human-level modes of cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/72z5492c",
            "frozenauthors": [
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Carney",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27477/galley/17113/download/"
                }
            ]
        },
        {
            "pk": 27287,
            "title": "A comparison between human micro-affordances and computational classification",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2qk16285",
            "frozenauthors": [
                {
                    "first_name": "Arthur-Henri",
                    "middle_name": "",
                    "last_name": "Michalland",
                    "name_suffix": "",
                    "institution": "University of Montpellier",
                    "department": ""
                },
                {
                    "first_name": "Denis",
                    "middle_name": "",
                    "last_name": "Brouillet",
                    "name_suffix": "",
                    "institution": "University of Montpellier",
                    "department": ""
                },
                {
                    "first_name": "Philippe",
                    "middle_name": "",
                    "last_name": "Fraisse",
                    "name_suffix": "",
                    "institution": "University of Montpellier",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27287/galley/16923/download/"
                }
            ]
        },
        {
            "pk": 26947,
            "title": "A Computational Logic Approach to Human Syllogistic Reasoning",
            "subtitle": null,
            "abstract": "A recent meta-analysis (Khemlani & Johnson-Laird, 2012)about psychological experiments of syllogistic reasoningdemonstrates that the conclusions drawn by human reasonersstrongly deviate from conclusions of classical logic. Moreover,none of the current cognitive theories predictions fit reliablythe empirical data. In this paper, we show how humansyllogistic reasoning can be modeled under a new cognitivetheory, the Weak Completion Semantics. Our analysis basedon computational logics identifies seven principles necessaryto draw the inferences. Hence, this work contributes to acomputational foundation of cognitive reasoning processes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Human Reasoning; Syllogistic Reasoning; LogicProgramming; Three-valued Łukasiewicz Logic; Abduction"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0df8k0z1",
            "frozenauthors": [
                {
                    "first_name": "Ana",
                    "middle_name": "",
                    "last_name": "Oliveira da Costa",
                    "name_suffix": "",
                    "institution": "Dresden University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Emmanuelle-Anna",
                    "middle_name": "Dietz",
                    "last_name": "Saldanha",
                    "name_suffix": "",
                    "institution": "Dresden University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Steffen",
                    "middle_name": "",
                    "last_name": "H ̈olldobler",
                    "name_suffix": "",
                    "institution": "Dresden University of Technology",
                    "department": ""
                },
                {
                    "first_name": "Marco",
                    "middle_name": "",
                    "last_name": "Ragni",
                    "name_suffix": "",
                    "institution": "University of Freiburg",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26947/galley/16583/download/"
                }
            ]
        },
        {
            "pk": 27030,
            "title": "A Computational Model for Constructing Preferences for Multiple Choice Options",
            "subtitle": null,
            "abstract": "When choosing between multiple alternatives, people usuallydo not have ready-made preferences in their mind but ratherconstruct them on the go. The 2N-ary Choice Tree Model(Wollschlaeger & Diederich, 2012) proposes a preference con-struction process for N choice options from description, whichis based on attribute weights, differences between attribute val-ues, and noise. It is able to produce similarity, attraction,and compromise effects, which have become a benchmark formulti-alternative choice models, but also several other contextand reference point effects. Here, we present a new and math-ematically tractable version of the model – the Simple ChoiceTree Model – which also explains the above mentioned effectsand additionally accounts for the positive correlation betweenthe attraction and compromise effect, and the negative correla-tion between these two and the similarity effect as observed byBerkowitsch, Scheibehenne, and Rieskamp (2014).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "computational model; multi-alternative choice;choice from description; preference construction; context ef-fects"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8sr4k4m9",
            "frozenauthors": [
                {
                    "first_name": "Lena",
                    "middle_name": "M.",
                    "last_name": "Wollschlaeger",
                    "name_suffix": "",
                    "institution": "Jacobs University Bremen",
                    "department": ""
                },
                {
                    "first_name": "Adele",
                    "middle_name": "",
                    "last_name": "Diederich",
                    "name_suffix": "",
                    "institution": "Jacobs University Bremen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27030/galley/16666/download/"
                }
            ]
        },
        {
            "pk": 27012,
            "title": "A computational model for decision tree search",
            "subtitle": null,
            "abstract": "How do people plan ahead in sequential decision-makingtasks? In this article, we compare computational models of hu-man behavior in a challenging variant of tic-tac-toe, to inves-tigate the cognitive processes underlying sequential planning.We validate the most successful model by predicting choicesduring games, two-alternative forced choices and board evalu-ations. We then use this model to study individual skill differ-ences, the effects of time pressure and the nature of expertise.Our findings suggest that people perform less tree search un-der time pressure, and that players search more as they improveduring learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Sequential decision-making"
                },
                {
                    "word": "Behavioral model-ing"
                },
                {
                    "word": "expertise"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0v94n7cd",
            "frozenauthors": [
                {
                    "first_name": "Bas",
                    "middle_name": "",
                    "last_name": "van Opheusde",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Gianni",
                    "middle_name": "",
                    "last_name": "Galbiati",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Zahy",
                    "middle_name": "",
                    "last_name": "Bnaya",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Yunqi",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Wei",
                    "middle_name": "Ji",
                    "last_name": "Ma",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27012/galley/16648/download/"
                }
            ]
        },
        {
            "pk": 27069,
            "title": "A Computational Model for Reasoning About the Paper Folding TaskUsing Visual Mental Images",
            "subtitle": null,
            "abstract": "The paper folding task is commonly used for the evaluation ofnonverbal, spatial reasoning skills. In this paper, we presenta computational model that attempts to use visual-imagery-based representations and operations to solve this task. Themodel was tested against all problems from the standard pa-per folding task and achieved a perfect score, illustrating thatvisual-imagery-based representations and operations are suf-ficiently expressive to capture at least one successful solutionstrategy. Although the model does not closely resemble humancognitive processing, and thus should not be considered in itscurrent form to be a plausible psychological model of humantask performance, the assumptions made and their implicationsfor our understanding of human cognition on the paper foldingtask point to fruitful lines of future work towards this goal.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "artificial intelligence; cognitive assessment; paperfolding; spatial skills."
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7dk0w3n2",
            "frozenauthors": [
                {
                    "first_name": "James",
                    "middle_name": "",
                    "last_name": "Ainooson",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Maithilee",
                    "middle_name": "",
                    "last_name": "Kunda",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27069/galley/16705/download/"
                }
            ]
        },
        {
            "pk": 26865,
            "title": "A Computational Model for the Dynamical Learning of Event Taxonomies",
            "subtitle": null,
            "abstract": "We present a computational model that can learn event tax-onomies online from the continuous sensorimotor informationflow perceived by an agent while interacting with its environ-ment. Our model implements two fundamental learning bi-ases. First, it learns probabilistic event models as temporal sen-sorimotor forward models and event transition models, whichpredict event model transitions given particular perceptual cir-cumstances. Second, learning is based on the principle of min-imizing free energy, which is further biased towards the detec-tion of free energy transients. As a result, the algorithm formsconceptual structures that encode events and event boundaries.We show that event taxonomies can emerge when the algo-rithm is run on multiple levels of precision. Moreover, weshow that generally any type of forward model can be used,as long as it learns sufficiently fast. Finally, we show that thedeveloped structures can be used to hierarchically plan goal-directed behavior by means of active inference.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "event models; object interaction; predictive encod-ing; event segmentation; free energy; active inference; eventtaxonomy; concept learning"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/15q1k95w",
            "frozenauthors": [
                {
                    "first_name": "Christian",
                    "middle_name": "",
                    "last_name": "Gumbsch",
                    "name_suffix": "",
                    "institution": "University of T ̈ubingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26865/galley/16501/download/"
                }
            ]
        },
        {
            "pk": 27097,
            "title": "A Computational Model of the Role of Attention in Subitizing and Enumeration",
            "subtitle": null,
            "abstract": "Recent studies in the perception of numerosity have indicatedthat subitizing (the rapid and accurate enumeration of smallquantities) requires attention. We present a novel computa-tional model of enumeration in which attention unifies dis-tinct processes of numerosity approximation, subitizing, andexplicit counting. We demonstrate how this model accountsfor both the reaction time results from the subitizing literatureand the effects of attentional load on subitizing accuracy.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "attention; subitizing; enumeration; perception ofnumerosity; counting; inattentional blindness"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/48b3s2p3",
            "frozenauthors": [
                {
                    "first_name": "Gordon",
                    "middle_name": "",
                    "last_name": "Briggs",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Will",
                    "middle_name": "",
                    "last_name": "Bridewell",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "F.",
                    "last_name": "Bello",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27097/galley/16733/download/"
                }
            ]
        },
        {
            "pk": 26917,
            "title": "A core-affect model of decision making in simple and complex tasks",
            "subtitle": null,
            "abstract": "When it comes to decision making, the dominant viewsuggests that engaging in a detailed analytical thought processis more beneficial than deciding based on one’s feelings.However, there seems to be a tradeoff, as the complexity andamount of elements on which to base the decision increases,decisions based on affect seem to be more accurate thandecisions based on a thorough analytical process in specificcontexts. In those last cases, an affective modulation ofmemory may help to make better decisions in complex tasksthat exceed human’s limited cognitive capacities. Some dualprocess accounts, ‘‘deliberation-without-attention’’hypothesis (Dijksterhuis et al., 2006), oppose a cognitive (i.e.,conscious) route to an affective (i.e., unconscious) route.Since most dual process accounts suggest one type of processis better than the other, the interaction and integration ofaffective and more conscious analytical processes in decisionmaking have been understudied. To address this issue, wepropose an explanation of the dynamics and interaction ofcognitive (i.e., explicit) and affective (i.e., implicit) encodingand retrieval of elements in memory, using a unified theorybased on core affect (Russell, 2003), in the shape of acognitive model in the ACT-R cognitive architecture.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Core affect; ACT-R; decision making; dualprocess theory; memory modulation; implicit strategy"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2db3r63w",
            "frozenauthors": [
                {
                    "first_name": "Othalia",
                    "middle_name": "",
                    "last_name": "Larue",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Alexander",
                    "middle_name": "",
                    "last_name": "Hough",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                },
                {
                    "first_name": "Ion",
                    "middle_name": "",
                    "last_name": "Juvina",
                    "name_suffix": "",
                    "institution": "Wright State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26917/galley/16553/download/"
                }
            ]
        },
        {
            "pk": 27379,
            "title": "Acquiring pitch associations across modalities: the role of experience",
            "subtitle": null,
            "abstract": "When interpreting our perceptual world, information from multiple perceptual modalities is often associated. Suchcrossmodal associations can arise from innate structural connections in the brain, statistical correlations in the environment, orthrough language. In a large group of participants across a wide age range and language background, we tested crossmodalassociations between pitch and 7 dimensions in comparison modalities. We found evidence supporting the existence of all 7types of associations, but the strength of association varied by dimension. Pitch-angularity and pitch-weight judgments werethe most robust associations. In general, strength of associations increased with age, with significant associations occurring inthe oldest age group (age 19+), consistent with experiential accounts of crossmodal associations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8822640c",
            "frozenauthors": [
                {
                    "first_name": "Laura",
                    "middle_name": "",
                    "last_name": "Speed",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Ilja",
                    "middle_name": "",
                    "last_name": "Croijmans",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Sarah",
                    "middle_name": "",
                    "last_name": "Dolscheid",
                    "name_suffix": "",
                    "institution": "University of Cologne",
                    "department": ""
                },
                {
                    "first_name": "Asifa",
                    "middle_name": "",
                    "last_name": "Majid",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27379/galley/17015/download/"
                }
            ]
        },
        {
            "pk": 27063,
            "title": "Action and actor gaze mismatch effects during spoken sentence processing",
            "subtitle": null,
            "abstract": "Eye tracking research on situated language comprehension hasshown that participants rely more on a recent event than on aplausible future event during spoken sentence comprehension.When people saw a recent action event and then they listenedto a German (NP1-Verb-Adv-NP2) past or futuric present tensesentence, they preferentially looked at the recent event targetover another plausible target object (that might be involvedin a future action) independent of tense. This preferential in-spection persisted even when future events and futuric presentsentences were much more frequent within the experiment,or when a gaze cue biased towards the future action target.The present experiments extend this line of research by intro-ducing incongruence (in Experiment 1 a past tense verb mis-matched the recently seen action and in Experiment 2 an actorgaze cue mismatched the past tense sentence condition). Canthe verb-action and the gaze-sentence mismatches eliminatethe recent-event inspection preference? Would participants re-call information in post-experimental memory tests better formatches (the futuric present tense condition) than mismatches(the past tense condition)? Results revealed inspection of therecent event target as participants processed the verb-actionmismatch (Exp 1) and actor gaze incongruence (Exp 2). How-ever, the gaze (but not the verb-action) incongruence elimi-nated the overall recent event preference in the NP2 region.The memory tests also showed some evidence for a reversal ofthe recent-event preference.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Eye-tracking; spoken sentence comprehen-sion; visual world paradigm; recent-event preference; event-sentence incongruence; actor gaze mismatch"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4h02f1rk",
            "frozenauthors": [
                {
                    "first_name": "Dato",
                    "middle_name": "",
                    "last_name": "Abashidze",
                    "name_suffix": "",
                    "institution": "Bielefeld University",
                    "department": ""
                },
                {
                    "first_name": "Pia",
                    "middle_name": "",
                    "last_name": "Knoeferle",
                    "name_suffix": "",
                    "institution": "Humboldt University of Berlin",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27063/galley/16699/download/"
                }
            ]
        },
        {
            "pk": 27388,
            "title": "Actions that Modify Schedules of Reinforcement",
            "subtitle": null,
            "abstract": "Many everyday activities involve the use of one action tomodify the effects of another: When driving, shiftinggears modifies the influence of pressing the gas pedal onacceleration; when cooking, the rate of adding aparticular ingredient modifies the influence of stirring onviscosity. Here, we investigate a general ability to learnhow to use actions to control schedules of reinforcement.In Experiment 1, participants quickly discovered theoptimal rate of responding on an action that controlledthe rate of reward contingent on performing a differentaction. In Experiment 2, when the modifying action wasitself rewarded, participants failed to discover the optimalrate. Implications for formal theories of instrumentalbehavior are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Schedules of reinforcement; reward learning;instrumental contingencies."
