API Endpoint for journals.

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        {
            "pk": 39445,
            "title": "Review: Face à Gaïa. Huit conférences sur le nouveau régime climatique. [Facing Gaia. Eight Lectures on the New Climate Regime]",
            "subtitle": null,
            "abstract": "Book Review",
            "language": "fr",
            "license": {
                "name": "none",
                "short_name": "none",
                "text": "",
                "url": "https://escholarship.org/terms"
            },
            "keywords": [
                {
                    "word": "ecology"
                },
                {
                    "word": "environment"
                },
                {
                    "word": "climate change"
                }
            ],
            "section": "Reviews",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/95j1x2d0",
            "frozenauthors": [
                {
                    "first_name": "Yves",
                    "middle_name": "",
                    "last_name": "Laberge",
                    "name_suffix": "",
                    "institution": "Centre de recherche en éducation et formation relatives à l’environnement et à l’écocitoyenneté – Centr'ERE, Québec, G1V 0A6, Canada",
                    "department": "None"
                }
            ],
            "date_submitted": "2016-01-04T17:24:46+02:00",
            "date_accepted": "2016-01-04T17:24:46+02:00",
            "date_published": "2016-01-04T17:29:42+02:00",
            "render_galley": null,
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                    "label": "",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/egj/article/39445/galley/29777/download/"
                }
            ]
        },
        {
            "pk": 36022,
            "title": "2015-2016 CATESOL Board of Directors",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5dp6d725",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36022/galley/26874/download/"
                }
            ]
        },
        {
            "pk": 36037,
            "title": "2015-2016 CATESOL Board of Directors",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/94r316xs",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36037/galley/26889/download/"
                }
            ]
        },
        {
            "pk": 26490,
            "title": "A 3D shape inference model matches human visual object similarity judgmentsbetter than deep convolutional neural networks",
            "subtitle": null,
            "abstract": "In the past few years, deep convolutional neural networks(CNNs) trained on large image data sets have shown impres-sive visual object recognition performances. Consequently,these models have attracted the attention of the cognitive sci-ence community. Recent studies comparing CNNs with neuraldata from cortical area IT suggest that CNNs may—in addi-tion to providing good engineering solutions—provide goodmodels of biological visual systems. Here, we report evidencethat CNNs are, in fact, not good models of human visual per-ception. We show that a 3D shape inference model explainshuman performance on an object shape similarity task betterthan CNNs. We argue that deep neural networks trained onlarge amounts of image data to maximize object recognitionperformance do not provide adequate models of human vision.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "shape perception; object recognition; neural net-works; 3D shape; deep learning"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0ws4t547",
            "frozenauthors": [
                {
                    "first_name": "Goker",
                    "middle_name": "",
                    "last_name": "Erdogan",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "A.",
                    "last_name": "Jacobs",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
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                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26490/galley/16126/download/"
                }
            ]
        },
        {
            "pk": 26535,
            "title": "A 6-month longitudinal study on numerical estimation in preschoolers",
            "subtitle": null,
            "abstract": "The current study investigated the development of numerical\nestimation in 3- to 5-year-old children sampled monthly for six\nmonths. At each session, children completed a task that\nassesses verbal number knowledge (Give-N task) and a\nnumerical estimation task that assesses approximate number\nknowledge (Fast Cards). Results showed that children who\nacquired the cardinal principle (CP) during the course of the\nstudy showed marked improvement on the estimation task.\nFollowing CP acquisition, estimation became more accurate\noverall but also fluctuated widely. We discuss the implications\nof our findings for number word learning, particularly the\nmapping between verbal number and the approximate number\nsystem (ANS).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "numerical estimation; approximate number;\nsubset-knowers; cardinal principle knowers; longitudinal"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4932939m",
            "frozenauthors": [
                {
                    "first_name": "Pierina",
                    "middle_name": "",
                    "last_name": "Cheung",
                    "name_suffix": "",
                    "institution": "Wesleyan University",
                    "department": ""
                },
                {
                    "first_name": "Emily",
                    "middle_name": "",
                    "last_name": "Slusser",
                    "name_suffix": "",
                    "institution": "San Jose State University",
                    "department": ""
                },
                {
                    "first_name": "Anna",
                    "middle_name": "",
                    "last_name": "Shusterman",
                    "name_suffix": "",
                    "institution": "Wesleyan University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
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            ]
        },
        {
            "pk": 26539,
            "title": "A Bayesian Metric for Network Similarity",
            "subtitle": null,
            "abstract": "Networks of every kind and in numerous fields areomnipresent in today’s society (e.g. brain networks, socialnetworks) and are the intense subject of research. It wouldbe of great utility to have a computationally efficient andgenerally applicable method for assessing similarity ofnetworks. The field (going back to the 1950s) has not comeup with such a method (albeit a few moves in this directionexist, such as Jaccard coefficients, QAP--quadraticassignment procedure, and more recently Menezes & Roth,2013, and Asta & Shalizi, 2014). I present a Bayesian-basedmetric for assessing similarity of two networks, possibly ofdifferent size, that include nodes and links between nodes. Iassume the nodes are labeled so that both the nodes andlinks between two nodes that are shared between the twonetworks can be identified.The method calculates similarity as (a monotonictransformation of) the odds that the two observed networks,termed V and W, were produced by random sampling froma single master network, termed G, as opposed to generationby two different but similar networks, termed Gv and Gw.The simplest form of the method ignores strengths thatcould be assigned to nodes and links, and considers onlynodes and links that are, or are not, shared by the networks.Suppose there are n V nodes and N V links only in V, n Wnodes and N W links only in W and n c nodes and N c linksshared between the networks. Thus the number of nodes inV is n c + n V and the number in W is n c + n W . The number ofunique nodes in both V and W is n c + n V + n W = n. Thenumber of links in V is N c + N V and the number in W is N c +N W . The number of unique links in both V and W is N c + N V+ N W = N.The single master network, G, is assumed to consist of theunion of the nodes and links in the two networks, and has nnodes and N links. The probability a given shared node willbe randomly and independently sampled twice is[(n V +n c )/n][(n W +n c )/n]. The probability a given shared linkwill be randomly and independently sampled twice is[(N V +N c )/N][(N W +N c )/N].If there are two generating networks I assume they eachhave n nodes and N links. I also assume they are similar, because we would not be comparing dissimilar networks.The degree of similarity is controlled by ‘tuning’parameters 1 : Gv and Gw are assumed to share αn nodes andβN links. The probability a given shared node will besampled twice is then α[(n V +n c )/n][(n W +n c )/n], and theprobability a given shared link will be sampled twice isβ[(N V +N c )/N][(N W +N c )/N]. The likelihood ratio λ js for G vs(GV, GW) as generator of a given shared node is then 1/αand the likelihood ratio π js of a given shared link is then 1/β.For a non-shared node, say in V, similar reasoning gives alikelihood ratio λ kV of[1-(n W +n c )/n)] /[1– α(n W +n c )/n]and for a non-shared link a likelihood ratio π kV of[1-(N W +N c )/n)] /[1– α(N W +N c )/N]For a non-shared node or link in W substitute a Wsubscript for the V subscript in these likelihood ratios.Computational efficiency is a necessity if the similaritymetric is to be applied to large networks. For this reason Ido not calculate the exact probabilities for the numbers ofshared and non-shared nodes and links that are observed(the combinatoric complexity of such calculations isenormous). Instead I make the simplifying assumption thateach node and link contribute the likelihood ratios givenabove and that the total odds is obtained by multiplying allthe likelihood ratios together. This simplification canperhaps be justified if similar distortion is produced by thissimplifying assumption for both the cases of G and (G V ,G W )as generators. Under this simplifying assumption the overallodds becomes:φ(1/2) = (λ js ) nc (λ kV ) nV (λ jW ) nW (π js ) Nc (π kV ) NV (π jW ) NWTaking the log of this product converts the calculation tosums and makes calculation highly efficient.This abstract is too short to permit giving the different andmore complex results that hold for the several cases whenthe nodes and/or links have associated strengths. I give asummary of some of the results here. The results for linksand nodes are similar so consider the results for nodes. Letthere be just one set of strength values, Si for the i-th node.Norm these to sum to 1.0. For either generation by G or(Gv,Gw) assume sampling is made without replacement andproportional to strength. Let Ziv and Ziw be theprobabilities that node i will be sampled by n v +n c samples,or n w +n c samples respectively. The Z’s would be difficult to obtain analytically but could be estimated by Monte Carlosampling. Consider two possibilities for the way that Gv andGw overlap. In Case A the probability a node will be sharedis simply α, independent of strength. In Case B, theprobability a node will be shared is an increasingfunction of strength, Y i .For Case A the likelihood ratio for a shared node i is:1/α. For a node k only in V the likelihood ratio is: λ kV =(1-­‐Zkw)/{1 – α (1-­‐Zkw)}. For a node only in W exchangethe subscripts v and w. Then we have for the odds due tonodes: φ D = (1/α) nc Π k (λ kV )Π j (λ jW ).For Case B the likelihood ratio for a shared node i is1/Y i . For a node k only in V the likelihood ratio is: λ kV =(1-­‐Zkw)/{1–Y k (1-­‐Zkw)}. Again switch v and w subscriptsfor a node only in W. Then we have for the odds due tonodes: φ D = Π i (1/Y i )Π k (λ kV )Π j (λ jW ).These expressions would have analogous forms forlinks, with different Ns, Z’s and Y’s, and the overall oddswould, as before, be a product of the odds for nodes andthe odds for links.The critical difference between Cases A and B is thedegree to which evidence based on an observed sharednode or link is strength dependent: For Case B thisevidence rises as strength decreases. This should raiseconcerns: However strengths are obtained there is likelyto be measurement noise that reduces the reliability oflow strength values. This might argue in favor of usingCase A, or if one preferred Case B to restrict the Yi valuesto lie above a lower bound. The idea would be to letevidence depend most on the nodes (or links with highstrength values.It should be observed that the existence of acomputationally efficient and generally applicable metricfor network similarity would allow alignment of non-labeled networks. One would search for the alignment ofnodes that would maximize the metric.I have many relevant publications demonstrating somedegree of expertise in Bayesian modeling (e.g.: Shiffrin &Chandramouli, in press; Shiffrin, Chandramouli, &Grünwald, 2015; Chandramouli & Shiffrin, 2015; Nelson &Shiffrin, 2013; Cox & Shiffrin, 2012; Shiffrin, Lee, Kim, &Wagenmakers, 2008; Cohen, Shiffrin, Gold, Ross, & Ross,2007; Denton & Shiffrin; Huber, Shiffrin, Lyle, & Ruys,2001; Shiffrin & Steyvers, 1997). I note that the presentresults are in a vague sense an extension of the metricproposed for matching memory probes to memory tracesthat are given in Cox and Shiffrin (2012) and in theappendix of Nelsonb and Shiffrin (2013).",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Network Similarity"
                },
                {
                    "word": "Network Inference"
                },
                {
                    "word": "NetworkComparison"
                },
                {
                    "word": "Bayesian Methods"
                }
            ],
            "section": "Publication-Based Presentations",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2r38g0nx",
            "frozenauthors": [
                {
                    "first_name": "Richard",
                    "middle_name": "M.",
                    "last_name": "Shiffrin",
                    "name_suffix": "",
                    "institution": "Indiana University Bloomington",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26539/galley/16175/download/"
                }
            ]
        },
        {
            "pk": 26752,
            "title": "A Brain-Based Feature Model of Adjective-Noun Composition",
            "subtitle": null,
            "abstract": "Brain-based features of meaning (sensory-motor features: sound, color, manipulation, motion, and shape) are usedto compare two popular models of adjective-noun semantic composition: element-wise vector addition and multiplication. Alarge literature (e.g. Fernandino et al., 2015) suggests that perceptual systems contain information that can be extracted usingneural decoding (e.g. Anderson, Murphy & Poesio, 2014). Using Amazon’s Mechanical Turk, participants rated how mucheach of the words and phrases (made of all combinations of the selected adjectives and nouns) evoked the features. Bothmultiplication and addition surpass chance at matching the correct phrase, but addition outperformed multiplication (addition =7.6/60, multiplication = 13.4/60). Addition allows the adjective to weight the important sensory-motor attributes for the noun.Based on these behavioral results, we predict, and will test in upcoming work, that addition will also be successful when usingbrain activity (from fMRI) as the representations of the adjectives, nouns, and phrases.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3hj869mz",
            "frozenauthors": [
                {
                    "first_name": "Elizabeth",
                    "middle_name": "A.",
                    "last_name": "Shay",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26752/galley/16388/download/"
                }
            ]
        },
        {
            "pk": 26446,
            "title": "Abstraction in time: Finding hierarchical linguistic structure in a model ofrelational processing",
            "subtitle": null,
            "abstract": "Abstract mental representation is fundamental for humancognition. Forming such representations in time, especiallyfrom dynamic and noisy perceptual input, is a challenge forany processing modality, but perhaps none so acutely as forlanguage processing. We show that LISA (Hummel &Holyaok, 1997) and DORA (Doumas, Hummel, & Sandhofer,2008), models built to process and to learn structured (i.e.,symbolic) representations of conceptual properties andrelations from unstructured inputs, show oscillatory activationduring processing that is highly similar to the cortical activityelicited by the linguistic stimuli from Ding et al. (2016). Weargue, as Ding et al. (2016), that this activation reflectsformation of hierarchical linguistic representation, andfurthermore, that the kind of computational mechanisms inLISA/DORA (e.g., temporal binding by systematicasynchrony of firing) may underlie formation of abstractlinguistic representations in the human brain. It may be thisrepurposing that allowed for the generation or emergence ofhierarchical linguistic structure, and therefore, humanlanguage, from extant cognitive and neural systems. Weconclude that models of thinking and reasoning and models oflanguage processing must be integrated—not only forincreased plausiblity, but in order to advance both fieldstowards a larger integrative model of human cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "computational models"