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3wx4k7zh",
            "frozenauthors": [
                {
                    "first_name": "Mac",
                    "middle_name": "",
                    "last_name": "Strelioff",
                    "name_suffix": "",
                    "institution": "University of California Irvine",
                    "department": ""
                },
                {
                    "first_name": "Mimi",
                    "middle_name": "",
                    "last_name": "Liljeholm",
                    "name_suffix": "",
                    "institution": "University of California Irvine",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27388/galley/17024/download/"
                }
            ]
        },
        {
            "pk": 27237,
            "title": "Action Understanding in High-Functioning Autism: The Faux Pas Task Revisited",
            "subtitle": null,
            "abstract": "Individuals with autism spectrum disorders (ASD) are said to\nhave deficits in “theory of mind.” The present paper explores\ntwo main accounts of the mechanisms underlying these\ndeficits. On one account, high-functioning adults with ASD\nstruggle to infer others’ mental states. On another account,\nthey lack an ability to integrate those mental states into a\ncoherent understanding of action. We tested these two\naccounts by making several modifications to the Faux Pas\ntask—a commonly used advanced theory of mind task—\nincluding the presentation of explicit mental state information.\nSurprisingly, in contrast to previous work, individuals on the\nautism spectrum exhibited both intact integration and intact\ninference.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Theory of mind; intentional action; autism spectrum\ndisorder; mental state inference"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5n49b682",
            "frozenauthors": [
                {
                    "first_name": "Joanna",
                    "middle_name": "",
                    "last_name": "Korman",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Tiziana",
                    "middle_name": "",
                    "last_name": "Zalla",
                    "name_suffix": "",
                    "institution": "Pavillon Jardin\nEcole Normale Supérieure",
                    "department": ""
                },
                {
                    "first_name": "Bertram",
                    "middle_name": "F.",
                    "last_name": "Malle",
                    "name_suffix": "",
                    "institution": "Brown University,",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27237/galley/16873/download/"
                }
            ]
        },
        {
            "pk": 27428,
            "title": "Actively Detecting Patterns in an Artificial Language to Learn Non-AdjacentDependencies",
            "subtitle": null,
            "abstract": "Many grammatical dependencies in natural language involve elements that are not adjacent, such as between thesubject and verb in ”the dog always barks”. We recently showed that non-adjacent dependencies are easily learnable withoutpauses in the signal when speech is presented rapidly. In this study, we used an online measure to look at the relationshipbetween online parsing and the learning performance from the offline assessment of non-adjacent dependency learning. Wefound that participants who showed current parsing of the language online also learned the dependencies better. However, thispattern disappeared when they are explicitly told where the boundaries are before parsing. Theories of non-adjacent dependencylearning are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1425x2jh",
            "frozenauthors": [
                {
                    "first_name": "Hao",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Jason",
                    "middle_name": "",
                    "last_name": "Zevin",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Calvin",
                    "middle_name": "",
                    "last_name": "Leather",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Toby",
                    "middle_name": "",
                    "last_name": "Mintz",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27428/galley/17064/download/"
                }
            ]
        },
        {
            "pk": 27360,
            "title": "Adaptability and Neural Reuse in Minimally Cognitive Agents",
            "subtitle": null,
            "abstract": "Cognitive agents are continuously faced with new problems.To facilitate adaptation, emerging theories of neural reuse pro-pose that evolution might often favor re-purposing existingbrain structures for new functions. This paper presents a novelapproach to the study of neural reuse based on the evolutionof simulated agents in an object-categorization task. We arti-ficially evolve populations of dynamic neural networks to per-form two variants of a categorization task that alternate overevolutionary time. We find that populations become increas-ingly adaptive over repeated exposures to the tasks. Analysisof evolved networks reveals two types of equally-fit solutions:one that is specialized to a given task variant and does not adaptto changes easily; and another that is more general, in that itcan adapt to the other task with minimal change to its structure.Interestingly, we find that populations exposed to alternatingtasks spontaneously locate the latter type of structures.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "neural networks; minimally-cognitive behaviors;neural reuse; artificial evolution; evolvability"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5wr3682d",
            "frozenauthors": [
                {
                    "first_name": "Matthew",
                    "middle_name": "",
                    "last_name": "Setzler",
                    "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": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27360/galley/16996/download/"
                }
            ]
        },
        {
            "pk": 27382,
            "title": "Adapting to a listener with incomplete lexical semantics",
            "subtitle": null,
            "abstract": "Speakers involved in a communicative exchange construct aninternal model of their addressees and draw upon the model tocraft utterances that are likely to be understood. In many real-world situations (e.g., when talking to a non-expert, non-nativespeaker, or a child), this process of audience design involvesidentifying gaps in the lexical-semantic knowledge of thelistener and selecting alternative expressions. We examinespeaker adaptation to a listener with incomplete lexicalknowledge in the spatial domain, specifically a failure tocomprehend the basic terms left/right. Experimental andmodeling results provide evidence of rapid adaptation that ismodulated by the availability of alternative spatial terms. Weconsider how our approach relates to recent work incomputational pragmatics, and suggest that adaptation to thelexical knowledge of the addressee is an important butrelatively understudied topic for future research.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "language adaptation; audience design; spatiallanguage; lexical semantics; computational pragmatics"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0cr531wn",
            "frozenauthors": [
                {
                    "first_name": "Sadhwi",
                    "middle_name": "",
                    "last_name": "Srinivas",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                },
                {
                    "first_name": "Barbara",
                    "middle_name": "",
                    "last_name": "Landau",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                },
                {
                    "first_name": "Colin",
                    "middle_name": "",
                    "last_name": "Wilson",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27382/galley/17018/download/"
                }
            ]
        },
        {
            "pk": 27560,
            "title": "Adaptive response priors in context-dependent decision-making",
            "subtitle": null,
            "abstract": "Context (such as our location or current goal) informs everyday decisions, both by predicting stimuli and determiningrelevant responses. How do we develop priors that are general enough to apply in various contexts yet specific enough tomaximize reward in a given context? We investigated this using the AX-CPT, a task in which a cue determines which buttonto press for a probe that appears seconds later. We manipulated the frequency of the probe given the cue across participantsand built a diffusion model to estimate how the cue informs participants’ priors for the decision. We found that participants’context-dependent priors were closer to each other and less extreme than those predicted by a model that maximizes rewardrate given the true stimulus frequencies. However, participants’ priors were optimal given their subjective frequency estimates,which showed that they averaged response probabilities across cues when the cues made sufficiently similar predictions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1jz5v7jp",
            "frozenauthors": [
                {
                    "first_name": "Olga",
                    "middle_name": "",
                    "last_name": "Lositsky",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Shvartsman",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "C.",
                    "last_name": "Wilson",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "D.",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27560/galley/17196/download/"
                }
            ]
        },
        {
            "pk": 27366,
            "title": "A Data Driven Approach for Making Analogies",
            "subtitle": null,
            "abstract": "Making analogies is an important way for people to explain\nand understand new concepts. Though making analogies is\nnatural for human beings, it is not a trivial task for a dia-\nlogue agent. Making analogies requires the agent to estab-\nlish a correspondence between concepts in two different\ndomains. In this work, we explore a data-driven approach\nfor making analogies automatically. Our proposed approach\nworks with data represented as a flat graphical structure,\nwhich can either be designed manually or extracted from In-\nternet data. For a given concept from the base domain, our\nanalogy agent can automatically suggest a corresponding\nconcept from the target domain, and a set of mappings be-\ntween the relationships each concept has as supporting evi-\ndence. We demonstrate the working of this algorithm by\nboth reproducing a classical example of analogy inference\nand making analogies in new domains generated from\nDBPedia data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "creativity; analogy; intelligent agents"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2dx8b228",
            "frozenauthors": [
                {
                    "first_name": "Mei",
                    "middle_name": "",
                    "last_name": "Si",
                    "name_suffix": "",
                    "institution": "Rensselaer Polytechnic Institute",
                    "department": ""
                },
                {
                    "first_name": "Craig",
                    "middle_name": "",
                    "last_name": "Carlson",
                    "name_suffix": "",
                    "institution": "Rensselaer Polytechnic Institute",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27366/galley/17002/download/"
                }
            ]
        },
        {
            "pk": 27306,
            "title": "A Domain-Independent Approach of Cognitive Appraisal Augmented by HigherCognitive Layer of Ethical Reasoning",
            "subtitle": null,
            "abstract": "According to cognitive appraisal theory, emotion in an indi-vidual is the result of how a situation/event is evaluated by theindividual. This evaluation has different outcomes among peo-ple and it is often suggested to be operationalised by a set ofrules or beliefs acquired by the subject throughout develop-ment. Unfortunately, this view is particularly detrimental forcomputational applications of emotion appraisal. In fact, it re-quires providing a knowledge base that is particularly difficultto establish and manage, especially in systems designed forhighly complex scenarios, such as social robots. In addition,according to appraisal theory, an individual might elicit morethan one emotion at a time in reaction to an event. Hence, de-termining which emotional state should be attributed in rela-tionship to a specific event is another critical issue not yet fullyaddressed by the available literature. In this work, we showthat: (i) the cognitive appraisal process can be realised withouta complex set of rules; instead, we propose that this processcan be operationalised by knowing only the positive or nega-tive perceived effect the event has on the subject, thus facili-tating extensibility and integrability of the emotional system;(ii) the final emotional state to attribute in relation to a specificsituation is better explained by ethical reasoning mechanisms.These hypotheses are supported by our experimental results.Therefore, this contribution is particularly significant to pro-vide a more simple and generalisable explanation of cognitiveappraisal theory and to promote the integration between theo-ries of emotion and ethics studies, currently often neglected bythe available literature.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive appraisal theory; computational emo-tion model; emotion combination; ethics"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2409j1r0",
            "frozenauthors": [
                {
                    "first_name": "Suman",
                    "middle_name": "",
                    "last_name": "Ojha",
                    "name_suffix": "",
                    "institution": "University of Technology Sydney",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Vitale",
                    "name_suffix": "",
                    "institution": "University of Technology Sydney",
                    "department": ""
                },
                {
                    "first_name": "Mary-Anne",
                    "middle_name": "",
                    "last_name": "Williams",
                    "name_suffix": "",
                    "institution": "University of Technology Sydney",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27306/galley/16942/download/"
                }
            ]
        },
        {
            "pk": 35993,
            "title": "Adult Hispanic ESL Students and Graded Readers",
            "subtitle": null,
            "abstract": "This study examined the extent to which graded readers vis-à-vis scaffolded silent reading (ScSR) resulted\nin increased vocabulary, reading comprehension, and\na positive attitude toward reading. A mixed-methods\nstudy was administered to two upper-intermediate adult\nESL classes at a community college in southwestern Arizona. Both groups took The Vocabulary Size Test and\nTABE Complete Language Assessment System–English.\nThe treatment group selected and read graded readers,\nmet individually with the instructor, and kept a journal;\nin addition, several students from the treatment group\nwere interviewed at the beginning and end of the study.\nDescriptive statistics were used on the pre- and posttests.\nThe findings were promising and showed some growth in\nvocabulary and reading comprehension for both the treatment and control groups. Furthermore, participants of\nthe treatment group expressed a positive attitude toward\nreading graded readers through scaffolded silent reading.\nAs a result, this study demonstrated that graded readers\nused with scaffolded silent reading show promise with this\nstudent population.",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Theme Section - Extensive Reading",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0mk9q4dw",
            "frozenauthors": [
                {
                    "first_name": "Liza",
                    "middle_name": "E.",
                    "last_name": "Martinez",
                    "name_suffix": "",
                    "institution": "Arizona Western College, San Luis Branch",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/35993/galley/26845/download/"
                }
            ]
        },
        {
            "pk": 27007,
            "title": "A Dynamic Process Model for Predicting Workload in an Air Traffic ControllerTask",
            "subtitle": null,
            "abstract": "We present a dynamic process model for workload, developedaccording to a conducted experiment, which recorded the pupildilation during an air traffic controller simulation. We describehow we built such a dynamic system based on the collecteddata. Logged events that happened in our simulation were usedas system input and the recorded pupil dilation as output. Af-terwards, we used the MATLAB system identification toolboxto identify the transfer function between input and output. Theidentified model is validated with a validation data set that hasbeen excluded from the identification process. Results showthat we are able to explain nearly 50% of the variance of therecorded pupil dilation data in the air traffic controller simu-lation. Moreover, the model explains some contrary results ofthe statistical analysis from our experiment.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Dynamic process model; System theory; Work-load; Pupillometry; Air traffic controllers"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/49x5146n",
            "frozenauthors": [
                {
                    "first_name": "Martina",
                    "middle_name": "",
                    "last_name": "Truschzinski",
                    "name_suffix": "",
                    "institution": "University of Technology Chemnitz",
                    "department": ""
                },
                {
                    "first_name": "Maria",
                    "middle_name": "",
                    "last_name": "Wirzberger",
                    "name_suffix": "",
                    "institution": "University of Technology Chemnitz",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27007/galley/16643/download/"
                }
            ]
        },
        {
            "pk": 26833,
            "title": "A Dynamic Tradeoff Model of Intertemporal Choice",
            "subtitle": null,
            "abstract": "The delay discounting perspective, which assumes an\nalternative-wise processing of attribute information, has long\ndominated research on intertemporal choice. Recent studies,\nhowever, have suggested that intertemporal choice is based on\nattribute-wise comparison. This line of research culminated in\nthe tradeoff model (Scholten & Read, 2010; Scholten, Read,\n& Sanborn, 2014), which can accommodate most established\nbehavioral regularities in intertemporal choice. One drawback\nof the tradeoff model, however, is that it is static, providing\nno account of the dynamic process leading to a choice. Here\nwe develop a dynamic tradeoff model that can qualitatively\naccount for empirical findings in intertemporal choice\nregarding not only choices but also response times. The\ndynamic model also outperforms the original, static tradeoff\nmodel when quantitatively fitting choices from representative\ndata sets, and even outperforms the best-performing dynamic\nmodel derived from Decision Field Theory in Dai and\nBusemeyer (2014) when fitting both choices and response\ntimes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "intertemporal choice; tradeoff model; dynamic\nmodels"
                },
                {
                    "word": "random utility"
                },
                {
                    "word": "discrimination threshold"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/906340xm",
            "frozenauthors": [
                {
                    "first_name": "Junyi",
                    "middle_name": "",
                    "last_name": "Dai",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Timothy",
                    "middle_name": "J.",
                    "last_name": "Pleskac",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Thorsten",
                    "middle_name": "",
                    "last_name": "Pachur",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26833/galley/16469/download/"
                }
            ]
        },
        {
            "pk": 26818,
            "title": "A Flexible Mapping Scheme for Discrete and DimensionalEmotion Representations: Evidence from Textual Stimuli",
            "subtitle": null,
            "abstract": "While research on emotions has become one of the most pro-ductive areas at the intersection of cognitive science, artifi-cial intelligence and natural language processing, the diversityand incommensurability of emotion models seriously hampersprogress in the field. We here propose kNN regression as asimple, yet effective method for computationally mapping be-tween two major strands of emotion representations, namelydimensional and discrete emotion models. In a series of ma-chine learning experiments on data sets of textual stimuli wegather evidence that this approach reaches a human level ofreliability using a relatively small number of data points only.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Models of Human Emotion; Representation Map-ping; Machine Learning; Natural Language Processing"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/670801tm",
            "frozenauthors": [
                {
                    "first_name": "Sven",
                    "middle_name": " ",
                    "last_name": "Buechel",
                    "name_suffix": "",
                    "institution": "Friedrich-Schiller-Universit ̈at Jena",
                    "department": ""
                },
                {
                    "first_name": "Udo",
                    "middle_name": "",
                    "last_name": "Hahn",
                    "name_suffix": "",
                    "institution": "Friedrich-Schiller-Universit ̈at Jena",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26818/galley/16454/download/"
                }
            ]
        },
        {
            "pk": 26949,
            "title": "A Formal Approach to Modeling the Cost of Cognitive Control",
            "subtitle": null,
            "abstract": "This paper introduces a formal method to model the level of de-mand on control when executing cognitive processes. The costof cognitive control is parsed into an intensity cost which en-capsulates how much additional input information is requiredso as to get the specified response, and an interaction costwhich encapsulates the level of interference between individ-ual processes in a network. We develop a formal relationshipbetween the probability of successful execution of desired pro-cesses and the control signals (additive control biases). Thisrelationship is also used to specify optimal control policies toachieve a desired probability of activation for processes. Weobserve that there are boundary cases when finding such con-trol policies which leads us to introduce the interaction cost.We show that the interaction cost is influenced by the relativestrengths of individual processes, as well as the directionalityof the underlying competition between processes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "cognitive control; multi-tasking; intensity; iden-tity"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6sb336sz",
            "frozenauthors": [
                {
                    "first_name": "Kayhan",
                    "middle_name": "",
                    "last_name": "Ozcimder",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Biswadip",
                    "middle_name": "",
                    "last_name": "Dey",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Sebastian",
                    "middle_name": "",
                    "last_name": "Musslick",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Giovanni",
                    "middle_name": "",
                    "last_name": "Petri",
                    "name_suffix": "",
                    "institution": "ISI Foundation",
                    "department": ""
                },
                {
                    "first_name": "Nesreen",
                    "middle_name": "K.",
                    "last_name": "Ahmed",
                    "name_suffix": "",
                    "institution": "Intel Labs",
                    "department": ""
                },
                {
                    "first_name": "Theodore",
                    "middle_name": "L.",
                    "last_name": "Willke",
                    "name_suffix": "",
                    "institution": "Intel Labs",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "D.",
                    "last_name": "Cohen",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26949/galley/16585/download/"
                }
            ]
        },
        {
            "pk": 27159,
            "title": "After braking comes hasting: reversed effects of indirect associations in 2nd and 4th\ngraders",
            "subtitle": null,
            "abstract": "The Associative Read-Out Model (AROM) suggests that\nassociations between words can be defined by the log likelihood\nthat they occur together more often in sentences than predicted by\ntheir single-word frequency. Moreover, semantic relations can be\ndefined by associative spreading across many common associates.\nHere, we addressed developmental effects of associative and\nsemantic priming. Thus, we manipulated sentence-co-occurrence-\nbased direct (syntagmatic) and common (paradigmatic)\nassociations between prime and target words in 2nd and 4th graders.\nSyntagmatic associations decreased response times and error rates\nin both, 2nd and 4th graders. Paradigmatic associations increased\nerrors rates in 2nd graders, whereas they decreased errors rates in\n4th graders. These results suggest that 2nd graders profit from\nsyntagmatic, i.e. contiguity-based associations, while a benefit\nfrom paradigmatic-semantic relationship probably develops from\ngeneralizing across many of these simple associations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Interactive Activation Model"
                },
                {
                    "word": "Associative Read-Out\nModel"
                },
                {
                    "word": "Semantic Priming"
                },
                {
                    "word": "computational models"
                },
                {
                    "word": "Syntagmatic-\nParadigmatic shift"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5343w9vd",
            "frozenauthors": [
                {
                    "first_name": "Nicole",
                    "middle_name": "",
                    "last_name": "Franke",
                    "name_suffix": "",
                    "institution": "University of Wuppertal",
                    "department": ""
                },
                {
                    "first_name": "André",
                    "middle_name": "",
                    "last_name": "Roelke",
                    "name_suffix": "",
                    "institution": "University of Wuppertal",
                    "department": ""
                },
                {
                    "first_name": "Ralph",
                    "middle_name": "R.",
                    "last_name": "Radach",
                    "name_suffix": "",
                    "institution": "University of Wuppertal",
                    "department": ""
                },
                {
                    "first_name": "Markus",
                    "middle_name": "J.",
                    "last_name": "Hofmann",
                    "name_suffix": "",
                    "institution": "University of Wuppertal",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27159/galley/16795/download/"
                }
            ]
        },
        {
            "pk": 27078,
            "title": "Against the group actor assumption in joint action research",
            "subtitle": null,
            "abstract": "A central assumption in joint action research is that in order toexplain how individuals act as part of a group, we must firstexplain how the group comes into existence. This assump-tion has led to an unnecessarily narrow research programme:research has focussed largely on interpersonal coordinationmechanisms. I outline an alternative approach predicated ona dynamic conception of the ecosystem. On this view, thereis no need to assume that actors must first constitute a groupagent with their fellows before entering into coordinated ac-tion. Such coordination can be more efficiently explained byrecognizing that all actions perturb the structure of the ecosys-tem itself in a manner that can alter the action possibilitiesavailable to neighbouring actors. This move allows us to over-come entrenched debates over the nature of shared intention-ality, and to instead focus on practical interventions in multi-actor settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "joint action; shared intentionality; ecosystems;ecological psychology"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0f36n652",
            "frozenauthors": [
                {
                    "first_name": "Ed",
                    "middle_name": "",
                    "last_name": "Baggs",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27078/galley/16714/download/"
                }
            ]
        },
        {
            "pk": 27182,
            "title": "Age differences in language comprehension during driving:\nRecovery from prediction errors is more effortful for older adults",
            "subtitle": null,
            "abstract": "Prior research yielded conflicting findings regarding\nwhether older adults show a greater processing cost than\nyounger adults when encountering unpredicted semantic\nmaterial during language processing. Here, we\ninvestigated whether age-related differences in recovery\nfrom prediction error are influenced by increased\ndemands on working memory. We used a dual task\ndesign: a primary sentence comprehension task in which\nsemantic predictions were fulfilled or violated, and a\nconcurrent driving task, thought to limit working memory\nresources in resolving prediction errors. In the dual task,\nolder participants showed an increase in comprehension\naccuracy for sentences with semantic violations, while\ndemonstrating a decrease in driving accuracy. Thus, when\nworking memory resources were limited, older adults\nfocused exclusively on the language task and neglected\nthe driving task. This could be related to an age-related\nincrease in generating semantic predictions, or to a\ngeneral inability among older adults to divide attention\nbetween two cognitively demanding tasks.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "aging"
                },
                {
                    "word": "semantic expectancy"
                },
                {
                    "word": "dual tasking"
                },
                {
                    "word": "attention allocation"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2v12n3h6",
            "frozenauthors": [
                {
                    "first_name": "Katja",
                    "middle_name": "",
                    "last_name": "Häuser",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Vera",
                    "middle_name": "",
                    "last_name": "Demberg",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                },
                {
                    "first_name": "Jutta",
                    "middle_name": "",
                    "last_name": "Kray",
                    "name_suffix": "",
                    "institution": "Saarland University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27182/galley/16818/download/"
                }
            ]
        },
        {
            "pk": 27587,
            "title": "Agent’s symmetry elicits egocentric transformations for spatial perspective-taking",
            "subtitle": null,
            "abstract": "Spatial perspective-taking is an ability to understand in which direction an object is located relative to an agent (e.g.,another person or a chair). Previous studies showed that left/right judgments prompted an egocentric transformation strategy(i.e., mental rotation of the self) whereas front/behind judgments prompted other strategies (e.g., tracing a line of sight). Toexamine whether the symmetrical shape of an agent could affect the choice of strategies, we used as an agent a cuboid whichhas a prong on one of its sides. We labeled the prong side as the front (Experiment 1) or right (Experiment 2) of the agent,about which participants made left/right and front/behind judgments. The results revealed that egocentric transformations weremore favored for judgments about directions along symmetrical than asymmetrical axes of the agent, regardless of whether thejudgment was about left/right or front/behind. This suggests similar processing underlies left/right and front/behind judgments.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3nf4m9jv",
            "frozenauthors": [
                {
                    "first_name": "Hiroyuki",
                    "middle_name": "",
                    "last_name": "Muto",
                    "name_suffix": "",
                    "institution": "Osaka University",
                    "department": ""
                },
                {
                    "first_name": "Soyogu",
                    "middle_name": "",
                    "last_name": "Matsushita",
                    "name_suffix": "",
                    "institution": "Osaka University",
                    "department": ""
                },
                {
                    "first_name": "Kazunori",
                    "middle_name": "",
                    "last_name": "Morikawa",
                    "name_suffix": "",
                    "institution": "Osaka University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27587/galley/17223/download/"
                }
            ]
        },
        {
            "pk": 27613,
            "title": "Age-related top-down and bottom-up guidance on eye movements when searchingin real-world scenes",
            "subtitle": null,
            "abstract": "Efficient selection of targets is crucial in everyday activities across the lifespan. Studies reporting age-related declinehave, however, typically utilised arrays of simple, unrealistic objects. Using real-world scenes, we investigated how reliability ofscene semantics (consistent vs. inconsistent targets), target template specificity (name vs. precise picture) and target perceptualsalience influence oculomotor search behaviour in older vs. young viewers. Aging resulted in slower search considering initialsaccade latency, time and number of fixations to locate the target, and verification of object-template matching. No groupdifferences emerged in accuracy and in search facilitation due to a pictorial template or a semantically consistent target. Targethigh salience enhanced efficiency in both groups, with stronger effects in older viewers. Aging seems therefore to lead to anoverall search speed reduction not due to specific deficits in utilisation of scene semantic guidance or in target recognition, andpossibly reduced by enhancing target perceptual guidance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0kn582zv",
            "frozenauthors": [
                {
                    "first_name": "Hanane",
                    "middle_name": "",
                    "last_name": "Ramzaoui",
                    "name_suffix": "",
                    "institution": "Universit ́e Cˆote d’Azur",
                    "department": ""
                },
                {
                    "first_name": "Sylvane",
                    "middle_name": "",
                    "last_name": "Faure",
                    "name_suffix": "",
                    "institution": "Universit ́e Cˆote d’Azur",
                    "department": ""
                },
                {
                    "first_name": "Sara",
                    "middle_name": "",
                    "last_name": "Spotorno",
                    "name_suffix": "",
                    "institution": "University of Glasgow",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27613/galley/17249/download/"
                }
            ]
        },
        {
            "pk": 27353,
            "title": "Aging of the Exploring Mind: Older Adults Deviate more from Optimality inComplex Choice Environments",
            "subtitle": null,
            "abstract": "Older adults (OA) need to make many important and difficultdecisions. Often, there are too many options available to ex-plore exhaustively, creating the ubiquitous tradeoff betweenexploration and exploitation. How do OA make these com-plex tradeoffs? We investigated age-related shifts in solvingexploration-exploitation tradeoffs depending on the complex-ity of the choice environment. Participants played four andeight option bandit problems with numbers of gambles and av-erage rewards available on the screen. OA reliably performedworse in a more complex choice environment and were alsomore deviant from an optimality model (Thompson sampling),which keeps track of uncertainty beyond just the mean or lastreward. OA seem to process important information in morecomplex choice environments sub-optimally, suggesting lim-ited representations of future rewards. This interpretation fitsto multiple contexts in the complex cognitive aging literature,in particular to the context of challenges in the maintenance ofgoal-directed learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7tg5m4sm",
            "frozenauthors": [
                {
                    "first_name": "Job",
                    "middle_name": "J.",
                    "last_name": "Schepens",
                    "name_suffix": "",
                    "institution": "Freie Universit ̈at",
                    "department": ""
                },
                {
                    "first_name": "Ralph",
                    "middle_name": "",
                    "last_name": "Hertwig",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Wouter",
                    "middle_name": "",
                    "last_name": "van den Bos",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27353/galley/16989/download/"
                }
            ]
        },
        {
            "pk": 27221,
            "title": "A Hebbian account of entrenchment and (over)-extension in language learning",
            "subtitle": null,
            "abstract": "In production, frequently used words are preferentially\nextended to new, though related meanings. In comprehension,\nfrequent exposure to a word instead makes the learner\nconfident that all of the word’s legitimate uses have been\nexperienced, resulting in an entrenched form-meaning\nmapping between the word and its experienced meaning(s).\nThis results in a perception-production dissociation, where the\nforms speakers are most likely to map onto a novel meaning\nare precisely the forms that they believe can never be used\nthat way. At first glance, this result challenges the idea of\nbidirectional form-meaning mappings, assumed by all current\napproaches to linguistic theory. In this paper, we show that\nbidirectional form-meaning mappings are not in fact\nchallenged by this production-perception dissociation. We\nshow that the production-perception dissociation is expected\neven if learners of the lexicon acquire simple symmetrical\nform-meaning associations through simple Hebbian learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Hebbian learning; word learning; mental lexicon"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1854n0jh",
            "frozenauthors": [
                {
                    "first_name": "Vsevolod",
                    "middle_name": "",
                    "last_name": "Kapatsinski",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                },
                {
                    "first_name": "Zara",
                    "middle_name": "",
                    "last_name": "Harmon",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27221/galley/16857/download/"
                }
            ]
        },
        {
            "pk": 27249,
            "title": "A Hierarchical Bayesian Model of Individual Differencesin Memory for Emotional Expressions",
            "subtitle": null,
            "abstract": "When participants view and then reproduce simple objects thatvary along a continuous dimension such as length or shade, orwhen they view images of faces that vary in emotional expression,their estimates tend to be biased toward the average value of thepresented objects, a phenomenon that has been modeled as theresult of a Bayesian combination of prior category knowledge withan imprecise memory trace (Corbin, Crawford & Vavra, 2017;Huttenlocher, Hedges & Vevea, 2000). Whereas previous workdescribed a general cognitive strategy based on data aggregatedacross participants, here we examined individual differences instrategy. Thirty-six participants viewed and reproduced 496morphed face stimuli that ranged from angry to happy. We foundsubstantial variation in the bias patterns participants produced.Individuals’ estimates were well fit by a model that positedattraction toward three categories, one at the happy end of therange, one at the angry end, and one that captured the entire rangeof presented stimuli, and by allowing the weight given to eachcategory to vary by participant.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "category adjustment models; emotionmemory; emotion perception; face perception; individualdifferences; Bayesian modeling"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4fw6j383",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Landy",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "L.",
                    "middle_name": "Elizabeth",
                    "last_name": "Crawford",
                    "name_suffix": "",
                    "institution": "University of Richmond",
                    "department": ""
                },
                {
                    "first_name": "Jonathan",
                    "middle_name": "",
                    "last_name": "Corbin",
                    "name_suffix": "",
                    "institution": "University of Richmond",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27249/galley/16885/download/"
                }
            ]
        },
        {
            "pk": 26838,
            "title": "A hierarchical Bayesian model of “memory for when”based on experience sampling data",
            "subtitle": null,
            "abstract": "Participants wore a smartphone, which collected GPS, audio,accelerometry and image data, in a pouch around their necksfor a period of two weeks. After a retention interval of oneweek, they were asked to judge the specific day on whicheach of a selection of images was taken. To account forpeople’s judgements, we proposed a mixture model of fourprocesses - uniform guessing, a signal detection process basedon decaying memory strength, a week confusion process anda event confusion process in which the sensor streams wereused to calculate the similarity of events. A model selectionexercise testing all possible subsets of the processes favoureda model that included only the event confusion model. GPSsimilarities were found to be the most significant predictors,followed by audio and accelerometry similarities and thenimage similarities.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "memory"
                },
                {
                    "word": "experience sampling"
                },
                {
                    "word": "hierarchicalBayesian model"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5fq2b61h",
            "frozenauthors": [
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "Dennis",
                    "name_suffix": "",
                    "institution": "University of Newcastle",
                    "department": ""
                },
                {
                    "first_name": "Hyungwook",