                },
                {
                    "word": "sentence processing"
                },
                {
                    "word": "analogy"
                },
                {
                    "word": "relational reasoning"
                },
                {
                    "word": "concepts"
                },
                {
                    "word": "binding"
                },
                {
                    "word": "temporalasynchrony"
                },
                {
                    "word": "oscillations"
                },
                {
                    "word": "computational neuroscience"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0nb7v1fs",
            "frozenauthors": [
                {
                    "first_name": "Leonidas",
                    "middle_name": "A.A.",
                    "last_name": "Doumas",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                },
                {
                    "first_name": "Andrea",
                    "middle_name": "E.",
                    "last_name": "Martin",
                    "name_suffix": "",
                    "institution": "University of Edinburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26446/galley/16082/download/"
                }
            ]
        },
        {
            "pk": 36020,
            "title": "Abstracts",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/06h0n6vp",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36020/galley/26872/download/"
                }
            ]
        },
        {
            "pk": 36035,
            "title": "Abstracts",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2jw7m6fh",
            "frozenauthors": [],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
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                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36035/galley/26887/download/"
                }
            ]
        },
        {
            "pk": 26765,
            "title": "A Cognitive Approach to Modeling Sentence Level Prominence Based on StimulusUnpredictability",
            "subtitle": null,
            "abstract": "The human sensory system is capable to rapidly respond to novel input, allowing for quick allocation of attentionalresources to the stimulus. In a similar manner, prominent words in speech seem to attract the listeners’ attention and facilitate oralter interpretation. Sentence prominence has been typically studied across languages by examining configurations of acousticprosodic features during prominent words. Recent studies have provided evidence that, in addition to the predictability of thelexical units in speech, manipulating the predictability of the acoustic prosodic features can also signal prominence. In thiswork, we provide a high-level description of a cognitive framework that attempts to characterize sentence prominence as aphenomenon that is connected with the unpredictability of suprasegmental acoustic features, thereby capturing the attention ofthe listener and causing differential processing of prominent speech.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/37q4q24r",
            "frozenauthors": [
                {
                    "first_name": "Sofoklis",
                    "middle_name": "",
                    "last_name": "Kakouros",
                    "name_suffix": "",
                    "institution": "Aalto University",
                    "department": ""
                },
                {
                    "first_name": "Okko",
                    "middle_name": "",
                    "last_name": "Rasanen",
                    "name_suffix": "",
                    "institution": "Aalto University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26765/galley/16401/download/"
                }
            ]
        },
        {
            "pk": 26722,
            "title": "A Cognitively Realistic Model of Decision Making in Ocean Ecology",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7vz8643v",
            "frozenauthors": [
                {
                    "first_name": "Philipp",
                    "middle_name": "",
                    "last_name": "Koralus",
                    "name_suffix": "",
                    "institution": "",
                    "department": ""
                },
                {
                    "first_name": "Jens",
                    "middle_name": "",
                    "last_name": "Madsen",
                    "name_suffix": "",
                    "institution": "",
                    "department": ""
                },
                {
                    "first_name": "Ernesto",
                    "middle_name": "",
                    "last_name": "Carella",
                    "name_suffix": "",
                    "institution": "",
                    "department": ""
                },
                {
                    "first_name": "Richard",
                    "middle_name": "",
                    "last_name": "Bailey",
                    "name_suffix": "",
                    "institution": "",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
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                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26722/galley/16358/download/"
                }
            ]
        },
        {
            "pk": 26578,
            "title": "A Cognitive Model of Fraction Arithmetic",
            "subtitle": null,
            "abstract": "Learning about fractions is a critical step on the path to high school mathematics, yet many children never masterbasic knowledge such as fraction arithmetic procedures. To better understand these difficulties, the present study describes acomputational model of fraction arithmetic problem solving. The model demonstrates that the majority of empirically observederrors over all four arithmetic operations can be explained by only two error-generating mechanisms – overgeneralization andrepair. Further, by assuming probabilistic selection of solution procedures using associative strengths learned from experience,the model predicts two other empirical phenomena: (1) variation in error rates and relative frequencies of specific errorsas a function of problem features, and (2) variable strategy selection within and between problems and individuals. Beyondproviding a formal account of errors, the model was used to simulate the effects of variation of instructional parameters, leadingto novel predictions regarding potentially effective instructional designs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/27k5d5qh",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Braithwaite",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "",
                    "last_name": "Siegler",
                    "name_suffix": "",
                    "institution": "Carnegie Mellon University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26578/galley/16214/download/"
                }
            ]
        },
        {
            "pk": 26661,
            "title": "A cognitive model of online event segmentation",
            "subtitle": null,
            "abstract": "People automatically segment online perceptual and conceptual experiences into events (Newston, 1973). A newmodel-based theory explains how people construct temporal markers and prioritize those changes to build representations ofevents (Khemlani et al., 2015). The theory is implemented within an embodied extension of the ACT-R cognitive architecture(Anderson, 2007) called ACT-R/E (Trafton et al., 2013). Its principal parameter is the prioritization scheme by which certaindetectable changes (e.g., in a perceived location) are preferred over others (e.g., in perceived states of an object). We tested thepredictions of the theory and its computational model against an experiment on narrative event segmentation. Participants in thestudy read an excerpt of text and were asked to assess whether certain lines marked the start of a new event. The computationalmodel readily accounted for their segmentation behavior. We conclude by discussing event segmentation and its relation toembodied cognition and cognitive robotics.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5h53t5qf",
            "frozenauthors": [
                {
                    "first_name": "Anthony",
                    "middle_name": "",
                    "last_name": "Harrison",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Sangeet",
                    "middle_name": "",
                    "last_name": "Khemlani",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Greg",
                    "middle_name": "",
                    "last_name": "Trafton",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26661/galley/16297/download/"
                }
            ]
        },
        {
            "pk": 26363,
            "title": "A Comparative Evaluation of Approximate Probabilistic Simulation and DeepNeural Networks as Accounts of Human Physical Scene Understanding",
            "subtitle": null,
            "abstract": "Humans demonstrate remarkable abilities to predict physicalevents in complex scenes. Two classes of models for physicalscene understanding have recently been proposed: “IntuitivePhysics Engines”, or IPEs, which posit that people make pre-dictions by running approximate probabilistic simulations incausal mental models similar in nature to video-game physicsengines, and memory-based models, which make judgmentsbased on analogies to stored experiences of previously en-countered scenes and physical outcomes. Versions of the lat-ter have recently been instantiated in convolutional neural net-work (CNN) architectures. Here we report four experimentsthat, to our knowledge, are the first rigorous comparisonsof simulation-based and CNN-based models, where both ap-proaches are concretely instantiated in algorithms that can runon raw image inputs and produce as outputs physical judg-ments such as whether a stack of blocks will fall. Both ap-proaches can achieve super-human accuracy levels and canquantitatively predict human judgments to a similar degree,but only the simulation-based models generalize to novel sit-uations in ways that people do, and are qualitatively consis-tent with systematic perceptual illusions and judgment asym-metries that people show.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "physical scene understanding; neural network;analysis by synthesis; simulation engine; blocks world"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4bd5068b",
            "frozenauthors": [
                {
                    "first_name": "Renqiao",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Jiajun",
                    "middle_name": "",
                    "last_name": "Wu",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Chengkai",
                    "middle_name": "",
                    "last_name": "Zhang",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "William",
                    "middle_name": "T.",
                    "last_name": "Freeman",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "B.",
                    "last_name": "Tenenbaum",
                    "name_suffix": "",
                    "institution": "Massachusetts Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26363/galley/15999/download/"
                }
            ]
        },
        {
            "pk": 26106,
            "title": "A Computational Exploration of Problem-Solving Strategies and Gaze Behaviorson the Block Design Task",
            "subtitle": null,
            "abstract": "The block design task, a standardized test of nonverbal reason-ing, is often used to characterize atypical patterns of cognitionin individuals with developmental or neurological conditions.Many studies suggest that, in addition to looking at quantita-tive differences in block design speed or accuracy, observingqualitative differences in individuals’ problem-solving strate-gies can provide valuable information about a person’s cogni-tion. However, it can be difficult to tie theories at the levelof problem-solving strategy to predictions at the level of ex-ternally observable behaviors such as gaze shifts and patternsof errors. We present a computational architecture that is usedto compare different models of problem-solving on the blockdesign task and to generate detailed behavioral predictions foreach different strategy. We describe the results of three differ-ent modeling experiments and discuss how these results pro-vide greater insight into the analysis of gaze behavior and errorpatterns on the block design task.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "artificial intelligence; cognitive assessment; non-verbal intelligence; spatial reasoning; visual attention."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9xw093cn",
            "frozenauthors": [
                {
                    "first_name": "Maithilee",
                    "middle_name": "",
                    "last_name": "Kunda",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "Mohamed",
                    "middle_name": "El",
                    "last_name": "Banani",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                },
                {
                    "first_name": "James",
                    "middle_name": "M.",
                    "last_name": "Rehg",
                    "name_suffix": "",
                    "institution": "Georgia Institute of Technology",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26106/galley/15742/download/"
                }
            ]
        },
        {
            "pk": 26438,
            "title": "A computational investigation of the Sapir-Whorf hypothesis:The case of spatial relations",
            "subtitle": null,
            "abstract": "Investigations of the Sapir-Whorf hypothesis often ask whetherthere is a difference in the non-linguistic behavior of speak-ers of two languages, generally without modeling the underly-ing process. Such an approach leaves underexplored the rela-tive contributions of language and universal aspects of cogni-tion, and how those contributions differ across languages. Weexplore the naming and non-linguistic pile-sorting of spatialscenes across speakers of five languages via a computationalmodel grounded in an influential proposal: that language willaffect cognition when non-linguistic information is uncertain.We report two findings. First, native language plays a smallbut significant role in predicting spatial similarity judgmentsacross languages, consistent with earlier findings. Second, thesize of the native-language role varies systematically, such thatfiner-grained semantic systems appear to shape similarity judg-ments more than coarser-grained systems do. These findingscapture the tradeoff between language-specific and universalforces in cognition, and how that tradeoff varies across lan-guages.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Linguistic relativity; Sapir-Whorf hypothesis; se-mantic universals; name strategy; categorization; spatial rela-tions; computational models."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3vj0k88n",
            "frozenauthors": [
                {
                    "first_name": "Christine",
                    "middle_name": "",
                    "last_name": "Tseng",
                    "name_suffix": "",
                    "institution": "California Institute of Technology, Pasadena",
                    "department": ""
                },
                {
                    "first_name": "Alexandra",
                    "middle_name": "",
                    "last_name": "Carstensen",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Terry",
                    "middle_name": "",
                    "last_name": "Regier",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Yang",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26438/galley/16074/download/"
                }
            ]
        },
        {
            "pk": 26414,
            "title": "A Computational Model of Perceptual Deficits in Medial Temporal Lobe Amnesia",
            "subtitle": null,
            "abstract": "Damage to the Medial Temporal Lobe (MTL) impairs declar-\native memory and perception. The Representational-Hierar-\nchical (RH) Account explains such impairments by assuming\nthat MTL stores conjunctive representations of items and\nevents, and that individuals with MTL damage must rely upon\nrepresentations of simple visual features in posterior visual\ncortex. A recent study revealed a surprising anti-perceptual\nlearning effect in MTL-damaged individuals: with exposure to\na set of visual stimuli, discrimination performance worsened\nrather than improved. We expand the RH account to explain\nthis paradox by assuming that visual discrimination is per-\nformed using a familiarity heuristic. Exposure to a set of highly\nsimilar stimuli entails repeated presentation of simple visual\nfeatures, eventually rendering all feature representations\nequally (maximally) familiar and hence inutile for solving the\ntask. Since the unique conjunctions represented in MTL do not\noccur repeatedly, healthy individuals are shielded from this\nperceptual interference. We simulate this mechanism with a\nneural network previously used to simulate recognition\nmemory, thereby providing a model that accounts for both\nmnemonic and perceptual deficits caused by MTL damage us-\ning a unified architecture and mechanism.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neural Network; memory; visual perception; Me-\ndial Temporal Lobe; hierarchical object representations"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4578d8qs",
            "frozenauthors": [
                {
                    "first_name": "Patrick",
                    "middle_name": "",
                    "last_name": "Sadil",
                    "name_suffix": "",
                    "institution": "University of Massachusetts",
                    "department": ""
                },
                {
                    "first_name": "Rosemary",
                    "middle_name": "A.",
                    "last_name": "Cowell",
                    "name_suffix": "",
                    "institution": "University of Massachusetts",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26414/galley/16050/download/"
                }
            ]
        },
        {
            "pk": 26558,
            "title": "A computational theory of temporal inference",
            "subtitle": null,
            "abstract": "We describe a novel model-based theory of how individuals reason deductively about temporal relations. It positsthat temporal assertions refer to mental models – iconic representations of possibilities – of events (Khemlani, Harrison, &Trafton, 2015; Schaeken, Johnson-Laird, & d’Ydewalle, 1996). In line with recent accounts of spatial reasoning (Ragni &Knauff, 2013), the theory posits that individuals tend to build a single preferred model of a temporal description. The moremodels necessary to yield a correct answer, the harder that problem is. The theory is implemented in a computer program,mReasoner, which draws temporal deductions by building models. It varies four separate factors in the process: the size of amodel, its contents, the propensity to consider alternative models, and the propensity to revise initial conclusions. Two studiescorroborated the predictions of the theory and its computational implementation. We conclude by discussing temporal andrelational inference more broadly.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0kh7m7wj",
            "frozenauthors": [
                {
                    "first_name": "Sangeet",
                    "middle_name": "",
                    "last_name": "Khemlani",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Anthony",
                    "middle_name": "",
                    "last_name": "Harrison",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Greg",
                    "middle_name": "",
                    "last_name": "Trafton",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26558/galley/16194/download/"
                }
            ]
        },
        {
            "pk": 26679,
            "title": "A concurrent task facilitates, not impedes, the heel-to-toe standing balance inchildren: The case of a dual-task benefit",
            "subtitle": null,
            "abstract": "Performance in a dual task is typically worse than performance in a single task due to the sharing of limited cognitivecapacity. The present study found the opposite results when the task involved postural control in non-typical standing. Thirty-six children aged 4-9 years stood on a force plate for 10 seconds with a normal or heel-to-toe stance. In the dual-task condition,they also performed an auditory or a visuospatial task. They were instructed to achieve high accuracy on the concurrent taskwhile maintaining balance. Standing balance, expressed in terms of the velocity and the trajectory of the center of pressureon the force plate, was significantly better in the dual-task than in the single-task condition. Performances on the concurrenttasks were also better in the dual-task condition. The overall dual-task benefits are attributed to the increased deployment ofcognitive capacity specially called for by the balance challenge in non-typical standing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7w12j0pk",
            "frozenauthors": [
                {
                    "first_name": "Rong-Ju",
                    "middle_name": "",
                    "last_name": "Cherng",
                    "name_suffix": "",
                    "institution": "National Cheng Kung University",
                    "department": ""
                },
                {
                    "first_name": "Hsien-Ying",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "National Cheng Kung University",
                    "department": ""
                },
                {
                    "first_name": "Chiu-Yu",
                    "middle_name": "",
                    "last_name": "Cho",
                    "name_suffix": "",
                    "institution": "National Cheng Kung University",
                    "department": ""
                },
                {
                    "first_name": "Jenn-Yeu",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "National Taiwan Normal University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26679/galley/16315/download/"
                }
            ]
        },
        {
            "pk": 26147,
            "title": "A connectionist model for automatic generation of child-adult interaction patterns",
            "subtitle": null,
            "abstract": "This study introduces a neural network that models thesocial interactions from a video corpus. The corpusconsists of recordings of naturalistic observations ofsocial interactions among children and theirenvironment. The videos are annotated multimodallyincluding features like gestures. We explore how thisvideo corpus can be utilized for modelling by trainingour model on a portion of the annotated data extractedfrom the corpus, and then by using the model to predictnovel interaction sequences. We evaluate our model bycomparing its automatically generated sequences to anunseen portion of the corpus data. The initial resultsshow strong similarities between the generatedinteractions and those observed in the corpus.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Neural Networks; Child Language Acquisition;Sequence Generation; Modelling Social Interactions."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4wf2k0rb",
            "frozenauthors": [
                {
                    "first_name": "Moinuddin",
                    "middle_name": "M.",
                    "last_name": "Haque",
                    "name_suffix": "",
                    "institution": "Tilburg University",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Vogt",
                    "name_suffix": "",
                    "institution": "Tilburg University",
                    "department": ""
                },
                {
                    "first_name": "Afra",
                    "middle_name": "",
                    "last_name": "Alishahi",
                    "name_suffix": "",
                    "institution": "Tilburg University",
                    "department": ""
                },
                {
                    "first_name": "Emiel",
                    "middle_name": "",
                    "last_name": "Krahmer",
                    "name_suffix": "",
                    "institution": "Tilburg University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26147/galley/15783/download/"
                }
            ]
        },
        {
            "pk": 26518,
            "title": "A cross-linguistic investigation on the acquisition of complex numerals",
            "subtitle": null,
            "abstract": "Complex numerals (e.g., four hundred) have a multiplicative\nstructure (four hundred = 4 x 100). This paper investigates\nwhether children are sensitive to the meaning of the\nmultiplicative structure. We designed a novel word learning\nparadigm and taught 4- to 6-year-old children the meaning of\na novel numeral phrase (e.g., ‘one gobi houses’ to mean a\ngroup of three houses). We then asked whether they could\ngeneralize it to a novel context (e.g., ‘two gobi butterflies’ to\nmean two groups of three). Experiment 1 showed that only\nEnglish-speaking children who received multiplier syntax\ntraining were able to generalize. Experiment 2 extended\nfindings from Experiment 1 to Cantonese-speaking children\nand found that they could also generalize a novel multiplier to\nnovel contexts. These results suggest that children as young\nas 4 can create a mapping between the structure of complex\nnumerals and a multiplicative meaning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "complex numerals"
                },
                {
                    "word": "digits"
                },
                {
                    "word": "multipliers"
                },
                {
                    "word": "Syntax"
                },
                {
                    "word": "Semantics"
                },
                {
                    "word": "preschoolers"
                },
                {
                    "word": "cross-linguistic investigation"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5dr9j89d",
            "frozenauthors": [
                {
                    "first_name": "Pierina",
                    "middle_name": "",
                    "last_name": "Cheung",
                    "name_suffix": "",
                    "institution": "Wesleyan University",
                    "department": ""
                },
                {
                    "first_name": "Meghan",
                    "middle_name": "",
                    "last_name": "Dale",
                    "name_suffix": "",
                    "institution": "Queen’s University",
                    "department": ""
                },
                {
                    "first_name": "Mathieu",
                    "middle_name": "Le",
                    "last_name": "Corre",
                    "name_suffix": "",
                    "institution": "Universidad Autónoma del Estado de Morelos",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26518/galley/16154/download/"
                }
            ]
        },
        {
            "pk": 26512,
            "title": "Active control of study leads to improved recognition memory in children",
            "subtitle": null,
            "abstract": "This paper reports an experiment testing whether volitionalcontrol over the presentation of stimuli leads to enhancedrecognition memory in 6- to 8-year-old children. Childrenwere presented with a simple memory game on an iPad.During the study phase, for half of the materials childrencould decide the order and pacing of stimuli presentation(active condition). For the other half of the materials, childrenobserved the study choices of another child (yokedcondition). We found that recognition performance was betterfor the objects studied in the active condition as compared tothe yoked condition. Furthermore, we found that the memoryadvantages of active learning persisted over a one-week delaybetween study and test. Our results support pedagogicalapproaches that emphasize self-guided learning and show thateven young children benefit from being able to control howthey learn.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "active learning"
                },
                {
                    "word": "recognition memory"
                },
                {
                    "word": "Exploration"
                },
                {
                    "word": "metacognition"
                },
                {
                    "word": "inquiry learning"
                },
                {
                    "word": "cognitive development."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5jr4w11v",
            "frozenauthors": [
                {
                    "first_name": "Azzurra",
                    "middle_name": "",
                    "last_name": "Ruggeri",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development, University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Douglas",
                    "middle_name": "",
                    "last_name": "Markant",
                    "name_suffix": "",
                    "institution": "Max Planck Institute for Human Development",
                    "department": ""
                },
                {
                    "first_name": "Todd",
                    "middle_name": "",
                    "last_name": "Gureckis",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Fei",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26512/galley/16148/download/"
                }
            ]
        },
        {
            "pk": 26054,
            "title": "Active learning: Cognitive development, education, and computational models",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "active learning"
                },
                {
                    "word": "Exploration"
                },
                {
                    "word": "information gain"
                },
                {
                    "word": "computational models"
                },
                {
                    "word": "education"
                }
            ],
            "section": "Workshops",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7g5039n2",
            "frozenauthors": [
                {
                    "first_name": "Elizabeth",
                    "middle_name": "",
                    "last_name": "Bonawitz",
                    "name_suffix": "",
                    "institution": "Rutgers University",
                    "department": ""
                },
                {
                    "first_name": "Fei",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California – Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26054/galley/15690/download/"
                }
            ]
        },
        {
            "pk": 26429,
            "title": "Active Overhearing:Development in Preschoolers’ Skill at ‘Listening in’ to Naturalistic Overheard Speech",
            "subtitle": null,
            "abstract": "Overhearing can be seen as active learning, and overheardspeech provides an increasingly viable source of linguisticinput across development. This study extends previous re-sults showing learning from overhearing simplified, pedagogicspeech to a more ecologically valid context. Children learnmultiple words and facts corresponding to novel toys eitherthrough an overheard phone call or through direct instruction.Remarkably, 4.5–6-year-olds learned four new words equallywell in both conditions. Their performance on a set of six factswas even better, especially when taught directly. Analysis ofthe videos revealed that older children with high test accuracyboth looked toward the experimenter often, and tracked ob-jects as she discussed them. 3–4.5-year-olds only learned factsfrom overhearing, and exhibited greater varability in attention.These results suggest learning from overhearing is driven byattention to the indirect input, and may be a skill that under-goes substantial development during the preschool years.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "active learning; lexical development; overhearing"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2s21g88s",
            "frozenauthors": [
                {
                    "first_name": "Ruthe",
                    "middle_name": "",
                    "last_name": "Foushee",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Fei",
                    "middle_name": "",
                    "last_name": "Xu",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26429/galley/16065/download/"
                }
            ]
        },
        {
            "pk": 26338,
            "title": "Active Viewing in Toddlers Facilitates Visual Object Learning:An Egocentric Vision Approach",
            "subtitle": null,
            "abstract": "Early visual object recognition in a world full of cluttered vi-sual information is a complicated task at which toddlers areincredibly efficient. In their everyday lives, toddlers con-stantly create learning experiences by actively manipulatingobjects and thus self-selecting object views for visual learn-ing. The work in this paper is based on the hypothesis that ac-tive viewing and exploration of toddlers actually creates high-quality training data for object recognition. We tested thisidea by collecting egocentric video data of free toy play be-tween toddler-parent dyads, and used it to train state-of-the-artmachine learning models (Convolutional Neural Networks, orCNNs). Our results show that the data collected by parentsand toddlers have different visual properties and that CNNscan take advantage of these differences to learn toddler-basedobject models that outperform their parent counterparts in aseries of controlled simulations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "vision"