                    "middle_name": "",
                    "last_name": "Yim",
                    "name_suffix": "",
                    "institution": "University of Newcastle",
                    "department": ""
                },
                {
                    "first_name": "Vishnu",
                    "middle_name": "",
                    "last_name": "Sreekumar",
                    "name_suffix": "",
                    "institution": "National Institutes of Health",
                    "department": ""
                },
                {
                    "first_name": "Nathan",
                    "middle_name": "J.",
                    "last_name": "Evans",
                    "name_suffix": "",
                    "institution": "University of Newcastle",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Garrett",
                    "name_suffix": "",
                    "institution": "University of Newcastle",
                    "department": ""
                },
                {
                    "first_name": "Per",
                    "middle_name": "",
                    "last_name": "Sederberg",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26838/galley/16474/download/"
                }
            ]
        },
        {
            "pk": 27206,
            "title": "Algebra is not like trivia:Evaluating self-assessment in an online math tutor",
            "subtitle": null,
            "abstract": "Appraising one’s own performance after a task, known as self-assessment, has been studied from a cognitive science perspec-tive in domains such as humor, trivia, and logic. Previous stud-ies have found that participants are systematically poor at judg-ing their own performance, though sometimes self-assessmentvaries based on actual performance. We explored calibrationof self-assessment on algebra problems, a domain where peo-ple have typically received explicit instruction. In this domain,we found that people do not behave as they do in other do-mains previously studied: they are generally well-calibrated injudging their algebra performance. This suggests that in thecourse of learning to solve algebra problems, people have alsolearned to accurately judge their performance, both absolutelyand relative to others.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "self-assessment; algebra; intelligent tutor; calibra-tion"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5x63k9d7",
            "frozenauthors": [
                {
                    "first_name": "Rachel",
                    "middle_name": "A.",
                    "last_name": "Jansen",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "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": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27206/galley/16842/download/"
                }
            ]
        },
        {
            "pk": 27291,
            "title": "A Longitudinal Study of Differences between Predicted, Actual, and Remembered\nPersonal ChangeLongitudinal Study of Differences between Predicted, Actual, and Remembered\nPersonal Change",
            "subtitle": null,
            "abstract": "We investigated people’s assessments of their own personal\nchange over time, comparing predicted, actual, and recalled\nchange in personality, values, and performance. On average,\nparticipants underestimated the absolute magnitude of their\npersonal change in both prediction and recall. However, people\nspecifically neglected negative future change, resulting in overly\noptimistic predictions of improvement. In contrast, recall of\npositive and negative change was relatively more balanced, such\nthat assessments of past improvement were better calibrated on\naverage. Our findings provide insight into how people think\nabout their own identity over time and address disparate theories\nin the literature regarding predictions of personal stability versus\nimprovement.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "self-perception; social cognition; future self; past\nself; identity; time; personal change"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/30f3s1hf",
            "frozenauthors": [
                {
                    "first_name": "Sarah",
                    "middle_name": "",
                    "last_name": "Molouki",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "M.",
                    "last_name": "Bartels",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Oleg",
                    "middle_name": "",
                    "last_name": "Urminsky",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27291/galley/16927/download/"
                }
            ]
        },
        {
            "pk": 27452,
            "title": "Alternation blindness in the perception of binary sequences",
            "subtitle": null,
            "abstract": "Binary information is prevalent in the environment. In this\nstudy, we examined how people process repetition and\nalternation in binary sequences. Across four paradigms\ninvolving estimation, working memory, change detection, and\nvisual search, we found that the number of alternations is\nunder-estimated compared to repetitions (Experiment 1).\nMoreover, recall for binary sequences deteriorates as the\nsequence alternates more (Experiment 2). Changes in bits are\nalso harder to detect as the sequence alternates more\n(Experiment 3). Finally, visual targets superimposed on bits\nof a binary sequence take longer to process as alternation\nincreases (Experiment 4). Overall, our results indicate that\ncompared to repetition, alternation in a binary sequence is\nless salient in the sense of requiring more attention for\nsuccessful encoding. The current study thus reveals the\ncognitive constraints in the representation of alternation and\nprovides a new explanation for the over-alternation bias in\nrandomness perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "alternation bias"
                },
                {
                    "word": "randomness perception"
                },
                {
                    "word": "working\nmemory"
                },
                {
                    "word": "attention"
                },
                {
                    "word": "numerosity perception"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4x13w18w",
            "frozenauthors": [
                {
                    "first_name": "Ru",
                    "middle_name": "Qi",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "University of British Columbia",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Osherson",
                    "name_suffix": "",
                    "institution": "Princeton University",
                    "department": ""
                },
                {
                    "first_name": "Jiaying",
                    "middle_name": "",
                    "last_name": "Zhao",
                    "name_suffix": "",
                    "institution": "University of British Columbia",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27452/galley/17088/download/"
                }
            ]
        },
        {
            "pk": 27424,
            "title": "Altruist vs Egoist Detection and Individual vs Group Selection\nin Personnel Management",
            "subtitle": null,
            "abstract": "In the Wason-Selection Task debate it has been suggested that\npeople may be able to detect cheaters but not co-operators or\naltruists. This position has been challenged. Here we focus on\na scenario that is more ecologically valid with regard to\ndifferent strategies for detecting workers who negatively\ninteract with others (here ‘egoists’) and positive interactors\n(here ‘altruist’). The results on altruist detection in two-level\npersonnel evaluation tasks (T-PETs), with information on\nindividual and team performance, suggested a disregard of the\nteam performance and a resulting “Tragedy of Personnel\nEvaluation”. Experiment 1 transfers the idea of altruist\ndetection in a personnel evaluation and personnel selection\ntask (von Sydow & Braus, 2016) to egoist detection and\nexplores whether there are analogous problems for egoist\ndetection. Experiment 2 explores egoist and altruist detection\nin more realistic settings where individual and group-selection\nmay affect our sampling of the interactor.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Altruist/Egoist Detection; Wason Selection Task;\nPersonal Selection Task; Tragedy of Personnel Selection;\nGroup Selection; Learning Correlations; Decision Making"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/13k4v7wq",
            "frozenauthors": [
                {
                    "first_name": "Momme",
                    "middle_name": "",
                    "last_name": "von Sydow",
                    "name_suffix": "",
                    "institution": "University of Munich",
                    "department": ""
                },
                {
                    "first_name": "Niels",
                    "middle_name": "",
                    "last_name": "Braus",
                    "name_suffix": "",
                    "institution": "University of Heidelberg",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27424/galley/17060/download/"
                }
            ]
        },
        {
            "pk": 27223,
            "title": "A Meta-Analysis of the Joint Simon Effect",
            "subtitle": null,
            "abstract": "Since its design in 2003, the joint Simon task and corollaryjoint Simon effect (JSE) have been invaluable tools towardsthe study of joint action and the understanding of howindividuals represent the action/task of a co-actor. Thepurpose of this meta-analysis was to systematically andquantitatively review the sizeable behavioural evidence forthe JSE. Google Scholar was used to identify studies citingthe first report of the joint Simon task (Sebanz, Knoblich, &Prinz, 2003) up until June 23, 2015. After screening, thirty-nine manuscripts were included in the meta-analysis, thirteenof which included individual go/no-go (IGNG) control data.Separate random-effects models were conducted for both thejoint Simon and IGNG datasets, and meta-regression modelswere used to assess potential moderators that may impact thestrength of the JSE. The results provide an importantquantitative summary of the literature and serve as afoundation for future research surrounding the JSE.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "joint action; spatial compatibility; co-representation"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9bf4n967",
            "frozenauthors": [
                {
                    "first_name": "April",
                    "middle_name": "",
                    "last_name": "Karlinsky",
                    "name_suffix": "",
                    "institution": "University of British Columbia",
                    "department": ""
                },
                {
                    "first_name": "Keith",
                    "middle_name": "R.",
                    "last_name": "Lohse",
                    "name_suffix": "",
                    "institution": "Auburn University",
                    "department": ""
                },
                {
                    "first_name": "Melanie",
                    "middle_name": "Y.",
                    "last_name": "Lam",
                    "name_suffix": "",
                    "institution": "St. Francis Xavier University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27223/galley/16859/download/"
                }
            ]
        },
        {
            "pk": 27391,
            "title": "A Minimal Neural Network Model of The Gambler’s Fallacy",
            "subtitle": null,
            "abstract": "The gambler’s fallacy has been a notorious showcase of humanirrationality in probabilistic reasoning. Recent studies suggestthe neural basis of this fallacy might have originated from thepredictive learning by neuron populations over the latent tem-poral structures of random sequences, particularly due to thestatistics of pattern times and the precedence odds betweenpatterns. Here we present a biologically-motivated minimalneural network model with only eight neurons. Through unsu-pervised training, the model naturally develops a bias towardalternation patterns over repetition patterns, even when bothpatterns are equally likely presented to the model. Our analysessuggest that the way the neocortex integrates information overtime makes the neuron populations not only sensitive to thefrequency signals but also relational structures embedded overtime. Moreover, we offer an explanation for how higher-levelcognitive biases may have an early start at the level of sensoryprocessing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "gambler’s fallacy; alternation bias; waiting time;temporal integration; predictive learning."
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4t18m9s9",
            "frozenauthors": [
                {
                    "first_name": "Yanlong",
                    "middle_name": "",
                    "last_name": "Sun",
                    "name_suffix": "",
                    "institution": "Texas A&M University Health Science Center",
                    "department": ""
                },
                {
                    "first_name": "Hongbin",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "Texas A&M University Health Science Center",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27391/galley/17027/download/"
                }
            ]
        },
        {
            "pk": 27342,
            "title": "A Model-based Approach for Assessing Attentional Biases in People with Depressive\nSymptoms",
            "subtitle": null,
            "abstract": "Biased attention is assumed to play an important role in the\netiology and maintenance of depression and depressive\nsymptoms. In this paper, we used data from a categorization\ntask and an associated model to assess the attentional bias of\npeople with varying levels of depressive symptoms.\nAttentional bias was operationalized as the parameter estimate\nin a prototype model of categorization. For estimation, we used\na Bayesian hierarchical mixture approach. We expected to find\na positive correlation between depressive symptoms and an AB\nfor negative material and a negative correlation between\ndepressive symptoms and a bias toward positive material.\nDespite good model fit, Bayesian regression analyses revealed\nweak or moderate evidence in favor of the null model assuming\nno association between attentional preferences and depressive\nsymptoms, both for negative and positive material.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "psychology; cognitive science ; attention; concepts\nand categories; Bayesian modeling; mood disorder"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0js9x745",
            "frozenauthors": [
                {
                    "first_name": "Isa",
                    "middle_name": "",
                    "last_name": "Rutten",
                    "name_suffix": "",
                    "institution": "University of Leuven",
                    "department": ""
                },
                {
                    "first_name": "Wouter",
                    "middle_name": "",
                    "last_name": "Voorspoels",
                    "name_suffix": "",
                    "institution": "KU Leuven",
                    "department": ""
                },
                {
                    "first_name": "Ernst",
                    "middle_name": "H.W.",
                    "last_name": "Koster",
                    "name_suffix": "",
                    "institution": "Ghent University",
                    "department": ""
                },
                {
                    "first_name": "Wolf",
                    "middle_name": "",
                    "last_name": "Vanpaemel",
                    "name_suffix": "",
                    "institution": "KU Leuven",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27342/galley/16978/download/"
                }
            ]
        },
        {
            "pk": 26891,
            "title": "A modeling link between cognitive and biological homeostasis",
            "subtitle": null,
            "abstract": "The problem of stability has long been a limiting factor in de-veloping neural networks that can grow in size and complex-ity. Outside of particular, narrow parameter ranges, changesin activity can easily result in total loss of control. Humancognition must have reliable means of acting to stay withinthe stable ranges of sensitivity and activation. Learning is onesuch mechanism, and population dynamics are another. Here,we focus on another, often overlooked stability mechanism:cellular homeostasis through metabolism dynamics. We ran avisual change detection experiment designed to strain networkstability while minimizing any learnable patterns. We fit thedata using models with and without cellular energy levels as afactor, finding that the model influenced by its past history ofenergy use was a closer fit to the human data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Homeostasis; attention; visual change detection;neural modeling"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0r4095g1",
            "frozenauthors": [
                {
                    "first_name": "Gavin",
                    "middle_name": "",
                    "last_name": "Jenkins",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                },
                {
                    "first_name": "Jordan",
                    "middle_name": "",
                    "last_name": "Barnes",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Tupper",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                },
                {
                    "first_name": "Mark",
                    "middle_name": "",
                    "last_name": "Blair",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26891/galley/16527/download/"
                }
            ]
        },
        {
            "pk": 27667,
            "title": "A model of cultural co-evolution of language and mindreading",
            "subtitle": null,
            "abstract": "Language requires mindreading for entertaining communicative intentions, and mindreading in turn profits fromlanguage as a means for sharing mental states. Hence it has been hypothesised that the two skills have co-evolved.We present a Bayesian agent-based model to formalise this hypothesis. This model combines referential signalling withmental states, such that a speaker’s topic choice is probabilistically dependent on their perspective on the world. In order tolearn the language, a learner has to simultaneously infer the speaker’s lexicon and perspective. Learners can solve this task bybootstrapping one with the other, but only if the speaker uses an informative language.We will present results of an iterated learning version of this model, showing that selection on communication results inthe emergence of a fully informative lexicon from scratch. However, selection on perspective-taking alone also results in theemergence of partially-informative lexicons, which is sufficient for inferring others’ perspectives.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0p75885r",
            "frozenauthors": [
                {
                    "first_name": "Marieke",
                    "middle_name": "",
                    "last_name": "Woensdregt",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "Kirby",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Cummins",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Kenny",
                    "middle_name": "",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27667/galley/17303/download/"
                }
            ]
        },
        {
            "pk": 26845,
            "title": "A Model of Event Knowledge",
            "subtitle": null,
            "abstract": "We present a connectionist model of event knowledge that istrained on examples of sequences of activities that are notexplicitly labeled as events. The model learns co-occurrencepatterns among the components of activities as they occur inthe moment (entities, actions, and contexts), and also learns topredict sequential patterns of activities. In so doing, the modeldisplays behaviors that in humans have been characterized asexemplifying inferencing of unmentioned event components,the prediction of upcoming components (which may or maynot ever happen or be mentioned), reconstructive memory,and the ability to flexibly accommodate novel variations frompreviously encountered experiences. All of these behaviorsemerge from what the model learns.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "events; schema; scripts; prediction; recurrentconnectionist model"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1nh6g2xm",
            "frozenauthors": [
                {
                    "first_name": "Jeffrey",
                    "middle_name": "L.",
                    "last_name": "Elman",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                },
                {
                    "first_name": "Ken",
                    "middle_name": "",
                    "last_name": "McRae",
                    "name_suffix": "",
                    "institution": "Social Science Centre London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26845/galley/16481/download/"
                }
            ]
        },
        {
            "pk": 27330,
            "title": "A model of structure learning, inference, and generation for scene understanding",
            "subtitle": null,
            "abstract": "Humans possess rich knowledge of the structure of the world, including co-occurrences among entities, and co-variation among their discrete and continuous features. But how people learn, infer and predict this structure is not wellunderstood. Here we explore everyday scene understanding as a case study of people’s structural knowledge and reasoning.We introduce a probabilistic model over scene graphs that can learn the relational structure of objects and their arrangementsand support inference and generation. Our model was able to learn the underlying structure of real-world scenes, and use it forinference and compression. In two human psychophysical experiments we found that a corresponding computational cognitivemodel was able to explain how people learn novel scene distributions and use it for classification and construction. Our workrepresents the first computational theory of human scene understanding that can account for people’s rich capacity for learningand reasoning about structure.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6420j6pn",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Raposo",
                    "name_suffix": "",
                    "institution": "DeepMind",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Dayan",
                    "name_suffix": "",
                    "institution": "Gatsby Computational Neuroscience Unit",
                    "department": ""
                },
                {
                    "first_name": "Demis",
                    "middle_name": "",
                    "last_name": "Hassabis",
                    "name_suffix": "",
                    "institution": "DeepMind",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Battaglia",
                    "name_suffix": "",
                    "institution": "DeepMind",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27330/galley/16966/download/"
                }
            ]
        },
        {
            "pk": 27135,
            "title": "Amortized Hypothesis Generation",
            "subtitle": null,
            "abstract": "Bayesian models of cognition posit that people compute prob-ability distributions over hypotheses, possibly by construct-ing a sample-based approximation. Since people encountermany closely related distributions, a computationally efficientstrategy is to selectively reuse computations – either the sam-ples themselves or some summary statistic. We refer to thesereuse strategies as amortized inference. In two experiments,we present evidence consistent with amortization. When se-quentially answering two related queries about natural scenes,we show that answers to the second query vary systematicallydepending on the structure of the first query. Using a cog-nitive load manipulation, we find evidence that people cachesummary statistics rather than raw sample sets. These resultsenrich our notions of how the brain approximates probabilisticinference.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Amortization; hypothesis generation; Bayesian in-ference; Monte Carlo methods"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6cc8954w",
            "frozenauthors": [
                {
                    "first_name": "Ishita",
                    "middle_name": "",
                    "last_name": "Dasgupta",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Schulz",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Noah",
                    "middle_name": "D.",
                    "last_name": "Goodman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Samuel",
                    "middle_name": "J.",
                    "last_name": "Gershman",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27135/galley/16771/download/"
                }
            ]
        },
        {
            "pk": 27074,
            "title": "Analogical Abstraction in Three-Month-Olds",
            "subtitle": null,
            "abstract": "This research tests whether analogical processing ability is\npresent in 3-month-old infants. Infants are habituated to a series\nof analogous pairs, instantiating either same (e.g., AA, BB,\netc.) or different (e.g., AB, CD, etc.), and then tested with\nfurther exemplars of the relations. If they can distinguish the\nfamiliar relation from the novel relation, even with new\nobjects, this is evidence that for analogical abstraction across\nthe study pairs. In Experiment 1, we did not find evidence of\nanalogical abstraction when 3-month-olds were habituated to\nsix pairs instantiating the relation. However, in Experiment 2,\ninfants showed evidence of analogical abstraction after\nhabituation to two alternating pairs (e.g., AA, BB, AA, BB...).\nFurther, as with older groups, rendering individual objects\nsalient disrupted relational learning. These results demonstrate\nthat 3-month-old infants are capable of analogical comparison\nand abstraction. Our findings also place limits on the conditions\nunder which these processes are likely to occur. We discuss\nimplications for theories of relational learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Development"
                },
                {
                    "word": "relational processing"
                },
                {
                    "word": "Infants"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3748q8vn",
            "frozenauthors": [
                {
                    "first_name": "Erin",
                    "middle_name": "M.",
                    "last_name": "Anderson",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Yin-Juei",
                    "middle_name": "",
                    "last_name": "Chang",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Susan",
                    "middle_name": "J.",
                    "last_name": "Hespos",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Dedre",
                    "middle_name": "",
                    "last_name": "Gentner",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27074/galley/16710/download/"
                }
            ]
        },
        {
            "pk": 26828,
            "title": "Analogical gestures foster understanding of causal systems",
            "subtitle": null,
            "abstract": "Sensitivity to the causal structure underlying phenomena iscritical to expert understanding. Fostering such understandingin learners is therefore a key goal in education. Wehypothesized that observing analogical gestures—whichrepresent relational information in visuospatial format—would lead learners to notice and reason about underlyingcausal patterns, such as positive and negative feedback.Participants watched brief video lectures about the humanbody and the plant kingdom, which were delivered along withgestures representing either: 1) visuospatial details (iconicgesture condition); or 2) relational structure (analogicalgesture condition). In a subsequent classification task, relativeto participants who saw iconic gestures, participants who sawanalogical gestures were more likely to sort the phenomenadescribed in the videos—as well as novel phenomena—bytheir causal structure (e.g., positive feedback). The resultssuggest that analogical gestures can be harnessed to fostercausal understanding.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "analogy; relational reasoning; gesture; learning;complex systems"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/58n6v5r6",
            "frozenauthors": [
                {
                    "first_name": "Kensy",
                    "middle_name": "",
                    "last_name": "Cooperrider",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Dedre",
                    "middle_name": "",
                    "last_name": "Gentner",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Susan",
                    "middle_name": "",
                    "last_name": "Goldin-Meadow",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26828/galley/16464/download/"
                }
            ]
        },
        {
            "pk": 26939,
            "title": "Analogical Inferences in Causal Systems",
            "subtitle": null,
            "abstract": "Analogical and causal reasoning theories both seek to explainpatterns of inductive inference. Researchers have claimed thatreasoning scenarios incorporating aspects of both analogicalcomparison and causal thinking necessitate a new model of in-ductive inference (Holyoak, Lee, & Lu, 2010; Lee & Holyoak,2008). This paper takes an opposing position, arguing that fea-tures of analogical models make correct claims about infer-ence patterns found among causal analogies, including analo-gies with both generative and preventative relations. Experi-ment 1 demonstrates that analogical inferences for these kindsof causal systems can be explained by alignment of relationalstructure, including higher-order relations. Experiment 2 fur-ther demonstrates that inferences strengthened by matchinghigher-order relations are not guided by the transfer of prob-abilistic information about a cause from base to target. Weconclude that causal analogies behave like analogies in gen-eral—analogical mapping provides candidate inferences whichcan then be reasoned about in the target.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "analogy; causality; structure mapping theory; in-ductive inferences"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9cq5c1r7",
            "frozenauthors": [
                {
                    "first_name": "Matthew",
                    "middle_name": "",
                    "last_name": "Myers",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Dedre",
                    "middle_name": "",
                    "last_name": "Gentner",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26939/galley/16575/download/"
                }
            ]
        },
        {
            "pk": 27248,
            "title": "Analogies Emerge from Learning Dyamics in Neural Networks",
            "subtitle": null,
            "abstract": "When a neural network is trained on multiple analogous tasks,previous research has shown that it will often generate rep-resentations that reflect the analogy. This may explain thevalue of multi-task training, and also may underlie the powerof human analogical reasoning – awareness of analogies mayemerge naturally from gradient-based learning in neural net-works. We explore this issue by generalizing linear analysistechniques to explore two sets of analogous tasks, show thatanalogical structure is commonly extracted, and address somepotential implications.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "neural networks; structure learning; representa-tion; analogy; transfer;"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5s8259wx",
            "frozenauthors": [
                {
                    "first_name": "Andrew",
                    "middle_name": "",
                    "last_name": "Lampinen",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Shaw",
                    "middle_name": "",
                    "last_name": "Hsu",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "James",
                    "middle_name": "L.",
                    "last_name": "McClelland",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27248/galley/16884/download/"
                }
            ]
        },
        {
            "pk": 27050,
            "title": "Analogy and Episodic Memory to Support Domain Learning in a CognitiveArchitecture: An Exploration",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "analogy"
                },
                {
                    "word": "cognitive architecture"
                },
                {
                    "word": "CognitiveSimulation"
                }
            ],
            "section": "Talks: Publication-Based",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5ts8x287",
            "frozenauthors": [
                {
                    "first_name": "Kenneth",
                    "middle_name": "D.",
                    "last_name": "Forbus",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27050/galley/16686/download/"
                }
            ]
        },
        {
            "pk": 27113,
            "title": "Analytic Causal Knowledge for Constructing Useable Empirical Causal Knowledge:Two Experiments on Preschoolers",
            "subtitle": null,
            "abstract": "The present paper examines what domain-general causalknowledge reasoners need for at least some outcome-variabletypes to construct useable content-specific causal knowledge.In particular, it explains why it is essential to have analyticknowledge of causal-invariance integration functions:knowledge for predicting the expected outcome assuming thatthe empirical knowledge acquired regarding a causal relationholds across the learning context and an application context.The paper reports two studies that support the hypothesis thatpreschool children have such knowledge regarding binarycauses and effects, enabling them to generalize acrosscontexts rationally, favoring the causal-invariance hypothesisover alternative hypotheses, including interaction (e.g., linear)integration functions, heuristics, and biases.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Causal induction; causal learning; causalinvariance"
                },
                {
                    "word": "rationality; cognitive development"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7wn6j5dz",
            "frozenauthors": [
                {
                    "first_name": "Patricia",
                    "middle_name": "W.",
                    "last_name": "Cheng",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Mimi",
                    "middle_name": "",
                    "last_name": "Liljeholm",
                    "name_suffix": "",
                    "institution": "University of California, Irvine",
                    "department": ""
                },
                {
                    "first_name": "Catherine",
                    "middle_name": "M.",
                    "last_name": "Sandhofer",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27113/galley/16749/download/"
                }
            ]
        },
        {
            "pk": 26921,
            "title": "An automatic method for discovering rational heuristics for risky choice",
            "subtitle": null,
            "abstract": "What is the optimal way to make a decision given that yourtime is limited and your cognitive resources are bounded? Toanswer this question, we formalized the bounded optimal de-cision process as the solution to a meta-level Markov deci-sion process whose actions are costly computations. We ap-proximated the optimal solution and evaluated its predictionsagainst human choice behavior in the Mouselab paradigm,which is widely used to study decision strategies. Our compu-tational method rediscovered well-known heuristic strategiesand the conditions under which they are used, as well as novelheuristics. A Mouselab experiment confirmed our model’smain predictions. These findings are a proof-of-concept thatoptimal cognitive strategies can be automatically derived as therational use of finite time and bounded cognitive resources.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision-Making; Heuristics; Bounded Rational-ity; Strategy Selection; Rational Metareasoning"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/721295xk",
            "frozenauthors": [
                {
                    "first_name": "Falk",
                    "middle_name": "",
                    "last_name": "Lieder",
                    "name_suffix": "",
                    "institution": "University of California Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "M.",
                    "last_name": "Krueger",
                    "name_suffix": "",
                    "institution": "University of California Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L.",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "University of California Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26921/galley/16557/download/"
                }
            ]
        },
        {
            "pk": 27485,
            "title": "ANCHORING is amodal: evidence from a signed language.",
            "subtitle": null,
            "abstract": "Modern linguistic theory posits the existence of universal constraints. But whether these constraints concern lan-guage structure, generally, or speech, specifically, is unknown. To address this question, here we ask whether the constraintsidentified in spoken languages transfer to sign languages. ANCHORING (McCarthy & Prince, 1993) is a putatively universalconstraint on reduplication. ANCHORING requires that the final element of a suffixed reduplicant match the final element ofthe base (e.g., pana ‘chase’––>panana, ‘run’ not panapa). Here, we examine whether ANCHORING is likewise operative in asigned language. In our experiments, native ASL signers rated novel reduplicated forms: either ones consistent or inconsistentwith ANCHORING (i.e., ABB vs. ABA, where A and B are syllables). Results showed that signers reliably favored ABB formsover ABA. These findings show for the first time that ANCHORING constrains a sign language. This conclusion is consistentwith the existence of amodal linguistic principles.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9029f7xg",
            "frozenauthors": [
                {
                    "first_name": "Qatherine",
                    "middle_name": "",
                    "last_name": "Dana",
                    "name_suffix": "",
                    "institution": "Northeastern University",
                    "department": ""
                },
                {
                    "first_name": "Diane",
                    "middle_name": "",
                    "last_name": "Brentari",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Outi",
                    "middle_name": "",
                    "last_name": "Bat-El",
                    "name_suffix": "",
                    "institution": "Tel-Aviv University",
                    "department": ""
                },
                {
                    "first_name": "Iris",
                    "middle_name": "",
                    "last_name": "Berent",
                    "name_suffix": "",
                    "institution": "Northeastern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27485/galley/17121/download/"
                }
            ]
        },
        {
            "pk": 27153,
            "title": "A Neural Network Model for Taxonomic Responding with Realistic Visual Inputs",
            "subtitle": null,
            "abstract": "We propose a neural network model that accounts for the emer-gence of the taxonomic constraint in early word learning. Ourproposal is based on Mayor and Plunkett (2010)’s neurocom-putational model of the taxonomic constraint and overcomesone of its limitations, namely the fact that it considers arti-ficially built, simplified stimuli. In fact, while in the originalmodel the visual stimuli are random, sparse dot patterns, in ourproposed solution they are photographic images from the Im-ageNet database. In our model the represented objects in theimage can be of different size, color, location in the picture,point of view, etc.. We show that, notwithstanding the aug-mented complexity in the input, the proposed model comparesfavorably with respect to Mayor and Plunkett (2010)’s model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1vg4s7j2",
            "frozenauthors": [
                {
                    "first_name": "Giorgia",
                    "middle_name": "",
                    "last_name": "Fenoglio",
                    "name_suffix": "",
                    "institution": "University of Torino",
                    "department": ""
                },
                {
                    "first_name": "Roberto",
                    "middle_name": "",
                    "last_name": "Esposito",
                    "name_suffix": "",
                    "institution": "University of Torino",
                    "department": ""
                },
                {
                    "first_name": "Valentina",
                    "middle_name": "",
                    "last_name": "Gliozzi",
                    "name_suffix": "",
                    "institution": "University of Torino",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27153/galley/16789/download/"
                }
            ]
        },
        {
            "pk": 27489,
            "title": "A Neurodynamical Model of How Prior Knowledge Influences Visual Perception",
            "subtitle": null,
            "abstract": "Recent behavioral studies showed that prior knowledge can directly influence visual perception. In the current work,we offer an explanation of the observed findings based on the adaptive resonance theory (ART). The ART neural network wasdesigned to solve the problem of catastrophic forgetting during learning in non-stationary environment. In the ART, stability oflearning is achieved by matching bottom-up sensory signals with top-down expectations. Resonant state that corresponds withconscious perception develops in the network when the bottom-up and top-down signals are closely aligned. On the other hand,mismatch produces global reset signal that clears the traces of erroneous top-down expectations. Therefore, prior knowledge caninfluence conscious perception only when it already closely matches with sensory signals. We performed computer simulationswith real-time implementation of the ART circuit that confirm our analysis. Simulations also showed how observed behavioralfindings arise from response bias.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/19n7r359",
            "frozenauthors": [
                {
                    "first_name": "Draˇzen",
                    "middle_name": "",
                    "last_name": "Domijan",
                    "name_suffix": "",
                    "institution": "University of Rijeka",
                    "department": ""
                },
                {
                    "first_name": "Mateja",
                    "middle_name": "",
                    "last_name": "Mari ́",
                    "name_suffix": "",
                    "institution": "University of Rijeka",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27489/galley/17125/download/"
                }
            ]
        },
        {
            "pk": 27199,
            "title": "A New Model of Statistical Learning: Trajectories Through Perceptual Similarity Space",
            "subtitle": null,