                },
                {
                    "word": "visual object learning"
                },
                {
                    "word": "convolutional neuralnetworks"
                },
                {
                    "word": "head-mounted cameras"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2xq2h5kq",
            "frozenauthors": [
                {
                    "first_name": "Sven",
                    "middle_name": "",
                    "last_name": "Bambach",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "J.",
                    "last_name": "Crandall",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Linda",
                    "middle_name": "B.",
                    "last_name": "Smith",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                },
                {
                    "first_name": "Chen",
                    "middle_name": "",
                    "last_name": "Yu",
                    "name_suffix": "",
                    "institution": "Indiana University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26338/galley/15974/download/"
                }
            ]
        },
        {
            "pk": 26460,
            "title": "Adapting Deep Network Features to Capture Psychological Representations",
            "subtitle": null,
            "abstract": "Deep neural networks have become increasingly successful atsolving classic perception problems such as object recognition,semantic segmentation, and scene understanding, often reach-ing or surpassing human-level accuracy. This success is duein part to the ability of DNNs to learn useful representationsof high-dimensional inputs, a problem that humans must alsosolve. We examine the relationship between the representa-tions learned by these networks and human psychological rep-resentations recovered from similarity judgments. We find thatdeep features learned in service of object classification accountfor a significant amount of the variance in human similarityjudgments for a set of animal images. However, these fea-tures do not capture some qualitative distinctions that are a keypart of human representations. To remedy this, we develop amethod for adapting deep features to align with human sim-ilarity judgments, resulting in image representations that canpotentially be used to extend the scope of psychological exper-iments.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "deep learning; neural networks; psychologicalrepresentations; similarity"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/63c047pd",
            "frozenauthors": [
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Peterson",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Joshua",
                    "middle_name": "",
                    "last_name": "Abbott",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26460/galley/16096/download/"
                }
            ]
        },
        {
            "pk": 36024,
            "title": "Addressing the Needs of 21st-Century Teachers Working With Culturally and Linguistically Diverse Learners",
            "subtitle": null,
            "abstract": "Preparing mainstream classroom teachers to work with culturally and linguistically diverse learners is a growing concern in\neducation as more and more schools host increasing numbers of\nstudents whose primary language is not English. Unfortunately,\nsignificant numbers of teachers have had little preparation for\nworking with these diverse learners and feel ill equipped to support their academic development. This mixed-methods case study\nexplores the longitudinal impact of a professional-development\nprogram designed to increase teachers’ knowledge of second language acquisition and of appropriate instructional practices for\nsupporting English language learners (ELLs). Findings suggest\nthat participation in the program had a positive effect on participants’ knowledge of language and literacy acquisition, their ability\nto plan and manage instruction for ELLs, their understanding of\nappropriate assessment for ELLs, and their classroom practice. A\nyear later, though focal participants claimed maintenance, these\neffects were only marginally present in their classroom practice.",
            "language": "eng",
            "license": null,
            "keywords": [],
            "section": "Regular Article",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/21j6f1rd",
            "frozenauthors": [
                {
                    "first_name": "Xenia",
                    "middle_name": "",
                    "last_name": "Hadjioannou",
                    "name_suffix": "",
                    "institution": "Penn State University,\nLehigh Valley Campus",
                    "department": ""
                },
                {
                    "first_name": "Mary",
                    "middle_name": "C.",
                    "last_name": "Hutchinson",
                    "name_suffix": "",
                    "institution": "Penn State University,\nLehigh Valley Campus",
                    "department": ""
                },
                {
                    "first_name": "Marisa",
                    "middle_name": "",
                    "last_name": "Hockman",
                    "name_suffix": "",
                    "institution": "Penn State University,\nLehigh Valley Campus",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/catesoljournal/article/36024/galley/26876/download/"
                }
            ]
        },
        {
            "pk": 26103,
            "title": "A Deep Siamese Neural Network Learns the Human-Perceived SimilarityStructure of Facial Expressions Without Explicit Categories",
            "subtitle": null,
            "abstract": "In previous work, we showed that a simple neurocomputa-tional model The Model, or TM) trained on the Ekman &Friesen Pictures of Facial Affect (POFA) dataset to catego-rize the images into the six basic expressions can account forwide array of data (albeit from a single study) on facial ex-pression processing. The model demonstrated categorical per-ception of facial expressions, as well as the so-called facialexpression circumplex, a circular configuration based on MDSresults that places the categories in the order happy, surprise,fear, sadness, anger and disgust. Somewhat ironically, the cir-cumplex in TM was generated from the similarity between thecategorical outputs of the network, i.e., the six numbers rep-resenting the probability of the category given the face. Here,we extend this work by 1) using a new dataset, NimsStims,that is much larger than POFA, and is not as tightly controlledfor the correct Facial Action Units; 2) using a completely dif-ferent neural network architecture, a Siamese Neural Network(SNN) that maps two faces through twin networks into a 2Dsimilarity space; and 3) training the network only implicitly,based on a teaching signal that pairs of faces are in either inthe same or different categories. Our results show that in thissetting, the network learns a representation that is very similarto the original circumplex. Fear and surprise overlap, whichis consistent with the inherent confusability between these twofacial expressions. Our results suggest that humans evolvedin such a way that nearby emotions are represented by similarappearances.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "facial expressions; similarity structure; deepsiamese neural network; multidimensional scaling (MDS); fa-cial expression circumplex"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6n45n1cf",
            "frozenauthors": [
                {
                    "first_name": "Sanjeev",
                    "middle_name": "Jagannatha",
                    "last_name": "Rao",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                },
                {
                    "first_name": "Yufei",
                    "middle_name": "",
                    "last_name": "Wang",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                },
                {
                    "first_name": "Garrison",
                    "middle_name": "W",
                    "last_name": "Cottrell",
                    "name_suffix": "",
                    "institution": "University of California San Diego",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26103/galley/15739/download/"
                }
            ]
        },
        {
            "pk": 26591,
            "title": "ADHD modulates link between event processing and recall",
            "subtitle": null,
            "abstract": "How might ADHD symptomatology influence adults’ ability to process and recall the actions of others? Universityundergraduates observed a woman packing a suitcase by advancing through a self-paced slide show of still images extractedfrom a digital video, and were then asked to recall as many actions as possible. Results showed that lower self-reported retro-spective ADHD symptomatology was associated with a) longer overall dwelling on images from the slideshow, r(91) = -.315,p=.002, and b) recall of more actions r(85) = -.237, p=01. Further, exploratory analyses indicated that ADHD symptomatologymodulated the specific linkage between dwell time patterns and stronger recall: Attention to fine-grain details within activityimproved recall for those reporting higher ADHD symptomatology; those reporting lower ADHD symptomatology displayedstronger recall when prioritizing attention at a more coarse-grain level, F(1,83) = 4.19, p=.04. These findings offer suggestivenovel evidence that ADHD has implications for event processing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8xp3x3fm",
            "frozenauthors": [
                {
                    "first_name": "Robbie",
                    "middle_name": "",
                    "last_name": "Ross",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                },
                {
                    "first_name": "Leah",
                    "middle_name": "",
                    "last_name": "Child",
                    "name_suffix": "",
                    "institution": "University of Chicago",
                    "department": ""
                },
                {
                    "first_name": "Dare",
                    "middle_name": "",
                    "last_name": "Baldwin",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26591/galley/16227/download/"
                }
            ]
        },
        {
            "pk": 26333,
            "title": "A Dream Model: Reactivation and Re-encoding Mechanisms for Sleep-dependentMemory Consolidation",
            "subtitle": null,
            "abstract": "We humans spend almost a third of our lives asleep, andthere is mounting evidence that sleep not only maintains, butactually improves many of our cognitive functions. Mem-ory consolidation–the process of crystallizing and integratingmemories into knowledge and skills–is particularly benefittedby sleep. We survey the evidence that sleep aids memory con-solidation in various declarative and implicit tasks and reviewthe basic neurophysiological structure of sleep with a focus onunderstanding what neural systems are involved. Drawing onmachine learning research, we discuss why it might be usefulfor humans–and robots, perhaps–to have such an offline pe-riod for processing, even though humans are clearly capable oflearning incrementally, online. Finally, we propose and simu-late two mechanisms for use in computational memory modelsto accomplish sleep-based consolidation via either or both 1)re-encoding knowledge representations and 2) reactivating andstrengthening recent memories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "memory consolidation; sleep; dreaming; hip-pocampal replay; memory model"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9ns183zb",
            "frozenauthors": [
                {
                    "first_name": "George",
                    "middle_name": "",
                    "last_name": "Kachergis",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Roy",
                    "middle_name": "de",
                    "last_name": "Kleijn",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                },
                {
                    "first_name": "Bernhard",
                    "middle_name": "",
                    "last_name": "Hommel",
                    "name_suffix": "",
                    "institution": "Leiden University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26333/galley/15969/download/"
                }
            ]
        },
        {
            "pk": 26653,
            "title": "Adults’ drawing and recognition of familiar objects and substances: Nonsolids are hard to identify",
            "subtitle": null,
            "abstract": "In English, categories of solid objects (e.g., couch) are similar in shape, but vary in color and material; categories ofnonsolid substances (e.g., yogurt) are similar in material, but vary in color and shape (Samuelson & Smith, 1999). Althougheven infants can discriminate between how solids and nonsolids should behave (Hespos et al., 2009), increasing evidencesuggests recognizing specific substances is difficult for children (Perry et al., 2014). This begs the question, what do adults evenknow about nonsolids? Twenty adults drew 23 familiar solids and nonsolids. 116 participants from Amazon Mechanical Turkattempted to identify each drawing. Participants more accurately identified drawings of solids (M=.70) than nonsolids (M=.25),X2(1)=13.87, p=.0002. Drawings of nonsolids leading to accurate identification often depicted prototypical containers (e.g.,milk carton). These results suggest visual recognition—even of nonsolids—is aided by shape and that adults may conceptualizenonsolids as more object-like than was previously thought.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6k57v97z",
            "frozenauthors": [
                {
                    "first_name": "Lynn",
                    "middle_name": "",
                    "last_name": "Perry",
                    "name_suffix": "",
                    "institution": "University of Miami",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26653/galley/16289/download/"
                }
            ]
        },
        {
            "pk": 26538,
            "title": "Adults’ guesses on probabilistic tasks reveal incremental representativeness biases",
            "subtitle": null,
            "abstract": "Participants in most binary-choice tasks with multiple trialstend to probability-match (Vulkan, 2000) — i.e., provide re-sponses that match the probability distribution of the presentedpopulation. Given a single trial, however, participants usuallychoose the majority option (James & Koehler, 2011). By us-ing a method that visually presents the probabilities of the twocompeting options, we examine responses when participantsare given only a single trial, and initial responses when partic-ipants are given multiple trials. While we still observe aggre-gate probability-matching in the multiple-trial condition, wefind robust sequence effects in participants’ initial responses,including robust maximizing behavior on the first response.This suggests that both maximizing in single-trial experimentsand aggregate probability-matching in multiple-trial ones canbe explained by a single, underlying mechanism; one thatseeks to provide a representative sample at each point duringsequence generation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Decision making; statistics; psychology; humanexperimentation; probability-matching; maximizing."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4vp9n4wm",
            "frozenauthors": [
                {
                    "first_name": "Habiba",
                    "middle_name": "",
                    "last_name": "Azab",
                    "name_suffix": "",
                    "institution": "Meliora Hall",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Ruskin",
                    "name_suffix": "",
                    "institution": "Meliora Hall",
                    "department": ""
                },
                {
                    "first_name": "Celeste",
                    "middle_name": "",
                    "last_name": "Kidd",
                    "name_suffix": "",
                    "institution": "Meliora Hall",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26538/galley/16174/download/"
                }
            ]
        },
        {
            "pk": 26151,
            "title": "A Dynamic Neural Field Model of Speech Cue Compensation",
            "subtitle": null,
            "abstract": "Categorical speech content can often be perceived directlyfrom continuous auditory cues in the speech stream, buthuman-level performance on speech recognition tasksrequires compensation for contextual variables like speakeridentity. Regression modeling by McMurray and Jongman(2011) has suggested that for many fricative phonemes, acompensation scheme can substantially increasecategorization accuracy beyond even the information from 24un-compensated raw speech cues. Here, we simulate thesame dataset instead using a neurally rather than abstractlyimplemented model: a hybrid dynamic neural field model andconnectionist network. Our model achieved slightly loweraccuracy than McMurray and Jongman’s but similar accuracypatterns across most fricatives. Results also comparedsimilarly to more recent models that were also less neurallyinstantiated but somewhat closer fitting to humans inaccuracy. An even less abstracted model is an immediatefuture goal, as is expanding the present model to additionalsensory modalities and constancy/compensation effects.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Speech recognition"
                },
                {
                    "word": "concepts and categories"
                },
                {
                    "word": "Neural Networks"
                },
                {
                    "word": "Dynamic Systems Modeling"
                },
                {
                    "word": "psychology"
                },
                {
                    "word": "Linguistics"
                },
                {
                    "word": "Cognitive Science"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7pp5359f",
            "frozenauthors": [
                {
                    "first_name": "Gavin",
                    "middle_name": "W.",
                    "last_name": "Jenkins",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Tupper",
                    "name_suffix": "",
                    "institution": "Simon Fraser University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26151/galley/15787/download/"
                }
            ]
        },
        {
            "pk": 26386,
            "title": "A Framework for Evaluating Speech Representations",
            "subtitle": null,
            "abstract": "Listeners track distributions of speech sounds along percep-tual dimensions. We introduce a method for evaluating hy-potheses about what those dimensions are, using a cognitivemodel whose prior distribution is estimated directly from speechrecordings. We use this method to evaluate two speaker nor-malization algorithms against human data. Simulations showthat representations that are normalized across speakers predicthuman discrimination data better than unnormalized representa-tions, consistent with previous research. Results further revealdifferences across normalization methods in how well eachpredicts human data. This work provides a framework forevaluating hypothesized representations of speech and lays thegroundwork for testing models of speech perception on naturalspeech recordings from ecologically valid settings.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Speech perception"
                },
                {
                    "word": "speaker normalization"
                },
                {
                    "word": "Bayesian modeling"
                },
                {
                    "word": "approximate inference"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5m3610p8",
            "frozenauthors": [
                {
                    "first_name": "Caitlin",
                    "middle_name": "",
                    "last_name": "Richter",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Naomi",
                    "middle_name": "",
                    "last_name": "Feldman",
                    "name_suffix": "",
                    "institution": "University of Maryland",
                    "department": ""
                },
                {
                    "first_name": "Harini",
                    "middle_name": "",
                    "last_name": "Salgado",
                    "name_suffix": "",
                    "institution": "Pomona College",
                    "department": ""
                },
                {
                    "first_name": "Aren",
                    "middle_name": "",
                    "last_name": "Jansen",
                    "name_suffix": "",
                    "institution": "Johns Hopkins University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26386/galley/16022/download/"
                }
            ]
        },
        {
            "pk": 26758,
            "title": "Age Related Differences in Episodic Memory Recollections: Applying LatentDirichlet Allocation to Free-Writings on Driving Incidents by Older and YoungDrivers",
            "subtitle": null,
            "abstract": "Reporting driving incidents depends on episodic memories formed at a certain time point in the past, and its retrievalwith subjective feelings. This study examined aging effects on episodic memory recollections by analyzing free writing reportsby older and young drivers. Unstructured hand-writing samples from 199 older (Mage = 69.2) long-experienced (Mdriving =43.0 years), and 299 young (Mage = 21.5) novice (Mdriving = 2.2 years) drivers were avalyzed by Latent Dirichlet Allocation.This identified a 6-topic model labeled: (1) operational failures, (2) control aspects, (3) other vehicles, (4) jump-outs, (5) trafficlights, and (6) attention. Posterior distribution analysis revealed that older drivers reported less in topics concerning own drivingoperations. In addition, older drivers less attributed these topics to self than environment relative to young drivers. The agedifferences of episodic memory retrieval for free reports and applicability of natural language processing to psychology arediscussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4s49c0tw",
            "frozenauthors": [
                {
                    "first_name": "Ritsuko",
                    "middle_name": "",
                    "last_name": "Iwai",
                    "name_suffix": "",
                    "institution": "Kyoto University , RIKEN",
                    "department": ""
                },
                {
                    "first_name": "Takatsune",
                    "middle_name": "",
                    "last_name": "Kumada",
                    "name_suffix": "",
                    "institution": "Kyoto University , RIKEN",
                    "department": ""
                },
                {
                    "first_name": "Daisuke",
                    "middle_name": "",
                    "last_name": "Kawahara",
                    "name_suffix": "",
                    "institution": "Kyoto University",
                    "department": ""
                },
                {
                    "first_name": "Sadao",
                    "middle_name": "",
                    "last_name": "Kurohashi",
                    "name_suffix": "",
                    "institution": "Kyoto University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26758/galley/16394/download/"
                }
            ]
        },
        {
            "pk": 26276,
            "title": "A Hierarchical Probabilistic Language-of-Thought Modelof Human Visual Concept Learning",
            "subtitle": null,
            "abstract": "How do people rapidly learn rich, structured concepts fromsparse input? Recent approaches to concept learning havefound success by integrating rules and statistics. We describe ahierarchical model in this spirit in which the rules are stochas-tic, generative processes, and the rules themselves arise froma higher-level stochastic, generative process. We evaluate thisprobabilistic language-of-thought model with data from an ab-stract rule learning experiment carried out with adults. In thisexperiment, we find novel generalization effects, and we showthat the model gives a qualitatively good account of the exper-imental data. We then discuss the role of this kind of model inthe larger context of concept learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Probabilistic language of thought"
                },
                {
                    "word": "Bayesian infer-ence"
                },
                {
                    "word": "abstract rule learning"
                },
                {
                    "word": "Computational Model"
                },
                {
                    "word": "induction"
                },
                {
                    "word": "Generalization"
                },
                {
                    "word": "behavioral experiment"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5jn5d29h",
            "frozenauthors": [
                {
                    "first_name": "Matthew",
                    "middle_name": "C.",
                    "last_name": "Overlan",
                    "name_suffix": "",
                    "institution": "University of Rochester",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "A.",
                    "last_name": "Jacobs",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26276/galley/15912/download/"
                }
            ]
        },
        {
            "pk": 26219,
            "title": "Aiding Preschoolers’ word-learning by scaffolding lexical awareness",
            "subtitle": null,
            "abstract": "Preschool-aged children develop awareness of the words theydo and do not know. Awareness of one’s lexicon mayencourage word learning if children pay more attention to thedefinition of unknown words. Here, we tested 3-4-year-oldchildren (N = 91) on a word learning task embedded in an e-book. When a novel word was read, children were eitherasked if they knew the word, asked a question about thestoryline, or asked no question. Then they were given adescription without visual input and asked to identify thereferent’s picture from three choices. Participants who wereasked if they knew a word before being provided with thedefinition identified more referents than children in the otherconditions. Children’s word learning was predicted by short-term memory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "word learning"
                },
                {
                    "word": "lexical awareness"
                },
                {
                    "word": "preschoolers"
                },
                {
                    "word": "object representation"
                },
                {
                    "word": "memory"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8nz0z9k5",
            "frozenauthors": [
                {
                    "first_name": "Sofia",
                    "middle_name": "",
                    "last_name": "Jimenez",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Kaitlin",
                    "middle_name": "",
                    "last_name": "Ryan",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Megan",
                    "middle_name": "M.",
                    "last_name": "Saylor",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26219/galley/15855/download/"
                }
            ]
        },
        {
            "pk": 26180,
            "title": "A Learned Label Modulates Object Representations in 10-Month-Old Infants",
            "subtitle": null,
            "abstract": "Despite substantial evidence for a bidirectional relationshipbetween language and representation, the roots of this relationshipin infancy are not known. The current study explores thepossibility that labels may affect object representations at theearliest stages of language acquisition. We asked parents to playwith their 10-month-old infants with two novel toys for threeminutes, every day for a week, teaching infants a novel word forone toy but not the other. After a week infants participated in afamiliarization task in which they saw each object for 8 trials insilence, followed by a test trial consisting of both objectsaccompanied by the trained word. Infants exhibited a faster declinein looking times to the previously unlabeled object. These dataspeak to the current debate over the status of labels in humancognition, supporting accounts in which labels are an integral partof representation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Representation"
                },
                {
                    "word": "word learning"
                },
                {
                    "word": "languageacquisition"
                },
                {
                    "word": "LINGUISTIC RELATIVITY"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5z02v1jd",
            "frozenauthors": [
                {
                    "first_name": "Katherine",
                    "middle_name": "",
                    "last_name": "Twomey",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                },
                {
                    "first_name": "Gert",
                    "middle_name": "",
                    "last_name": "Westermann",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26180/galley/15816/download/"
                }
            ]
        },
        {
            "pk": 26498,
            "title": "Alien species and alienable traits: An artificial language game investigating thespread of cultural variants between antagonistic groups",
            "subtitle": null,
            "abstract": "The spread of cultural variants, such as dress or speech pat-terns, may be promoted or inhibited by different types of bias.In model-based bias, variants are differentially adopted accord-ing to characteristics of individuals exhibiting them. A surpris-ing case of cross-group adoption comes from sociolinguisticfieldwork in which White speakers were observed exhibiting afeature of African-American Vernacular English, in spite of ex-pressing aggressively negative attitudes towards their African-American neighbors. A likely explanation for this is that thefeature in question had become dissociated for these speakersfrom the inalienable trait Blackness, but had retained associa-tions with the more alienable trait of being “street” or tough.We tested this by conducting an artificial-language experimentin which groups of four participants played a computer gamethat involved typing instant messages to each other, tradingresources, and fighting. Participants were assigned to one oftwo mutually antagonistic “alien species” (weaker Wiwos andtougher Burls) and learned an alien language with two species-specific dialects. In one condition, the Wiwos were told thatthat Burl dialect was mainly used by Burls; in the other con-dition they were told it was mainly used by “tougher aliens”.Burl variants were significantly more likely to be used by Wi-wos in the latter condition than in the former, even though theywere associated with tougher aliens in both conditions. Thissuggests that cultural variants linked to more alienable traitsare more likely to be adopted than those linked to inalienableones, even if the practical implications of the two traits are verysimilar.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "language variation and change; dialect contact;cultural evolution; artificial language"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0vd0g5wd",
            "frozenauthors": [
                {
                    "first_name": "Betsy",
                    "middle_name": "",
                    "last_name": "Sneller",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                },
                {
                    "first_name": "Gareth",
                    "middle_name": "",
                    "last_name": "Roberts",
                    "name_suffix": "",
                    "institution": "University of Pennsylvania",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26498/galley/16134/download/"
                }
            ]
        },
        {
            "pk": 26073,
            "title": "Aligning implicit learning and statistical learning:\nTwo approaches, one phenomenon",
            "subtitle": null,