            "abstract": "Existing models of statistical learning involve computation ofconditional probabilities over discrete, categorical items in asequence. We propose an alternative view that learning occursthrough a process of tracking changes along physicaldimensions from one stimulus to the next within a “perceptualsimilarity space.” To test this alternative, we examined asituation where it is difficult or impossible to label stimuli inreal time, and where the two assumptions lead to conflictinghypotheses. We conducted two experiments in which humanparticipants passively listened to a familiarization sequence offrequency-modulated tones and were then asked to makefamiliarity judgments on a series of test bigrams. Behavioralresults were broadly consistent with a conceptualization oflearning as tracking trajectories through perceptual similarityspace. We also trained a neural network that codes stimuli asvalues along two continuous dimensions to predict the nextstimulus given the current stimulus, and show that it capturedkey features of the human data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "statistical learning; similarity space; connectionistmodeling"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2746p388",
            "frozenauthors": [
                {
                    "first_name": "Elizabeth",
                    "middle_name": "A.",
                    "last_name": "Hutton",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Felix",
                    "middle_name": "Hao",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                },
                {
                    "first_name": "Jason",
                    "middle_name": "D.",
                    "last_name": "Zevin",
                    "name_suffix": "",
                    "institution": "University of Southern California",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27199/galley/16835/download/"
                }
            ]
        },
        {
            "pk": 27598,
            "title": "An Exploratory Study of the Influence of Pretend Play on Children’sSelf-Regulation and Language Skills",
            "subtitle": null,
            "abstract": "Recently, there has been increased interest regarding how pretend play contributes to children’s cognitive develop-ment. This study examines the efficacy of a pretend play intervention on self-regulation and language skills of 4- to 5-year-oldsand explores parents’ perceptions about children’s engagement in pretend play. The small-scale intervention includes eight 30-minute sessions over 6 weeks, in groups of five children. Each session included: (1) shared storybook reading; (2) role-playing;and (3) review. During shared story-book reading the children were read two books with explicit phonological awareness andvocabulary instruction for 18 words in each book. Role-playing included providing the children with props, which allow forengagement in pretend play activities. Several measures were used pre- and post-intervention to evaluate children’s self- reg-ulation and language skills. The improvements that occurred in the intervention are considered alongside other cognitive andeducational factors to better understand the role of pretend play in educational settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7486k3qw",
            "frozenauthors": [
                {
                    "first_name": "Tanya",
                    "middle_name": "",
                    "last_name": "Paes",
                    "name_suffix": "",
                    "institution": "University of Cambridge",
                    "department": ""
                },
                {
                    "first_name": "Michelle",
                    "middle_name": "",
                    "last_name": "Ellefson",
                    "name_suffix": "",
                    "institution": "University of Cambridge",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27598/galley/17234/download/"
                }
            ]
        },
        {
            "pk": 27528,
            "title": "An Exploratory Study on Remote Associates Problem Solving: Evidence of EyeMovement Indicators",
            "subtitle": null,
            "abstract": "Remote associates problems (RAP) have been widely used to measure creative processes. However, studies haverarely explored the RAP processes. The main purpose of this study was to record eye movements while solving RAP. Theresults show that: (1) The mean fixation duration increases throughout the problem-solving process, which indicates that moreproblem solvers encounter impasses. This result supports the “impasse encounter” phase of insight. (2) During the initial periodof problem solving, individuals display more regression counts in the fixation region than in the key region, which supportsthat the impasses are caused by inappropriate initial representation. (3) During the middle period of the process, the timeindividuals spend gazing at the key region increases, while the time spend at the fixation region decreases. This supports the“impasse resolution and insight” phase of insight.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/59529482",
            "frozenauthors": [
                {
                    "first_name": "Po-Sheng",
                    "middle_name": "",
                    "last_name": "Huang",
                    "name_suffix": "",
                    "institution": "Hsuan Chuang University",
                    "department": ""
                },
                {
                    "first_name": "Shu-Ling",
                    "middle_name": "",
                    "last_name": "Peng",
                    "name_suffix": "",
                    "institution": "National Cheng Kung Univeristy",
                    "department": ""
                },
                {
                    "first_name": "Jon-Fan",
                    "middle_name": "",
                    "last_name": "Hu",
                    "name_suffix": "",
                    "institution": "National Cheng Kung Univeristy",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27528/galley/17164/download/"
                }
            ]
        },
        {
            "pk": 27532,
            "title": "An fNIRS Hyperscanning Study on Brain-Brain Interactions of a Dyad during aJoint Sentence Reading Task",
            "subtitle": null,
            "abstract": "Existing studies in cognitive neuroscience predominantly focus on a single participant’s behavioral and brain re-sponses. Lack of an interactive context for joint action particularly limited social neuroscience studies to simulated socialcontexts. Advances in portable brain imaging technologies have made it practical to simultaneously monitor the brain activityof two or more people in an interactive context to investigate neural correlates of social interaction. In this study, the rela-tionship between behavioral synchrony and inter-brain coherence is investigated during simultaneous reading of matching andmismatching sentences in different auditory conditions. A dual-fNIRS hyperscanning setup was used to obtain simultaneousrecordings of hemodynamic activity from the prefrontal cortices of the participants while they jointly read-aloud the sentencesdisplayed on their screens. The results suggest that the level of inter-brain coherence in the right superior cortex tends toincrease depending on the level of behavioral synchrony among the participants.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3sd502kk",
            "frozenauthors": [
                {
                    "first_name": "Erdinc",
                    "middle_name": "",
                    "last_name": "Isbilir",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                },
                {
                    "first_name": "Murat",
                    "middle_name": "Perit",
                    "last_name": "Cakir",
                    "name_suffix": "",
                    "institution": "Middle East Technical University",
                    "department": ""
                },
                {
                    "first_name": "Fred",
                    "middle_name": "",
                    "last_name": "Cummins",
                    "name_suffix": "",
                    "institution": "University College Dublin",
                    "department": ""
                },
                {
                    "first_name": "Hasan",
                    "middle_name": "",
                    "last_name": "Ayaz",
                    "name_suffix": "",
                    "institution": "Drexel University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27532/galley/17168/download/"
                }
            ]
        },
        {
            "pk": 27666,
            "title": "An immersive binaural horizon for sonic data analytics",
            "subtitle": null,
            "abstract": "Accessible data analytics—that can be experienced through vision, hearing, and touch—poses a challenge to in-teraction design. It is also a human rights requirement because many societies mandate that all individuals have the right toexperience products and services, yet not every individual accesses media visually. As more data is presented through visual-ization, accessibility for populations who do not access data through vision decreases.Guidelines that claim to make visual media accessible through text fail to translate the iconic properties of visual shapes, thussubtracting affordances for pattern recognition. Non-linguistic sonication can be a means for non-visual pattern recognition.Hearing is optimized for detecting locations on a horizontal plane, and our approach for presenting data analytics recruitsthis optimization by using an immersive binaural horizontal plane. We will demonstrate our approach via two case studies: Asonic translation of a map and a sonic translation of a computational fluid dynamics simulation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5s02t2vx",
            "frozenauthors": [
                {
                    "first_name": "Richard",
                    "middle_name": "",
                    "last_name": "Windeyer",
                    "name_suffix": "",
                    "institution": "OCAD University",
                    "department": ""
                },
                {
                    "first_name": "Dan",
                    "middle_name": "",
                    "last_name": "MacDonald",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Steinman",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Ambrose",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "OCAD University",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Coppin",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27666/galley/17302/download/"
                }
            ]
        },
        {
            "pk": 26934,
            "title": "An incremental information-theoretic buffer supports sentence processing",
            "subtitle": null,
            "abstract": "People have the capability to process text three times fasterthan they would naturally read it, yet many current theories ofsentence processing rely on natural reading times as a proxyfor processing difficulty. How can people read material soquickly in spite of information processing limitations sug-gested by sentence processing theories? One possibility is thatsurprisal effects on reading time, the hallmark of processingdifficulty under sentence processing theories, might arise fromperceptual processing, implying no relation between surprisaland sentence processing difficulty. In this paper, we conducteda novel self-paced rapid serial visual presentation (RSVP) ex-periment, which controlled perceptual processes to probe forsentence processing related surprisal effects. We further testedhow readers might compensate for information processing lim-its during RSVP. We find support for sentence processing re-lated surprisal effects, the pattern of which is consistent with aFirst-In, First-Out (FIFO) buffer model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "language processing; linguistic memory; RSVP"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/86g6r9nr",
            "frozenauthors": [
                {
                    "first_name": "Francis",
                    "middle_name": "",
                    "last_name": "Mollica",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "T.",
                    "last_name": "Piantadosi",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26934/galley/16570/download/"
                }
            ]
        },
        {
            "pk": 26929,
            "title": "An information-seeking account of eye movements during spoken and signedlanguage comprehension",
            "subtitle": null,
            "abstract": "Language comprehension in grounded contexts involves in-tegrating visual and linguistic information through decisionsabout visual fixation. But when the visual signal also con-tains information about the language source – as in the caseof written text or sign language – how do we decide where tolook? Here, we hypothesize that eye movements during lan-guage comprehension represent an adaptive response. Usingtwo case studies, we show that, compared to English-learners,young signers delayed their gaze shifts away from a languagesource, were more accurate with these shifts, and produced asmaller proportion of nonlanguage-driven shifts (E1). Next,we present a well-controlled, confirmatory experiment, show-ing that English-speaking adults produced fewer nonlanguage-driven shifts when processing printed text compared to spokenlanguage (E2). Together, these data suggest that people adaptto the value of seeking different information in order to in-crease the chance of rapid and accurate language understand-ing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "eye movements; language processing;information-seeking; American Sign Language"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1692q9pw",
            "frozenauthors": [
                {
                    "first_name": "Kyle",
                    "middle_name": "",
                    "last_name": "MacDonald",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Aviva",
                    "middle_name": "",
                    "last_name": "Blonder",
                    "name_suffix": "",
                    "institution": "Oberlin College",
                    "department": ""
                },
                {
                    "first_name": "Virginia",
                    "middle_name": "",
                    "last_name": "Marchman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Anne",
                    "middle_name": "",
                    "last_name": "Fernald",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "C.",
                    "last_name": "Frank",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26929/galley/16565/download/"
                }
            ]
        },
        {
            "pk": 27289,
            "title": "An Investigation of Factors that Influence Resource Allocation Decisions",
            "subtitle": null,
            "abstract": "We investigate how people allocate a limited set of resourcesbetween multiple risky prospects. We found that only a smallpercentage of decisions followed some form of naive diversifi-cation or mean-variance optimization. In general, people wereless mean-variance optimal than a naive 1/N heuristic. As-pects of choice sets, such as domain, skew, and second orderstochastic dominance, affected resource allocation decisions ina similar manner to their influence on single choice gambles.Individual traits traditionally linked to risk propensity seem tomanifest in terms of the degree to which people are inclinedto diversify. Lower risk aversion and higher risk seeking traitsare linked to increasing diversification. Risk congruency, thedegree to which peoples’ self-reported and elicited risk aver-sion matches, moderates how susceptible people are to costframing nudges. We find evidence for heterogeneous clusterswhere people either under-weight or over-weight segregatedcosts, leading to the same nudge producing opposite behav-ioral results within two risk incongruent groups.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "resource allocation; risk tolerance; riskychoice; individual differences; nudges"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7xd0f3qd",
            "frozenauthors": [
                {
                    "first_name": "Percy",
                    "middle_name": "K.",
                    "last_name": "Mistry",
                    "name_suffix": "",
                    "institution": "University of California Irvine",
                    "department": ""
                },
                {
                    "first_name": "Jennifer",
                    "middle_name": "S.",
                    "last_name": "Trueblood",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27289/galley/16925/download/"
                }
            ]
        },
        {
            "pk": 27035,
            "title": "A non-parametric Bayesian prior for causal inference of auditory streaming",
            "subtitle": null,
            "abstract": "Human perceptual grouping of sequential auditory cues hastraditionally been modeled using a mechanistic approach. Theproblem however is essentially one of source inference – aproblem that has recently been tackled using statisticalBayesian models in visual and auditory-visual modalities.Usually the models are restricted to performing inference overjust one or two possible sources, but human perceptualsystems have to deal with much more complex scenarios. Tocharacterize human perception we have developed a Bayesianinference model that allows an unlimited number of signalsources to be considered: it is general enough to allow anydiscrete sequential cues, from any modality. The model uses anon-parametric prior, hence increased complexity of thesignal does not necessitate more parameters. The model notonly determines the most likely number of sources, but alsospecifies the source that each signal is associated with. Themodel gives an excellent fit to data from an auditory streamsegregation experiment in which the pitch and presentationrate of pure tones determined the perceived number ofsources.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Bayesian modeling; Cognitive model; Causalreasoning; Computational neuroscience; Audition."
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0p24w89s",
            "frozenauthors": [
                {
                    "first_name": "Tim",
                    "middle_name": "",
                    "last_name": "Yates",
                    "name_suffix": "",
                    "institution": "University of Birmingham",
                    "department": ""
                },
                {
                    "first_name": "Nathanael",
                    "middle_name": "",
                    "last_name": "Larigaldie",
                    "name_suffix": "",
                    "institution": "Durham University",
                    "department": ""
                },
                {
                    "first_name": "Ulrik",
                    "middle_name": "R.",
                    "last_name": "Beierholm",
                    "name_suffix": "",
                    "institution": "University of Birmingham",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27035/galley/16671/download/"
                }
            ]
        },
        {
            "pk": 26783,
            "title": "Anthropological Contributions to Cognitive Science",
            "subtitle": null,
            "abstract": "Anthropology was a founding member of cognitive science(Bender et al., 2010; Gardner, 1985), sharing with othercognitive disciplines a deep interest in thinking and behav-ior. With its unique expertise in the cultural content, con-text, and constitution of cognition, it would still be essentialto any comprehensive endeavor to explore the human mind(Bloch, 2012), but rather has turned into cognitive science’s“missing discipline” (Boden, 2006), thus leaving importantquestions unanswered or even unasked. Given that substan-tial shares of knowledge are implicit and that cognition issituated, distributed, embodied, and grounded in variousother ways, anthropological approaches provide privilegedaccess to investigation: for arriving at reasonable hypothe-ses, ensuring ecological validity, and even for coming upwith new research questions and paradigms (Astuti &Bloch, 2012; Hutchins, 2010; Nersessian, 2006).In line with recent calls for rapprochement in Topics inCognitive Science (Bender et al., 2012; Beller & Bender,2015), our symposium brings together scholars that repre-sent different branches of contemporary anthropology withdistinct perspectives—including ‘traditional’ social anthro-pology, cognitive anthropology and ethno-linguistics, cogni-tive ecology, evolutionary anthropology, and archaeology—to present what they consider to be indispensable contribu-tions to cognitive science.With our selection of authors, we hope to demonstrate thevalue of anthropological approaches for cognitive science aswell as the potential benefits of cross-disciplinary collabora-tion. Cognitive archaeologist Overmann discusses a theo-retical perspective on how mind, behavior, and materialartifacts interact to shape human cognition. Combining theirexpertise in linguistics and evolutionary anthropology, Ráczand Jordan investigate the design principles of kinship sys-tems as near-universal conceptual tools. With his back-ground in (ethno-)linguistics and cognitive anthropology,Le Guen uses Yucatec Maya sign languages to illustrate theimportance of cultural practices for shaping cognitive be-havior. Based on Hutchins’ cognitive ecology approach,Solberg speaks to questions at the intersection of anthropol-ogy and philosophy of science by illuminating the culturalframework of science production in a biology lab. And so-cial anthropologist Astuti concludes by taking a bird’s eyeview on how efforts to understand the human mind cruciallybenefit from acknowledging its historical origins and fromtaking the specific sociocultural contexts into consideration.Based on work some of which is published in high-qualityjournals (such as Science, Nature, PNAS, BBS, TiCS, Cur-rent Anthropology, or Cognition), these participants willoffer invaluable contributions to a more diverse, more inclu-sive, and hence more comprehensive cognitive science.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "anthropology; cognitive science; philosophy ofscience; cognition; culture; language; materiality."