            "abstract": "The past 15-20 years have witnessed a particularly strong\ninterest in our ability to rapidly extract structured\ninformation from the environment. This fundamental\nprocess of human cognition is widely believed to underpin\nmany complex behaviors – from language development and\nsocial interaction to intuitive decision making and music\ncognition – so this interest spans practically all branches of\ncognitive science. Research on this topic can be found in\ntwo related, yet traditionally distinct research strands,\nnamely \"implicit learning\" (Reber, 1967) and \"statistical\nlearning\" (Saffran, Aslin, & Newport, 1996).\nBoth lines of research focus on how we acquire\ninformation from complex stimulus domains and both rely\nheavily on the use of artificial systems (e.g., finite-state\ngrammars, pseudoword lexicons). In typical experiments,\nparticipants are initially exposed to stimuli generated by an\nartificial system and then tested to determine what they have\nlearned. Given these and other significant similarities,\nPerruchet and Pacton (2006) argue that these distinct lines\nof research actually represent two approaches to a single\nphenomenon, and Conway and Christiansen (2006) propose\ncombining the two in name: \"implicit-statistical learning\".\nYet, despite frequent acknowledgements that researchers in\nimplicit learning and statistical learning might essentially be\nlooking at the same phenomenon, there is surprisingly little\nalignment between the two strands.\nThis symposium seeks to remedy this situation by\nbringing together leading researchers from both areas in\norder to promote a shared understanding of research\nquestions and methodologies, to discuss similarities and\ndifferences between the two approaches, and to work\ntowards a joint research agenda. The symposium comprises\nfour presentations, followed by a thematic discussion, which\nprovide coverage of these phenomena in terms of\ndevelopment (children and adults), different language\nlearning tasks (sublexical phonotactics, word acquisition,\ngrammar learning), and their role in both production and\ncomprehension, each integrating multidisciplinary\nperspectives. Gomez focuses on implicit-statistical learning\nin early development, identifying words and grammatical\nsequences and the memory systems that underlie this\nlearning. Monaghan and Rebuschat measure word learning\nand grammar learning in adults, while varying the\nknowledge that participants have of the structure they are\nacquiring. Dell and Anderson demonstrate how their work\non acquisition of phonotactic constraints is exhibited in\nspeakers’ productions, and discuss the inter-relation in\nspeech between implicit and statistical learning. Finally,\nConway provides an overview of the two fields, and\nproposes a novel framework that unifies implicit learning\nand statistical learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Implicit learning; statistical learning"
                }
            ],
            "section": "Symposia",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8cx2j2bx",
            "frozenauthors": [
                {
                    "first_name": "Patrick",
                    "middle_name": "",
                    "last_name": "Rebuschat",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                },
                {
                    "first_name": "Padraic",
                    "middle_name": "",
                    "last_name": "Monaghan",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                },
                {
                    "first_name": "Nathaniel",
                    "middle_name": "D.",
                    "last_name": "Anderson",
                    "name_suffix": "",
                    "institution": "University of Illinois at Urbana-\nChampaign",
                    "department": ""
                },
                {
                    "first_name": "Christopher",
                    "middle_name": "M.",
                    "last_name": "Conway",
                    "name_suffix": "",
                    "institution": "Georgia State University\nAtlanta",
                    "department": ""
                },
                {
                    "first_name": "Gary",
                    "middle_name": "S.",
                    "last_name": "Dell",
                    "name_suffix": "",
                    "institution": "University of Illinois at Urbana-\nChampaign",
                    "department": ""
                },
                {
                    "first_name": "Rebecca",
                    "middle_name": "",
                    "last_name": "Gomez",
                    "name_suffix": "",
                    "institution": "University of Arizona",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26073/galley/15709/download/"
                }
            ]
        },
        {
            "pk": 26432,
            "title": "Allocation of attention during auditory word learning",
            "subtitle": null,
            "abstract": "The deployment of selective attention has been studied in\ndepth as a mechanism of visual categorization for decades.\nHowever, little work has investigated how attentional\nmechanisms operate for non-visual domains, and many\nmodels of categorization tacitly presume domain-general\nattention use. In three experiments, we investigated whether\nlearners deploy attention to novel auditory features when\nlearning novel words in a similar fashion to the prevailing\nvisual categorization findings. These studies yielded evidence\nof non-isomorphism, as selective attention in the auditory\ndomain shows high context specificity, in contrast to the wide\ngeneralization of attention in the visual domain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "selective attention; auditory attention;\ncategorization; category learning; word learning"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3xn7d1kn",
            "frozenauthors": [
                {
                    "first_name": "Keith",
                    "middle_name": "S.",
                    "last_name": "Apfelbaum",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                },
                {
                    "first_name": "Vladimir",
                    "middle_name": "",
                    "last_name": "Sloutsky",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26432/galley/16068/download/"
                }
            ]
        },
        {
            "pk": 26246,
            "title": "Ambiguity and Representational Stability:\nWhat is the role of embodied experiences?",
            "subtitle": null,
            "abstract": "Embodied cognition is sometimes presented as an alternative\nto computational approaches, the argument being that\ncognition is strongly influenced by an agent's body movement.\nHowever, the exact nature of this influence is still uncertain. In\nthe current paper, we add to the conversation by analyzing\nadults’ predictions in a high-ambiguity task: Adults had to\ndecide which of two objects would sink faster (or slower) in\nwater. Ambiguity was achieved by pitting object volume and\nobject mass against buoyancy: The winning object of a pair was\nsometimes the bigger and heavier one, and sometimes it was\nthe smaller and lighter one. The crucial manipulation was\nwhether the stimuli were real-life objects or 2D pictures. All\nparticipants were presented with pictures of the objects during\na training phase (when they received feedback on their\npredictions). Real-life objects were either present during the\nphase prior to the training (jars-first condition), or during the\nphase after the training (jars-last condition). Findings showed\na clear influence of hands-on experiences: When allowed to\nhold the objects, adults were more likely to demonstrate a\nsimplistic focus on object heaviness. These results call for a\nmore nuanced understanding of the effect of embodied\nexperiences on the stability of representations. While\nembodiment sometimes can help distinguish relevant from\nirrelevant information, we show that it can also destabilize\nrepresentations acquired through visual information.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "action; knowledge representation; predictions;\nambiguity; misconceptions; hands-on explorations"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9250421m",
            "frozenauthors": [
                {
                    "first_name": "Ramón",
                    "middle_name": "",
                    "last_name": "Castillo",
                    "name_suffix": "",
                    "institution": "University of Talca",
                    "department": ""
                },
                {
                    "first_name": "Talia",
                    "middle_name": "L.",
                    "last_name": "Waltzer",
                    "name_suffix": "",
                    "institution": "University of California, Santa Cruz",
                    "department": ""
                },
                {
                    "first_name": "Heidi",
                    "middle_name": "",
                    "last_name": "Kloos",
                    "name_suffix": "",
                    "institution": "University of Cincinnati",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26246/galley/15882/download/"
                }
            ]
        },
        {
            "pk": 26475,
            "title": "A model of conditional probability judgment",
            "subtitle": null,
            "abstract": "A standard view in cognitive psychology is that people esti-mate probabilities using heuristics that do not follow proba-bility theory. We describe a model of probability estimationwhere people do follow probability theory in estimation, butare subject to random error or noise. This model predicts thatpeople’s conditional probability estimates will agree closelywith probability theory for certain noise-cancelling expres-sions, but deviate from probability theory for other expres-sions. We describe an experiment which strongly confirmsthese predictions, suggesting that people estimate conditionalprobabilities in a way that follows standard probability theory,but is subject to the biasing effects of random noise.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3585x7n2",
            "frozenauthors": [
                {
                    "first_name": "Fintan",
                    "middle_name": "J.",
                    "last_name": "Costello",
                    "name_suffix": "",
                    "institution": "University College Dublin",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Watts",
                    "name_suffix": "",
                    "institution": "National University of Ireland Maynooth",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26475/galley/16111/download/"
                }
            ]
        },
        {
            "pk": 26748,
            "title": "A Model of Language-Guided Concept Formation using a Common Frameworkfor Unsupervised and Supervised Learning",
            "subtitle": null,
            "abstract": "A general learning rule, “BCM-δ ”, is proposed that subsumes both unsupervised learning as a form of the BCMrule (Bienenstock, Cooper, Munro, 1982; Munro, 1984) and the delta rule (Rosenblatt, 1958; Rumelhart, Hinton, and Williams,1986). The “BCM-δ ” unit is composed of two subunits, T and L, each integrating distinct input streams across distinct setsof synapses. The two subunits follow a common Hebb-like learning procedure that reduces to an unsupervised rule for the Tsubunit and a supervised rule for the L subunit in which the T response is the training signal. This model suggests a neurallyplausible mechanism for the shaping of concepts by labels. More generally, stimuli from one modality can shape the responseproperties of a unit to another modality using a framework that is biologically plausible and gives clues to the source of ateaching signal for supervised learning.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6nm577w6",
            "frozenauthors": [
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Munro",
                    "name_suffix": "",
                    "institution": "University of Pittsburgh",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26748/galley/16384/download/"
                }
            ]
        },
        {
            "pk": 26712,
            "title": "An action dynamics study of the onset of prediction",
            "subtitle": null,
            "abstract": "A recent approach in cognitive science argues that prediction is a core concept underlying cognition, to the extent thatbrains could be referred to as ”prediction machines” (Clark, 2013). Extending experimental paradigms to explore predictionfacilitate tests of this claim. In a previous study we introduced a statistical learning paradigm to detect when participants arepredicting during implicit/explicit learning. The results revealed that participants tend to rapidly switch into a predictive modealmost as a discrete strategy. While this intriguing possibility was not directly explored in the original study, in this project werepurposed the task to explicitly explore the onset of predictive behaviors. Through a mouse-tracking task, participants get tolearn the statistical structure in a sequence of flashing dots while their mouse movements are being recorded. Findings revealthe level of statistical structure in the environment that triggers the rapid onset of predictive behavior in participants.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/430975rm",
            "frozenauthors": [
                {
                    "first_name": "Maryam",
                    "middle_name": "",
                    "last_name": "Tabatabaeian",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                },
                {
                    "first_name": "Rick",
                    "middle_name": "",
                    "last_name": "Dale",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26712/galley/16348/download/"
                }
            ]
        },
        {
            "pk": 26279,
            "title": "Analogical Generalization and Retrieval for Denominal Verb Interpretation",
            "subtitle": null,
            "abstract": "The creativity of natural language poses a significant\ntheoretical problem. One example of this is denominal verbs\n(those derived from nouns) such as spoon in “She spooned me\nsome sugar”. Traditional generative approaches typically\nposit a unique entry in the lexicon for this usage, though this\napproach has difficulty scaling. Construction Grammar has\nevolved as a competing theory which instead allows the\nsyntactic form of the sentence itself to contribute semantic\nmeaning. However, how people learn syntactic constructions\nremains an open question. One suggestion has been that they\nare learned through analogical generalization. We evaluate\nthis hypothesis using a computational model of analogical\ngeneralization to simulate Kaschak and Glenberg’s (2000)\nstudy regarding interpretation of denominal verbs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Analogy; Construction Grammar; Linguistics;\nAnalogical Generalization"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5z70v78d",
            "frozenauthors": [
                {
                    "first_name": "Clifton",
                    "middle_name": "J.",
                    "last_name": "McFate",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Kenneth",
                    "middle_name": "D.",
                    "last_name": "Forbus",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26279/galley/15915/download/"
                }
            ]
        },
        {
            "pk": 26628,
            "title": "Analogies and Graphics can lead to Illusions of Understanding",
            "subtitle": null,
            "abstract": "Many people experience illusions of understanding for explanations of scientific phenomena (Rozenbleit & Keil,2002) and readers tend to be poor at gauging how well they have understood what they have read in expository science texts(Dunlosky & Lipko, 2007; Maki, 1998; Thiede, Griffin, Wiley, & Redford, 2009). The present line of research includesstudies demonstrating that metacomprehension accuracy may be especially poor when students are presented with texts thatinclude features such as diagrams, graphs, animations, and analogical examples. Although these adjuncts are meant to improvecomprehension, they can often lead to illusions of understanding. An important theme of this research is articulating the kinds ofinstruction and skills that students may need before they can learn effectively from expository science texts including graphicsor analogies.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/25j4k00j",
            "frozenauthors": [
                {
                    "first_name": "Jennifer",
                    "middle_name": "",
                    "last_name": "Wiley",
                    "name_suffix": "",
                    "institution": "University of Illinois Chicago",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "",
                    "last_name": "Griffin",
                    "name_suffix": "",
                    "institution": "University of Illinois Chicago",
                    "department": ""
                },
                {
                    "first_name": "Allison",
                    "middle_name": "",
                    "last_name": "Jaeger",
                    "name_suffix": "",
                    "institution": "University of Illinois Chicago",
                    "department": ""
                },
                {
                    "first_name": "David",
                    "middle_name": "",
                    "last_name": "Sarmento",
                    "name_suffix": "",
                    "institution": "University of Illinois Chicago",
                    "department": ""
                },
                {
                    "first_name": "Marta",
                    "middle_name": "",
                    "last_name": "Mielicki",
                    "name_suffix": "",
                    "institution": "University of Illinois Chicago",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26628/galley/16264/download/"
                }
            ]
        },
        {
            "pk": 26062,
            "title": "Analysing discourse relations in natural language:The case of space and time",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "discourse relations; reference frames; cognitiveprocesses; verbal data; cognitive discourse analysis;spatiotemporal language."
                }
            ],
            "section": "Tutorials",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4pc0h3pp",
            "frozenauthors": [
                {
                    "first_name": "Thora",
                    "middle_name": "",
                    "last_name": "Tenbrink",
                    "name_suffix": "",
                    "institution": "Bangor University (Wales)",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26062/galley/15698/download/"
                }
            ]
        },
        {
            "pk": 26269,
            "title": "Analytical Thinking Predicts Less Teleological Reasoning and Religious Belief",
            "subtitle": null,
            "abstract": "Individual differences in reflectiveness have been found topredict belief in God. We hypothesize that this associationmay be due to a broader inclination for intuitive thinkers toendorse teleological explanations. In support of ourhypothesis, we find that scientifically unfounded teleologicalexplanations are more likely to be endorsed by intuitive compared to analytical thinkers, and that those who endorse teleological explanations are more likely to have religious beliefs.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "cognitive style; cognitive reflection test; religiousbelief; teleological explanations; causal reasoning"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0cf7q63p",
            "frozenauthors": [
                {
                    "first_name": "Jeffrey",
                    "middle_name": "",
                    "last_name": "Zemla",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Samantha",
                    "middle_name": "",
                    "last_name": "Steiner",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                },
                {
                    "first_name": "Steven",
                    "middle_name": "",
                    "last_name": "Sloman",
                    "name_suffix": "",
                    "institution": "Brown University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26269/galley/15905/download/"
                }
            ]
        },
        {
            "pk": 26209,
            "title": "Analytic Eye Movement Patterns in Face Recognition are Associated with BetterPerformance and more Top-down Control of Visual Attention: an fMRI Study",
            "subtitle": null,
            "abstract": "Recent research has revealed two different eye movement pat-terns during face recognition: holistic and analytic. The pre-sent study investigated the neural correlates of these two pat-terns through functional magnetic resonance imaging (fMRI).A more holistic pattern was associated with more activation inthe face-selective perceptual areas, including the occipitalface area and fusiform face area. In contrast, participants us-ing a more analytic pattern demonstrated more activation inareas important for top-down control of visual attention, in-cluding the frontal eye field and intraparietal sulcus. In addi-tion, participants using the analytic patterns had better recog-nition performance than those showing holistic patterns. The-se results suggest that analytic eye movement patterns are as-sociated with more engagement of top-down control of visualattention, which may consequently enhance recognition per-formance.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "eye movement; functional magnetic resonanceimaging (fMRI); face recognition; analytic patterns; HiddenMarkov Model (HMM); top-down visual attention."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2mf970bq",
            "frozenauthors": [
                {
                    "first_name": "Cynthia",
                    "middle_name": "Y.H.",
                    "last_name": "Chan",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "J.J.",
                    "middle_name": "",
                    "last_name": "Wong",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Antoni",
                    "middle_name": "B.",
                    "last_name": "Chan",
                    "name_suffix": "",
                    "institution": "City University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Tatia",
                    "middle_name": "M.C.",
                    "last_name": "Lee",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                },
                {
                    "first_name": "Janet",
                    "middle_name": "H.",
                    "last_name": "Hsiao",
                    "name_suffix": "",
                    "institution": "University of Hong Kong",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26209/galley/15845/download/"
                }
            ]
        },
        {
            "pk": 26359,
            "title": "Analyzing Distributional Learning of Phonemic Categories in Unsupervised DeepNeural Networks",
            "subtitle": null,
            "abstract": "Infants’ speech perception adapts to the phonemic categoriesof their native language, a process assumed to be driven bythe distributional properties of speech. This study investigateswhether deep neural networks (DNNs), the current state-of-the-art in distributional feature learning, are capable oflearning phoneme-like representations of speech in anunsupervised manner. We trained DNNs with unlabeled andlabeled speech and analyzed the activations of each layer withrespect to the phones in the input segments. The analysesreveal that the emergence of phonemic invariance in DNNs isdependent on the availability of phonemic labeling of theinput during the training. No increased phonemic selectivityof the hidden layers was observed in the purely unsupervisednetworks despite successful learning of low-dimensionalrepresentations for speech. This suggests that additionallearning constraints or more sophisticated models are neededto account for the emergence of phone-like categories indistributional learning operating on natural speech.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "statistical learning; distributional learning;language acquisition; phonemic categories; speechperception; categorical perception; connectionism"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/60d8x4fx",
            "frozenauthors": [
                {
                    "first_name": "Okko",
                    "middle_name": "",
                    "last_name": "Räsänen",
                    "name_suffix": "",
                    "institution": "Aalto University",
                    "department": ""
                },
                {
                    "first_name": "Tasha",
                    "middle_name": "",
                    "last_name": "Nagamine",
                    "name_suffix": "",
                    "institution": "Columbia University",
                    "department": ""
                },
                {
                    "first_name": "Nima",
                    "middle_name": "",
                    "last_name": "Mesgarani",
                    "name_suffix": "",
                    "institution": "Columbia University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26359/galley/15995/download/"
                }
            ]
        },
        {
            "pk": 26706,
            "title": "Analyzing experimental paradigms under modification on web-based experimentplatforms",
            "subtitle": null,
            "abstract": "Experimental paradigms are particular experiments that can be modified along a variety of dimensions to answerquestions different than the original inquiry but which have similar content or structure. For example, the original looking-timestudy is an experimental paradigm that has shaped developmental psychology. Thomas Kuhn proposed that, under normalconditions, experimentation by modification of previous paradigms is how science progresses.Web-based experiment platforms (e.g., psiturk and Wallace) are installed with collections of working experimental paradigmsthat are pre-populated with structures necessary to use the platform, but which can be modified to allow users to generate novelexperiments. Because these experiments are implemented in code, we can identify exactly how the code is modified in practice,and begin to directly measure and even test Kuhn’s hypothesis regarding the progress of normal science. I will describe possiblemethods for achieving this, ideally providing others a paradigm to modify.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8df624qm",
            "frozenauthors": [
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Pacer",
                    "name_suffix": "",
                    "institution": "University of California, Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26706/galley/16342/download/"
                }
            ]
        },
        {
            "pk": 26747,
            "title": "An Analogical Model of Pretense",
            "subtitle": null,
            "abstract": "Pretense has been implicated as playing a role in the development of many cognitive and social skills. Despite theimportance and ubiquity of this phenomena, few computational models of pretense exist. We propose a model of pretense viaanalogical abduction. We suggest that pretense occurs via structural alignment. Where a mismatch occurs (i.e. something inthe pretend scenario is not the same as its aligned match in an equivalent real-world scenario), a re-representation must takeplace in order for pretense to continue. For example, a seashell may be re-represented as a cup (as in Fein, 1975) or an emptycup may be re-represented as full (as in Onishi et al., 2007). We show that this model can explain results from two empiricalstudies, including failures in pretense.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6bg1n2x5",
            "frozenauthors": [
                {
                    "first_name": "Irina",
                    "middle_name": "",
                    "last_name": "Rabkina",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Ken",
                    "middle_name": "",
                    "last_name": "Forbus",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26747/galley/16383/download/"
                }
            ]
        },
        {
            "pk": 26206,
            "title": "An Analysis of Frame Semantics of Continuous Processes",
            "subtitle": null,
            "abstract": "Qualitative Process theory provides a formal representation\nfor human-like models of continuous processes. Prior\nresearch mapped qualitative process elements onto English\nlanguage constructions, but did not connect the\nrepresentations to existing frame semantic resources. Here we\nidentify and classify QP language constituents through their\ninstantiation in FrameNet frames to provide a unified\nsemantics for linguistic and non-linguistic representations of\nprocesses. We demonstrate that all core QP relations can map\nto FN, though larger QP evoking phrasal constructions do\nexist outside of this mapping. We conclude with a corpus\nanalysis showing that these frames occur in natural text\ninvolving a variety of continuous processes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Frame Semantics; Qualitative Reasoning"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/04k8s8ck",
            "frozenauthors": [
                {
                    "first_name": "Clifton",
                    "middle_name": "",
                    "last_name": "McFate",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                },
                {
                    "first_name": "Kenneth",
                    "middle_name": "",
                    "last_name": "Forbus",
                    "name_suffix": "",
                    "institution": "Northwestern University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26206/galley/15842/download/"
                }
            ]
        },
        {
            "pk": 26542,
            "title": "An Architectural Account of Variationin Problem Solving and Execution",
            "subtitle": null,
            "abstract": "",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Publication-Based Presentations",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1rm362kq",
            "frozenauthors": [
                {
                    "first_name": "Pat",
                    "middle_name": "",
                    "last_name": "Langley",
                    "name_suffix": "",
                    "institution": "Institute for the Study of Learning and Expertise",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26542/galley/16178/download/"
                }
            ]
        },
        {
            "pk": 26380,
            "title": "An Ecological Model of Memory and Inferences",
            "subtitle": null,
            "abstract": "In this paper, we develop a memory model that predicts\nretrieval characteristics of real-world facts. First, we show\nhow ACT-R’s memory model can be used to predict people’s\nknowledge about real-world objects. The model assumes the\nprobability of retrieving a chunk of information about an\nobject and the time to retrieve this information depend on the\npattern of prior environmental exposure to the object. Second,\nwe use frequencies of information appearing on the Internet\nas a proxy for what information people would encounter in\ntheir natural environment, outside the laboratory. In two\nExperiments, we use this model to account for subjects’\nassociative knowledge about real-world objects as well as the\nassociated retrieval latencies. Third, in a computer simulation,\nwe explore how such model predictions can be used to\nunderstand the workings and performance of decision\nstrategies that operate on the contents of declarative memory.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "ACT-R; declarative memory; decision making;\nfast-and-frugal heuristics; Internet; strategy selection"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1b58x026",
            "frozenauthors": [
                {
                    "first_name": "Daniela",
                    "middle_name": "",
                    "last_name": "Link",
                    "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": "",
                    "last_name": "Schooler",
                    "name_suffix": "",
                    "institution": "Syracuse University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26380/galley/16016/download/"
                }
            ]
        },
        {
            "pk": 26102,
            "title": "An Empirical Evaluation of Models for How People Learn Cue Search Orders",
            "subtitle": null,
            "abstract": "We propose simple parameter-free models that predict howpeople learn environmental cue contingencies, use this infor-mation to measure the usefulness of cues, and in turn, use thesemeasures to construct search orders. To develop the models,we consider a total of 8 previously proposed cue measures,based on cue validity and discriminability, and develop simpleBayesian and biased-Bayesian learning mechanisms for infer-ring these measures from experience. We evaluate the modelpredictions against people’s search behavior in an experimentin which people could freely search cues for information todecide between two stimuli. Our results show that people’sbehavior is best predicted by models relying on cue measuresmaximizing short-term accuracy, rather than long-term explo-ration, and using the biased learning mechanism that increasesthe certainty of inferences about cue properties, but does notnecessarily learn true environmental contingencies.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "learning; search order; predictive models; cuecontingencies"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7620g4mb",
            "frozenauthors": [
                {
                    "first_name": "Percy",
                    "middle_name": "",
                    "last_name": "Mistry",
                    "name_suffix": "",
                    "institution": "University of California Irvine",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Lee",
                    "name_suffix": "",
                    "institution": "University of California Irvine",
                    "department": ""
                },
                {
                    "first_name": "Ben",
                    "middle_name": "",
                    "last_name": "Newell",
                    "name_suffix": "",
                    "institution": "University of New South Wales",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26102/galley/15738/download/"
                }
            ]
        },
        {
            "pk": 26388,
            "title": "A Neural Dynamic Model Parses Object-Oriented Actions",
            "subtitle": null,
            "abstract": "Parsing actions entails that relations between objects are dis-covered. A pervasively neural account of this process requiresthat fundamental problems are solved: the neural pointer prob-lem, the binding problem, and the problem of generating dis-crete processing steps from time-continuous neural processes.We present a prototypical solution to these problems in a neuraldynamic model that comprises dynamic neural fields holdingrepresentations close to sensorimotor surfaces as well as dy-namic nodes holding discrete, language-like representations.Making the connection between these two types of represen-tations enables the model to parse actions as well as groundmovement phrases—all based on real visual input. We demon-strate how the dynamic neural processes autonomously gen-erate the processing steps required to parse or ground object-oriented action.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "relations; neural process model; action parsing;dynamic field theory; grounded cognition; cognitive schemas"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1b80h797",
            "frozenauthors": [
                {
                    "first_name": "Mathis",
                    "middle_name": "",
                    "last_name": "Richter",
                    "name_suffix": "",
                    "institution": "Ruhr-Universit ̈at Bochum",
                    "department": ""
                },
                {
                    "first_name": "Jonas",
                    "middle_name": "",
                    "last_name": "Lins",
                    "name_suffix": "",
                    "institution": "Ruhr-Universit ̈at Bochum",
                    "department": ""
                },
                {
                    "first_name": "Gregor",
                    "middle_name": "",
                    "last_name": "Schoner",
                    "name_suffix": "",
                    "institution": "Ruhr-Universit ̈at Bochum",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26388/galley/16024/download/"
                }
            ]
        },
        {
            "pk": 26527,
            "title": "A Neural Field Model of Word Repetition Effects in Early Time-Course ERPs inSpoken Word Perception",
            "subtitle": null,
            "abstract": "Previous attempts at modeling the neuro-cognitive mecha-nisms underlying word processing have used connectionist ap-proaches, but none has modeled spoken word architectures asthe input is presented in real-time. Hence, such models rely onthe ingenuity of the modeler to establish a mapping of real-time stimulus to the model’s input which may not preserveprocessing that happens during each time step. We present aneural field model which successfully replicates the effect ofimmediate auditory repetition of monosyllabic words and fitsit to a component of a well-studied mechanism for analyzinglanguage processing, the event-related potential (ERP). Thisrepresents a new modeling approach to studying the neuro-cognitive processes, one that is based on the bottom-up inter-action of real-time sensory information with higher-level cate-gories of cognitive processing.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "dynamic neural fields; event-related potential(ERP); spoken word perception; mental workload; computa-tional modeling; word repetition"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6508831h",