                }
            ],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2cx9p6gj",
            "frozenauthors": [
                {
                    "first_name": "Andrea",
                    "middle_name": " ",
                    "last_name": "Bender",
                    "name_suffix": "",
                    "institution": "University of Bergen",
                    "department": ""
                },
                {
                    "first_name": "Sieghard",
                    "middle_name": "",
                    "last_name": "Beller",
                    "name_suffix": "",
                    "institution": "University of Bergen",
                    "department": ""
                },
                {
                    "first_name": "Rita",
                    "middle_name": "",
                    "last_name": "Astuti",
                    "name_suffix": "",
                    "institution": "London School of Economics",
                    "department": ""
                },
                {
                    "first_name": "Olivier",
                    "middle_name": "",
                    "last_name": "Le Guen",
                    "name_suffix": "",
                    "institution": "CIESAS",
                    "department": ""
                },
                {
                    "first_name": "Karenleigh",
                    "middle_name": "A.",
                    "last_name": "Overmann",
                    "name_suffix": "",
                    "institution": "University of Colorado",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Rácz",
                    "name_suffix": "",
                    "institution": "University of Bristol",
                    "department": ""
                },
                {
                    "first_name": "Fiona",
                    "middle_name": "",
                    "last_name": "Jordan",
                    "name_suffix": "",
                    "institution": "University of Bristol",
                    "department": ""
                },
                {
                    "first_name": "Mads",
                    "middle_name": "",
                    "last_name": "Solberg",
                    "name_suffix": "",
                    "institution": "University of Bergen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26783/galley/16419/download/"
                }
            ]
        },
        {
            "pk": 27112,
            "title": "Anticipation Effect after Implicit Distributional Learning",
            "subtitle": null,
            "abstract": "Distributional learning research has established that humanscan track the frequencies of sequentially presented stimuli inorder to infer the probabilities of upcoming events (e.g., Hasher& Zacks, 1984). Here, we set out to explore anticipation of astimulus after implicit distributional learning. We hypothesizethat as people learn the category frequency informationimplicitly, response times will scale according to the relativefrequency of the stimulus category. Twelve adult participantsviewed photographs of faces, tools, and buildings whileperforming a simple classification task. We found that responsetimes significantly decreased with greater frequencies in thedistribution of stimulus categories. This result suggested thatdistributional information about the internal representations ofthe stimuli could be learned and indicated the possibility thatparticipants anticipated the stimuli proportional to theprobability of the category appearing and thereby reducedresponse times for the more frequent categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "statistical learning; implicit distributional learning;anticipation; classification"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6hs8d652",
            "frozenauthors": [
                {
                    "first_name": "Danlei",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Carol",
                    "middle_name": "A.",
                    "last_name": "Jew",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Benjamin",
                    "middle_name": "",
                    "last_name": "Zinszer",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Rajeev",
                    "middle_name": "D. S.",
                    "last_name": "Raizada",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27112/galley/16748/download/"
                }
            ]
        },
        {
            "pk": 27596,
            "title": "Anticipatory Active Inference from Learned Recurrent Neural Forward Models",
            "subtitle": null,
            "abstract": "We demonstrate that inference-based goal-directed behavior can be done by utilizing the temporal gradients in re-current neural network (RNN). The RNN learns a dynamic sensorimotor forward model. Once the RNN is trained, it can beused to execute active-inference-based, goal-directed policy optimization. The internal neural activities of the trained RNNessentially model the predictive state of the controlled entity. The implemented optimization process projects the neural activ-ities into the future via the RNN recurrences following a tentative sequence of motor commands (encoded in neurons akin torecurrent parametric biases). This sequence is adapted by back-projecting the error between the forward-projected hypotheticalstates and desired (goal-like) system states onto the motor commands. Few cycles of forward projection and goal-based errorbackpropagation yield the sequences of motor commands that control the dynamical systems. As an example, we show that atrained RNN model can be used to effectively control a quadrocopter-like system.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0mz9w75s",
            "frozenauthors": [
                {
                    "first_name": "Sebastian",
                    "middle_name": "",
                    "last_name": "Otte",
                    "name_suffix": "",
                    "institution": "University of T ̈ubingen",
                    "department": ""
                },
                {
                    "first_name": "Theresa",
                    "middle_name": "",
                    "last_name": "Schmitt",
                    "name_suffix": "",
                    "institution": "University of T ̈ubingen",
                    "department": ""
                },
                {
                    "first_name": "Martin",
                    "middle_name": "V.",
                    "last_name": "Butz",
                    "name_suffix": "",
                    "institution": "University of T ̈ubingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27596/galley/17232/download/"
                }
            ]
        },
        {
            "pk": 27025,
            "title": "Anticipatory Synchronization in Artificial Agents",
            "subtitle": null,
            "abstract": "By integrating theories and methodologies from a diverserange of scientific disciplines (e.g., physics, neuroscience,cognitive science, psychology and robotics engineering) thepresent work is aimed at harnessing self-organizedanticipatory synchronization in order to advance human-robotic interaction (HRI). This phenomenon is characterizedby the emergence of anticipatory behavior by one systemcoupled to the chaotic behavior of another, following theintroduction of short self-referential delays in the coordinatingsystem. The current set of studies involved the creation of anartificial agent based on a time-delayed, low-dimensionaldynamical model capable of behaving prospectively during aninteraction with a human actor performing complex,unpredictable behaviors. By achieving characteristics similarto those observed during natural human interaction andcoordination, the time-delayed modeling approachedadvocated here provides the potential for considerable futureadvancements in HRI.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "human-robotic interaction; artificial agents;dynamical modeling; virtual reality; anticipatorysynchronization; interpersonal coordination; chaos"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4gq493pn",
            "frozenauthors": [
                {
                    "first_name": "Auriel",
                    "middle_name": "",
                    "last_name": "Washburn",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Rachel",
                    "middle_name": "W.",
                    "last_name": "Kallen",
                    "name_suffix": "",
                    "institution": "University of Cincinnati",
                    "department": ""
                },
                {
                    "first_name": "Maurice",
                    "middle_name": "",
                    "last_name": "Lamb",
                    "name_suffix": "",
                    "institution": "University of Cincinnati",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27025/galley/16661/download/"
                }
            ]
        },
        {
            "pk": 27484,
            "title": "A picture falls under many categories: How ancient mathematical marks becameextinct",
            "subtitle": null,
            "abstract": "The development of mathematical marking conventions from prehistory to the present is characterized by a trendfrom conventions with more iconic relationships to concrete structures of the physical world (such as more pictorial ancient landsurveying marks) to marking systems with less-iconic relationships to physical structures (that represent numbers, operations,infinity, and other more abstract concepts). We propose how certain constraints of perception-cognition induced conventionsthat made more-iconic (pictorial) marks controversial. These became too conceptually ambiguous to convey more abstractconceptual categories during the formalization of mathematics: Iconic properties of ancient proto-mathematical conventionsrecruited lower level perceptual capabilities developed to perceive-act in a concrete world of occluded surfaces-edges andwere suitable for conveying concrete structures (such as landforms during surveying). However, these were too conceptuallyambiguous to convey more abstract conceptual categories that emerged when mathematics was formalized because a (pictured)concrete structure can fall under many possible conceptual categories",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1627v4k9",
            "frozenauthors": [
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Coppin",
                    "name_suffix": "",
                    "institution": "University of Toronto",
                    "department": ""
                },
                {
                    "first_name": "Daemon",
                    "middle_name": "",
                    "last_name": "Retren",
                    "name_suffix": "",
                    "institution": "OCAD University",
                    "department": ""
                },
                {
                    "first_name": "Ambrose",
                    "middle_name": "",
                    "last_name": "Li",
                    "name_suffix": "",
                    "institution": "OCAD University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27484/galley/17120/download/"
                }
            ]
        },
        {
            "pk": 27429,
            "title": "A Plausible Micro Neural Circuit for Decision-Making",
            "subtitle": null,
            "abstract": "An intermediate level between neural circuits and behaviors is\nneural computations, various behaviors that animals exhibit\nfollowing some basic control laws can be implemented by some\ncanonical neural computations [Carandini, 2012]. To explore how\nthe microscopic activity of neurons leads to macroscopic\nbehavioral control strategy, we consider basic logic-like operations\nas some canonical computations in the brain. In this paper, firstly\nwe designed the functional circuits for basic logic-like operations\nbased on the known neurophysiological properties. Secondly,\nusing basic functional circuits constructed a possible neural\nnetwork for decision logic of animal’s behavior. This study\nprovides a general approach for constructing the neural circuits to\nimplement the behavioral control rules. Furthermore, this study\nwill help us to establish a transitional bridge between the\nmicroscopic activity of the nervous system and the macroscopic\nanimal behavior.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neural circuits; Logic; Neural computations;"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/65s227h7",
            "frozenauthors": [
                {
                    "first_name": "Wei",
                    "middle_name": "",
                    "last_name": "Hui",
                    "name_suffix": "",
                    "institution": "Fudan University",
                    "department": ""
                },
                {
                    "first_name": "Dai",
                    "middle_name": "",
                    "last_name": "Dawei",
                    "name_suffix": "",
                    "institution": "Fudan University",
                    "department": ""
                },
                {
                    "first_name": "Bu",
                    "middle_name": "",
                    "last_name": "Yijie",
                    "name_suffix": "",
                    "institution": "Fudan University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27429/galley/17065/download/"
                }
            ]
        },
        {
            "pk": 27624,
            "title": "A positive attitude increases subjective life expectancy",
            "subtitle": null,
            "abstract": "Subjective life expectancy (SLE) has been related to psychological variables, such as optimism. Based on previousstudies where positive attitude was related with longer lifetime, the present study examined whether modifying participants’attitude would influence their SLE. Therefore, 50 participants were randomly assigned either to a positive or to a neutral attitudegroup. During one week, participants of the positive (neutral) group, had to choose the three most accurate positive (neutral)sentences (among 22) to describe their day. After this week, they had to estimate the probability of being 60, 70, 80, or 90years old (traditional measure) and to situate themselves on a line representing their lifetime (spatial based measure). Resultsshow that 1) a more positive attitude increased SLE more than a neutral one, 2) the spatial based measure was sensitive to theintervention and 3) both measures correlated positively with participants’ optimism.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7798p6j9",
            "frozenauthors": [
                {
                    "first_name": "Susana",
                    "middle_name": "Ruiz",
                    "last_name": "Fern ́andez",
                    "name_suffix": "",
                    "institution": "Leibniz-Institut f ̈ur Wissensmedien",
                    "department": ""
                },
                {
                    "first_name": "Martin",
                    "middle_name": "",
                    "last_name": "Lachmair",
                    "name_suffix": "",
                    "institution": "Leibniz-Institut f ̈ur Wissensmedien",
                    "department": ""
                },
                {
                    "first_name": "Juan",
                    "middle_name": "Jos ́e",
                    "last_name": "Rahona",
                    "name_suffix": "",
                    "institution": "Leibniz-Institut f ̈ur Wissensmedien",
                    "department": ""
                },
                {
                    "first_name": "Lotte",
                    "middle_name": "Sophia",
                    "last_name": "Roessler",
                    "name_suffix": "",
                    "institution": "Leibniz-Institut f ̈ur Wissensmedien",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Gerjets",
                    "name_suffix": "",
                    "institution": "Leibniz-Institut f ̈ur Wissensmedien",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27624/galley/17260/download/"
                }
            ]
        },
        {
            "pk": 27597,
            "title": "Application of fuzzy logic in dyslexia user modelling to design customizingassistive technology",
            "subtitle": null,
            "abstract": "Cognitive psychology studies phenomena that cannot be directly observed. Scientific knowledge about the brain isextensive, but there is still a lot to be understood about its functions. Cognitive functions are weakened in dyslexic children; thisis reflected in highly individual problems regarding the reading skills. Reading is a process which consists of decrypting graphiccharacters (perceptual level) and understanding the meaning of words (cognitive level). These levels cannot be separated.An approach – fuzzy logic – is used in order to address this issue and create a model of the dyslexic user, based on whichtechnologies can be individually tailored to a particular dyslexic. We discusse the possibilities of the use of the mathematicalapparatus for the categorisation of users with regard to their ”black box”. Further, we focuse on the development of newassistive technologies targeted at specific attention disorders, reading disorders, as well as information processing disorders.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/81f5z4tz",
            "frozenauthors": [
                {
                    "first_name": "Tereza",
                    "middle_name": "",
                    "last_name": "Paˇrilov ́a",
                    "name_suffix": "",
                    "institution": "Masaryk UniversityEva Hladk ́a",
                    "department": ""
                },
                {
                    "first_name": "Eva v",
                    "middle_name": "",
                    "last_name": "Hladk ́a",
                    "name_suffix": "",
                    "institution": "Masaryk UniversityEva Hladk ́a",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27597/galley/17233/download/"
                }
            ]
        },
        {
            "pk": 27601,
            "title": "Applications of Cognitive Science to Enhancing Scholarly Communication",
            "subtitle": null,
            "abstract": "Learning from and building on the accomplishments of scholarly publications is often difficult. To address thischallenge, this work leverages well-replicated cognitive science phenomena to promote people’s understanding of researchfound in journal articles. It forms the conceptual groundwork for a digital platform through which users can author and learnfrom interactive multimedia documents that communicate research more effectively. One of the many recommendations is toreduce the split-attention effect by integrating text and graphics in figures. Doing so may help readers understand complexvisuospatial representations. Encouraging active processing via comprehension questions and responsive simulations of ex-perimental procedures embedded in articles may boost learning even more. To promote the creative extension of research,evidence-based brainstorming prompts that trigger analogical reasoning and episodic specificity induction should be adopted.If scholarly communication is centered on scientific principles like these, then the dissemination and dynamics of science mayboth advance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/83b784s3",
            "frozenauthors": [
                {
                    "first_name": "Purav",
                    "middle_name": "",
                    "last_name": "Patel",
                    "name_suffix": "",
                    "institution": "University of Minnesota",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27601/galley/17237/download/"
                }
            ]
        },
        {
            "pk": 27013,
            "title": "Approximations of Predictive Entropy Correlate with Reading Times",
            "subtitle": null,
            "abstract": "The lexical frequency of an upcoming word affects read-ing times even when the upcoming word is masked fromreaders (Angele et al., 2015). One explanation for thisobservation is that readers may slow down if there is highuncertainty about upcoming material. In line with thishypothesis, this study finds a positive correlation be-tween predictive entropy and self-paced reading times.This study also demonstrates that such predictive en-tropy can be effectively approximated by the surprisalof upcoming observations and that this future surprisalestimate is more predictive of reading times when thegrammar is more granular, which would be prohibitivelyexpensive for predictive entropy. These results suggestreaders engage in fine-grained predictive estimations ofcertainty about upcoming lexical and syntactic material,that such predictions influence reading times, and thatestimating that uncertainty can be done less expensivelyand more robustly with information-theoretic surprisal.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Self-Paced Reading; Information Theory;Language Modeling; Corpus Studies"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/62b0s3tp",
            "frozenauthors": [
                {
                    "first_name": "Marten",
                    "middle_name": "",
                    "last_name": "van Schijndel",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                },
                {
                    "first_name": "William",
                    "middle_name": "",
                    "last_name": "Schuler",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27013/galley/16649/download/"
                }
            ]
        },
        {
            "pk": 27075,
            "title": "A Preliminary P-Curve Meta-Analysis of Learned Categorical Perception Research",
            "subtitle": null,
            "abstract": "A preliminary meta-analysis using the p-curve method(Simonsohn, Nelson, & Simmons, 2014) was performed on asubset of the learned categorical perception literature toexplore the robustness of the phenomenon. Only studies usingnovel visual categories and behavioral measures wereincluded. The results strongly suggest that the phenomenon isrobust but that the studies are somewhat underpowered. Weargue that this is problematic because it renders bothstatistically significant and nonsignificant results verydifficult to interpret, which impedes progress inunderstanding the learned CP phenomenon, for example, whyexpansion vs. compression is observed, or boundary vs.dimensional effects. Fortunately, there is a clear solution:conduct studies with greater statistical power.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "categorical perception; categorization; learning;p-curve; statistical power; expansion; compression;dimensional modulation"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1ss3r5wx",
            "frozenauthors": [
                {
                    "first_name": "Janet",
                    "middle_name": "",
                    "last_name": "Andrews",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "de Leeuw",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                },
                {
                    "first_name": "Calais",
                    "middle_name": "",
                    "last_name": "Larson",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                },
                {
                    "first_name": "Xiaoqing",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "Vassar College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27075/galley/16711/download/"
                }
            ]
        },
        {
            "pk": 26876,
            "title": "A Priming Model of Category-based Feature Inference",
            "subtitle": null,
            "abstract": "Categorization has a large impact on how people perceive theworld, especially when used to make inferences about uncer-tain features of new objects. While making these inferences,people tend to draw information from only one possible cate-gorization of a new object; in addition, people are sensitive topre-existing correlations between features. Here, we explainthese trends of feature inference using a priming-based cogni-tive process model, and show that our model is distinguishedin that it can explain not only these two main trends, but alsocases where people seem to reverse the first trend and base in-ferences on information from multiple categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "categorization; priming; spreading activation; in-ductive inference; cognitive models"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8p32f6qs",
            "frozenauthors": [
                {
                    "first_name": "Laura",
                    "middle_name": "M.",
                    "last_name": "Hiatt",
                    "name_suffix": "",
                    "institution": "US Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26876/galley/16512/download/"
                }
            ]
        },
        {
            "pk": 26840,
            "title": "A rational analysis of curiosity",
            "subtitle": null,
            "abstract": "We present a rational analysis of curiosity, proposing that peo-ple’s curiosity is driven by seeking stimuli that maximize theirability to make appropriate responses in the future. This per-spective offers a way to unify previous theories of curiosityinto a single framework. Experimental results confirm ourmodel’s predictions, showing how the relationship between cu-riosity and confidence can change significantly depending onthe nature of the environment.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "curiosity; rational analysis; computational model"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/52d9h9cr",
            "frozenauthors": [
                {
                    "first_name": "Rachit",
                    "middle_name": "",
                    "last_name": "Dubey",
                    "name_suffix": "",
                    "institution": "University of California at Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "L.",
                    "last_name": "Griffiths",
                    "name_suffix": "",
                    "institution": "University of California at Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26840/galley/16476/download/"
                }
            ]
        },
        {
            "pk": 26987,
            "title": "A rational analysis of marketing strategies",
            "subtitle": null,
            "abstract": "Rational accounts of decision-making are incompatible withthe prevalence and success of ubiquitous marketing strategies.In this paper, we demonstrate, using computational experi-ments, how an ideal Bayesian observer model of preferencelearning is compatible with the manipulation of purchasingdecisions via a number of well-known marketing techniques.The ability of this model to predict the effects of both famil-iar and novel marketing interventions suggests it as a plausiblecandidate theory of consumer marketing. Simultaneously, byclarifying the logic underneath the interplay between environ-mental exposure and preference distortions seen in economicdecisions, this model rationalizes the seemingly irrational sus-ceptibility of consumers to marketing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "decision-making; preference learning; advertris-ing; marketing; rational analysis"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5c3163r7",
            "frozenauthors": [
                {
                    "first_name": "Nisheeth",
                    "middle_name": "",
                    "last_name": "Srivastava",
                    "name_suffix": "",
                    "institution": "IIT Kanpur",
                    "department": ""
                },
                {
                    "first_name": "Edward",
                    "middle_name": "",
                    "last_name": "Vul",
                    "name_suffix": "",
                    "institution": "University of California, San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26987/galley/16623/download/"
                }
            ]
        },
        {
            "pk": 26985,
            "title": "A Rational Approach to Stereotype Change",
            "subtitle": null,
            "abstract": "Existing theories of stereotype change have often made use ofcategorisation principles in order to provide qualitative expla-nations for both the revision and maintenance of stereotypicalbeliefs. The present paper examines the quantitative methodsunderlying these explanations, contrasting both rational andheuristic models of stereotype change using participant dataand model fits. In a comparison of three models each simulat-ing existing descriptions of stereotype change, both empiricaldata and model fits suggest that stereotypes are updated usingrational categorisation processes. This presents stereotype useas a more rational behaviour than may commonly be assumed,and provides new avenues of encouraging stereotype changeaccording to rational principles.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Stereotypes; Categorisation; Rational Behaviour"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5t407851",
            "frozenauthors": [
                {
                    "first_name": "Jake",
                    "middle_name": "",
                    "last_name": "Spicer",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Adam",
                    "middle_name": "",
                    "last_name": "Sanborn",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26985/galley/16621/download/"
                }
            ]
        },
        {
            "pk": 26933,
            "title": "A Rational Constructivist Account of the Characteristic-to-Defining Shift",
            "subtitle": null,
            "abstract": "A widely observed phenomenon in children’s word-extensionsand generalizations is the characteristic-to-defining shift,whereby young children initially generalize words based ontypical properties and gradually transition into generalizingwords using abstract, logical information. In this paper, wepropose a statistically principled model of conceptual devel-opment grounded in the trade-off between simplicity and fit tothe data. We run our model based on informant-provided fam-ily trees and the real-life characteristic features of people onthose trees. We demonstrate that the characteristic-to-definingshift does not necessarily depend on discrete change in rep-resentation or processes. Instead, the shift could fall out nat-urally from statistical inference over conceptual hypotheses.Our model finds that the shift occurs even when abstract logicalrelations are present from the outset of learning as long as char-acteristic features are informative but imperfect in their abilityto capture the underlying concept to be learned—a property ofour elicited features.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "characteristic-to-defining shift; concept learning;development; computational modeling"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/86h0b8bd",
            "frozenauthors": [
                {
                    "first_name": "Francis",
                    "middle_name": "",
                    "last_name": "Mollica",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Shirlene",
                    "middle_name": "",
                    "last_name": "Wade",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "T.",
                    "last_name": "Piantadosi",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26933/galley/16569/download/"
                }
            ]
        },
        {
            "pk": 27142,
            "title": "Architectural process models of decision making:\nTowards a model database",
            "subtitle": null,
            "abstract": "We present the project aimed at creating a database of\ndetailed architectural process models of memory-based\ndecision models. Those models are implemented in the\ncognitive architecture ACT-R. In creating this database, we\nhave identified commonalities and differences of various\ndecision models in the literature. The model database can\nprovide insights into the interrelation among decision models\nand can be used in future research to address debates on\ninferences from memory, which are hard to resolve without\nspecifying the processing steps at the level of precision that a\ncognitive architecture provides.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "inference from memory; process model; ACT-R;\ndecision making; model database"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3wm638s3",
            "frozenauthors": [
                {
                    "first_name": "Cvetomir",
                    "middle_name": "M.",
                    "last_name": "Dimov",
                    "name_suffix": "",
                    "institution": "Université de Lausanne",
                    "department": ""
                },
                {
                    "first_name": "Julian",
                    "middle_name": "N.",
                    "last_name": "Marewski",
                    "name_suffix": "",
                    "institution": "Université de Lausanne",
                    "department": ""
                },
                {
                    "first_name": "Lael",
                    "middle_name": "J.",
                    "last_name": "Schooler",
                    "name_suffix": "",
                    "institution": "Syracuse University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27142/galley/16778/download/"
                }
            ]
        },
        {
            "pk": 36013,
            "title": "Are They All Language Learners?: Educational Labeling and Raciolinguistic Identifying in a California Middle School Dual Language Program",
            "subtitle": null,
            "abstract": "This manuscript draws from a 2-year multiple-case ethnography\non the educational experiences of immigrant families with California middle schools. The article explores the influence of the\npolitical landscape and raciolinguistic ideologies surrounding the\nnature and implementation of a dual language bilingual program,\nand it shares ethnographic snapshots from both a school- and\nhome-based perspective of (in)equity issues related to the program. Data sources include home and school observations, and\ninterviews with students, parents, administrators, and teachers.\nFindings suggest that though all students are treated as language\nlearners, educational-reform policies and practices may be undermining the school’s effort to implement an equitable bilingual\nprogram. Implications for practice include the interrogation of\neducational policies and practices that can further marginalize\nstudents across race and class in the process of becoming bilingual in the US.",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Theme Section - Language, Identity, and the Legacy of Colonialism",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5kn4d9fd",
            "frozenauthors": [
                {
                    "first_name": "Sera",
                    "middle_name": "J.",
                    "last_name": "Hernandez",
                    "name_suffix": "",
                    "institution": "San Diego State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36013/galley/26865/download/"
                }
            ]
        },
        {
            "pk": 27682,
            "title": "A Spatial-Temporal Analysis of a Visual Working Memory Task with EEG andECoG",
            "subtitle": null,
            "abstract": "In this study, we investigated the neural correlates of a visual working memory task. Two experiments were carriedout using scalp electroencephalography (EEG) and Electrocorticography (ECoG), respectively. In each trial, participants judgedwhether a test face had been among a small set of recently studied faces. We used a combination of hidden semi-Markov models(HSMMs) and multi-variate pattern analysis (MVPA) to decompose the neural signal into a sequence of latent stages. Analyzedseparately, EEG and ECoG data yielded converging results on the durations of recovered stages. Combining these stages withthe high spatial resolution of ECoG suggested that activity in the temporal cortex reflected item familiarity in the retrievalstage; and that once retrieval is complete, there is active maintenance of the studied face set in the medial temporal lobe (MTL).During this same period, the frontal lobe guides the decision by means of theta coupling with the MTL.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2kp923np",
            "frozenauthors": [
                {
                    "first_name": "Qiong",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Marieke",
                    "middle_name": "",
                    "last_name": "van Vugt",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "Jelmer",
                    "middle_name": "",
                    "last_name": "Borst",
                    "name_suffix": "",
                    "institution": "University of Groningen",
                    "department": ""
                },
                {
                    "first_name": "John",
                    "middle_name": "",
                    "last_name": "Anderson",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27682/galley/17318/download/"
                }
            ]
        },
        {
            "pk": 27176,
            "title": "A Spiking Independent Accumulator Model for Winner-Take-All Computation",
            "subtitle": null,
            "abstract": "Winner-take-all (WTA) mechanisms are an important compo-nent of many cognitive models. For example, they are oftenused to decide between multiple choices or to selectively di-rect attention. Here we compare two biologically plausible,spiking neural WTA mechanisms. We first provide a novelspiking implementation of the well-known leaky, competingaccumulator (LCA) model, by mapping the dynamics onto apopulation-level representation. We then propose a two-layerspiking independent accumulator (IA) model, and compare itsperformance against the LCA network on a variety of WTAbenchmarks. Our findings suggest that while the LCA net-work can rapidly adapt to new winners, the IA network is bet-ter suited for stable decision making in the presence of noise.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neural Engineering Framework; Nengo; winner-take-all; decision making; mutual inhibition; neural competi-tion; dynamical systems"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/01z51564",
            "frozenauthors": [
                {
                    "first_name": "Jan",
                    "middle_name": "",
                    "last_name": "Gosmann",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Aaron",
                    "middle_name": "R.",
                    "last_name": "Voelker",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Eliasmith",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27176/galley/16812/download/"
                }
            ]
        },
        {
            "pk": 27362,
            "title": "A Spiking Neural Bayesian Model of Life Span Inference",
            "subtitle": null,
            "abstract": "In this paper, we present a spiking neural model of life spaninference. Through this model, we explore the biologicalplausibility of performing Bayesian computations in the brain.Specifically, we address the issue of representing probabil-ity distributions using neural circuits and combining them inmeaningful ways to perform inference. We show that applyingthese methods to the life span inference task matches humanperformance on this task better than an ideal Bayesian modeldue to the use of neuron tuning curves. We also describe po-tential ways in which humans might be generating the priorsneeded for this inference. This provides an initial step towardsbetter understanding how Bayesian computations may be im-plemented in a biologically plausible neural network.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neural Engineering Framework; biologicallyplausible inference; neural bayesian model; expectation maxi-mization"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3dw672g6",
            "frozenauthors": [
                {
                    "first_name": "Sugandha",
                    "middle_name": "",
                    "last_name": "Sharma",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Aaron",
                    "middle_name": "R.",
                    "last_name": "Voelker",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Eliasmith",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27362/galley/16998/download/"
                }
            ]
        },
        {
            "pk": 27626,
            "title": "ASR Systems as Models of Phonetic Category Perception in Adults",
            "subtitle": null,
            "abstract": "Adult speech perception is tuned to efficiently process native phonetic categories, causing difficulties with certainnon-native categories. For example, Japanese has no equivalent of the distinction between American English /r/ and /l/ and na-tive speakers of Japanese have a hard time discriminating between these two sounds. Here, we ask whether standard AutomaticSpeech Recognition (ASR) systems trained on large corpora of continuous speech can make correct quantitative predictionsregarding such non-native phonetic category perception effects. By training an ASR system on language L1 and evaluatingit on language L2, we obtain predictions for a native L1 speaker tested on L2 phonetic contrasts. Using a variety of L1 andL2, we show that ASR models correctly predict several well-documented effects. Beyond the immediate results, our evaluationmethodology, based on a machine version of ABX discrimination tasks, opens the possibility of a more systematic investigationof computational models of phonetic category perception.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Posters: Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0jt7r6cm",
            "frozenauthors": [
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Schatz",
                    "name_suffix": "",
                    "institution": "Ecole Normale Sup ́erieure",
                    "department": ""
                },
                {
                    "first_name": "Francis",
                    "middle_name": "",
                    "last_name": "Bach",
                    "name_suffix": "",
                    "institution": "Ecole Normale Sup ́erieure",
                    "department": ""
                },
                {
                    "first_name": "Emmanuel",
                    "middle_name": "",
                    "last_name": "Dupoux",
                    "name_suffix": "",
                    "institution": "Ecole Normale Sup ́erieure",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27626/galley/17262/download/"
                }
            ]
        },
        {
            "pk": 26956,
            "title": "Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks",
            "subtitle": null,
            "abstract": "Increasingly, cognitive scientists have demonstrated interest inapplying tools from deep learning. One use for deep learning isin language acquisition where it is useful to know if a linguisticphenomenon can be learned through domain-general means.To assess whether unsupervised deep learning is appropriate,we first pose a smaller question: Can unsupervised neural net-works apply linguistic rules productively, using them in novelsituations? We draw from the literature on determiner/nounproductivity by training an unsupervised, autoencoder networkmeasuring its ability to combine nouns with determiners. Oursimple autoencoder creates combinations it has not previouslyencountered and produces a degree of overlap matching adults.While this preliminary work does not provide conclusive evi-dence for productivity, it warrants further investigation withmore complex models. Further, this work helps lay the foun-dations for future collaboration between the deep learning andcognitive science communities.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Deep Learning; Language Acquisition; LinguisticProductivity; Unsupervised Learning; Determiners"
                }
            ],
            "section": "Talks: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/72z2w2nd",
            "frozenauthors": [
                {
                    "first_name": "Lawrence",
                    "middle_name": "",
                    "last_name": "Phillips",
                    "name_suffix": "",
                    "institution": "Pacific Northwest National Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Nathan",
                    "middle_name": "",
                    "last_name": "Hodas",
                    "name_suffix": "",
                    "institution": "Pacific Northwest National Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26956/galley/16592/download/"
                }
            ]
        },
        {
            "pk": 27215,
            "title": "A Study on the Impact of Chess Training on Creativity of Indian School Children",
            "subtitle": null,
            "abstract": "Creativity is the ability to produce work that is both novel and\nappropriate. The study, funded by Indian government,\nanalyzed the effect of one-year chess training on the creativity\nof children. A pretest and posttest with control group design\nwas used, with 31 children in experimental and 32 in control\ngroup. The experimental group underwent weekly chess\ntraining. Wallach-Kogan Creativity Test (Indian Adaptation)\nwas used. Analysis revealed that only the experimental group\nhad statistically significant gains in total creativity and two\nnonverbal subtests. The authors conclude that systematic\nchess training inculcates in the child the ability to think\ndivergently and creatively.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Abstract Thinking; Chess Training; Creativity;\nInnovation; Divergent Thinking"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/11g4567d",
            "frozenauthors": [
                {
                    "first_name": "Ebenezer",
                    "middle_name": "",
                    "last_name": "Joseph",
                    "name_suffix": "",
                    "institution": "University of Madras",
                    "department": ""
                },
                {
                    "first_name": "S.",
                    "middle_name": "Sundar",
                    "last_name": "Manoharan",
                    "name_suffix": "",
                    "institution": "Karunya University",
                    "department": ""
                },
                {
                    "first_name": "Veena",
                    "middle_name": "",
                    "last_name": "Easvaradoss",
                    "name_suffix": "",
                    "institution": "Women’s Christian College",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Chandran",
                    "name_suffix": "",
                    "institution": "Emmanuel Chess Centre",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27215/galley/16851/download/"
                }
            ]
        },
        {
            "pk": 27183,
            "title": "Asymmetric detection of changes in volatility:\nImplications for risk perception",
            "subtitle": null,
            "abstract": "Variance of the outcomes associated with an option often\nprovides a measure of the riskiness of that option. Hence, it is\nimportant for organisms are able to detect any sudden changes\nin outcome variance. In Experiment 1, we presented people\nwith graphs of share price time series or water level time\nseries. In half the graphs, variance (financial or flooding risk)\nchanged at some point. People were better at detecting\nincreases than decreases in risk - maybe because it is more\nimportant to detect increases in danger than decreases in it.\nHowever, in Experiment 2, people were still better at\ndetecting increases than decreases in variance even when\nthose changes did not reflect altered levels of risk. Our\nfindings may reflect the fact that the actual change in variance\nexceeds the change needed to identify a regime change in\nvariance by a larger amount for upward than for downward\nchanges.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "volatility; variance; risk; change detection;\njudgment"
                }
            ],
            "section": "Posters: Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6f9665wc",
            "frozenauthors": [
                {
                    "first_name": "Nigel",
                    "middle_name": "",
                    "last_name": "Harvey",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Matt",
                    "middle_name": "",
                    "last_name": "Twyman",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                },
                {
                    "first_name": "Maarten",
                    "middle_name": "",
                    "last_name": "Speekenbrink",
                    "name_suffix": "",
                    "institution": "University College London",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2017-01-01T18:00:00Z",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/27183/galley/16819/download/"
                }
            ]
        }
    ]
}