            "frozenauthors": [
                {
                    "first_name": "Andrew",
                    "middle_name": "P.",
                    "last_name": "Valenti",
                    "name_suffix": "",
                    "institution": "Tufts University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Brady",
                    "name_suffix": "",
                    "institution": "Tufts University",
                    "department": ""
                },
                {
                    "first_name": "Matthias",
                    "middle_name": "J.",
                    "last_name": "Scheutz",
                    "name_suffix": "",
                    "institution": "Tufts University",
                    "department": ""
                },
                {
                    "first_name": "Phillip",
                    "middle_name": "J.",
                    "last_name": "Holcomb",
                    "name_suffix": "",
                    "institution": "Tufts University",
                    "department": ""
                },
                {
                    "first_name": "He",
                    "middle_name": "",
                    "last_name": "Pu",
                    "name_suffix": "",
                    "institution": "Tufts University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26527/galley/16163/download/"
                }
            ]
        },
        {
            "pk": 26253,
            "title": "A Neural Model of Context Dependent Decision Making in the Prefrontal Cortex",
            "subtitle": null,
            "abstract": "In this paper, we present a spiking neural model of contextdependent decision making. Prefrontal cortex (PFC) plays afundamental role in context dependent behaviour. We modelthe PFC at the level of single spiking neurons, to explore theunderlying computations which determine its contextual re-sponses. The model is built using the Neural EngineeringFramework and performs input selection and integration as anonlinear recurrent dynamical process. The results obtainedfrom the model closely match behavioural and neural experi-mental data obtained from macaque monkeys that are trainedto perform a context sensitive perceptual decision task. Theclose match suggests that the low-dimensional, nonlinear dy-namical model we suggest captures central aspects of contextdependent decision making in primates.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "context dependent decision making; decisionmaking; neural engineering framework; neural dynamics; the-oretical neuroscienc"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7pp1791t",
            "frozenauthors": [
                {
                    "first_name": "Sugandha",
                    "middle_name": "",
                    "last_name": "Sharma",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Brent",
                    "middle_name": "J.",
                    "last_name": "Komer",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26253/galley/15889/download/"
                }
            ]
        },
        {
            "pk": 26124,
            "title": "A neural network model of hierarchical category development",
            "subtitle": null,
            "abstract": "Object recognition and categorization is a fundamental aspectof cognition in humans and animals. Models have been imple-mented around the idea that categories are sets of frequentlyco-occurring features. Out of these models a question has beenraised, namely what is the mechanism by which we learn a hi-erarchically organized set of categories, including types andsubtypes? In this paper we introduce such a model, the Domi-nant Property Assembly Network (DPAN). DPAN uses an un-supervised neural network to model an agent which developsa hierarchy of object categories based on highly correlated ob-ject features. Initially, the network generates representations ofhigh-level object types by identifying commonly co-occurringsets of features. Over time, the network will start to use aninhibition of return (IOR) operation to examine the featuresof a categorized object that make it unusual as an instance ofits identified category. The result is a network which, earlyin training, represents classes of objects using coarse-grainedcategories and recognizes objects as members of these generalclasses, but eventually is able to recognize subtle differencesbetween subtypes of objects within the broad classes, and rep-resent objects using these more fine-grained categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "categorization; computational modeling; proto-type theory"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/64d3p4vv",
            "frozenauthors": [
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Gorman",
                    "name_suffix": "",
                    "institution": "University of Otago",
                    "department": ""
                },
                {
                    "first_name": "Alistair",
                    "middle_name": "",
                    "last_name": "Knott",
                    "name_suffix": "",
                    "institution": "University of Otago",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26124/galley/15760/download/"
                }
            ]
        },
        {
            "pk": 26123,
            "title": "A neurocomputational model of the effect of learned labels on infants’ objectrepresentations",
            "subtitle": null,
            "abstract": "The effect of labels on nonlinguistic representations is the focusof substantial debate in the developmental literature. A recentempirical study (Twomey & Westermann, 2016) suggested thatlabels are incorporated into object representations, such thatinfants respond differently to objects for which they know alabel relative to unlabeled objects. However, these empiricaldata cannot differentiate between two recent theories ofintegrated label-object representations, one of which assumeslabels are features of object representations, and one whichassumes labels are represented separately, but become closelyassociated with learning. We address this issue using aneurocomputational (auto-encoder) model to instantiate boththeoretical approaches. Simulation data support an account inwhich labels are features of objects, with the samerepresentational status as the objects’ visual and hapticcharacteristics.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "connectionist model"
                },
                {
                    "word": "label status"
                },
                {
                    "word": "wordlearning"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4pb869ds",
            "frozenauthors": [
                {
                    "first_name": "Arthur",
                    "middle_name": "",
                    "last_name": "Capelier-Mourguy",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                },
                {
                    "first_name": "Katherine",
                    "middle_name": "",
                    "last_name": "Twomey",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                },
                {
                    "first_name": "Gert",
                    "middle_name": "",
                    "last_name": "Westermann",
                    "name_suffix": "",
                    "institution": "Lancaster University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26123/galley/15759/download/"
                }
            ]
        },
        {
            "pk": 26181,
            "title": "An experimental study on the observation of facts in explanation reconstruction",
            "subtitle": null,
            "abstract": "Explanation reconstruction performs a crucial role not only inthe progress of science but also in educational practices anddaily activities, including the comprehension of phenomena.In this study, we conducted experiments to examine the factorsthat facilitate shifts in explanations. We focused on the tran-sition of attention on a key fact that contradicts an initial ex-planation and has a central role in its reconstruction. We useda short story as an experimental material in which participantsfirst constructed an initial explanation and then reconstructedit. In the experiment, we controlled the time of presentationof the key fact (bottom-up condition), reflective thinking (top-down condition), and the two together (bidirectional condition)to facilitate understanding of the explanatory shift. The experi-mental results are summarized as follows. First, when the priorexplanation was rejected, attention to the key fact was inhibitedalthough a new explanation was required. Second, the success-ful group increased their attention on the key fact just beforethe explanatory shift. Third, protection of the preceding expla-nation with unobserved facts was inhibited by guiding the par-ticipants ’attention toward the key fact. Finally, although theinitial explanation was not completely shifted, a explanatorypre-shift was achieved by activating reflective thinking withattention to the key fact.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "eye-movement analysis; explanation reconstruc-tion; explanatory shift; reinterpretation"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2m2946pj",
            "frozenauthors": [
                {
                    "first_name": "Hitoshi",
                    "middle_name": "",
                    "last_name": "Terai",
                    "name_suffix": "",
                    "institution": "Kindai University",
                    "department": ""
                },
                {
                    "first_name": "Kazuhisa",
                    "middle_name": "",
                    "last_name": "Miwa",
                    "name_suffix": "",
                    "institution": "Nagoya University",
                    "department": ""
                },
                {
                    "first_name": "Naohiro",
                    "middle_name": "",
                    "last_name": "Toyama",
                    "name_suffix": "",
                    "institution": "Nagoya University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26181/galley/15817/download/"
                }
            ]
        },
        {
            "pk": 26684,
            "title": "An explicit theory of sortal representation and some evidence for it.",
            "subtitle": null,
            "abstract": "Does the acquisition of words like “dog”, “table”, and “sand” require the support of sortal concepts? In arguing forand against sortals, theorists typically contrast representations of unsorted individuals (bare particulars) and sortal representa-tions. As such, bare particular and sortal representations are presented as alternative means of representing concepts like “dog”,“table” and “tree”. Arguments for and against sortals typically proceed in the absence of an explicit characterization of the formof sortal representations. I present an explicit theory of the form of sortal representations. It turns out that, for sortals to dothe work they need to do, they must incorporate bare particular representations into the sortal representation. Two experimentsprovide evidence for the predicted by the proposed theory of sortal representations. I also show how the proposed theory ofsortal representation is consistent with recent findings by Rips and colleagues that seem to provide empirical evidence againstsortals.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5m12b60x",
            "frozenauthors": [
                {
                    "first_name": "Sandeep",
                    "middle_name": "",
                    "last_name": "Prasada",
                    "name_suffix": "",
                    "institution": "Hunter College",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26684/galley/16320/download/"
                }
            ]
        },
        {
            "pk": 26736,
            "title": "An Eye For Figurative Meaning: The Effects of Familiarity on MetaphorComprehension",
            "subtitle": null,
            "abstract": "The career of metaphor hypothesis suggests that processing preference is a result of conventionality whereby con-ventional metaphors are processed through categorization, and novel ones processed through comparison. Alternatively, the cat-egorization model predicts that apt metaphors are processed as categorizations whether or not they are conventional. However,research has largely ignored another known factor to influence metaphor processing, namely familiarity. The categorizationmodel predicts familiarity to play no role in deciding on processing strategy. On the other hand, the career of metaphor hypoth-esis predicts that familiarity to play a facilitating role in metaphor comprehension. In this experiment, we used the eye trackingparadigm and controlled for aptness and conventionality, and manipulated familiarity in order to test these predictions. Ourinitial results support the career of metaphor hypothesis suggesting that familiarity facilitates metaphor processing. We discussthe implications these results have on the psycholinguistic models and briefly speculate on their philosophical consequences.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4bn2d84z",
            "frozenauthors": [
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Genovesi",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Vertolli",
                    "name_suffix": "",
                    "institution": "Carleton University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26736/galley/16372/download/"
                }
            ]
        },
        {
            "pk": 26443,
            "title": "Animal, dog, or dalmatian? Level of abstraction in nominal referring expressions",
            "subtitle": null,
            "abstract": "Nominal reference is very flexible—the same object may becalled a dalmatian, a dog, or an animal when all are literallytrue. What accounts for the choices that speakers make in howthey refer to objects? The addition of modifiers (e.g. big dog)has been extensively explored in the literature, but fewer stud-ies have explored the choice of noun, including its level of ab-straction. We collected freely produced referring expressionsin a multi-player reference game experiment, where we ma-nipulated the object’s context. We find that utterance choiceis affected by the contextual informativeness of a description,its length and frequency, and the typicality of the object forthat description. Finally, we show how these factors naturallyenter into a formal model of production within the RationalSpeech-Acts framework, and that the resulting model predictsour quantitative production data.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "referential ex-pressions"
                },
                {
                    "word": "levels of reference"
                },
                {
                    "word": "basic level"
                },
                {
                    "word": "experimental prag-matics"
                },
                {
                    "word": "computational pragmatics"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4sm7b9zn",
            "frozenauthors": [
                {
                    "first_name": "Caroline",
                    "middle_name": "",
                    "last_name": "Graf",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Judith",
                    "middle_name": "",
                    "last_name": "Degen",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Robert",
                    "middle_name": "X.D.",
                    "last_name": "Hawkins",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Noah",
                    "middle_name": "D.",
                    "last_name": "Goodman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26443/galley/16079/download/"
                }
            ]
        },
        {
            "pk": 26449,
            "title": "An Information-Processing Account of Representation Change:International Mathematical Olympiad Problems are Hard not only for Humans",
            "subtitle": null,
            "abstract": "In this paper, we present a new information-processing modelof math problem solving in which representation change the-ory can be implemented. Specifically, we divided the problemrepresentation process into two. One is to straightforwardlytranslate problem texts into formulas in a conservative exten-sion of Zermelo-Fraenkel’s set theory, and the other is to in-terpret the translated formulas in local mathematical theories.A ZF formula has several interpretations, and representationchange is thus implementable as a choice of an appropriate in-terpretation. Adopting the theory of real closed fields as an ex-ample of local theory and its quantifier elimination algorithmsas an approximate process of searching for solutions, we de-velop a prototype system. We use more than 400 problemsfrom three sources as benchmarks: exercise books, univer-sity entrance examination, and the International MathematicalOlympiad problems. Our experimental results suggest that ourmodel can serve as a basis of a quantitative study on represen-tation change in the sense that the performance of our proto-type system reflects difficulties of the problems quite precisely.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "problem solving; information-processing model;insight; representation change"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6ps6f4gm",
            "frozenauthors": [
                {
                    "first_name": "Takuya",
                    "middle_name": "",
                    "last_name": "Matsuzaki",
                    "name_suffix": "",
                    "institution": "Nagoya University",
                    "department": ""
                },
                {
                    "first_name": "Munehiro",
                    "middle_name": "",
                    "last_name": "Kobayashi",
                    "name_suffix": "",
                    "institution": "University of Tsukuba",
                    "department": ""
                },
                {
                    "first_name": "Noriko",
                    "middle_name": "H.",
                    "last_name": "Arai",
                    "name_suffix": "",
                    "institution": "National Institute of Informatics",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26449/galley/16085/download/"
                }
            ]
        },
        {
            "pk": 26559,
            "title": "An interactive model accounts for both ultra-rapid superordinate classificationand basic-level advantage in object recognition",
            "subtitle": null,
            "abstract": "While people are faster to categorize objects at an intermediate or basic level of specificity (e.g. “bird”), severalrecent studies have shown them to have much earlier access to more general category information (e.g. “animal”). Ultra-rapidsuperordinate classification has been taken as evidence that recognition processes are largely feed-forward. In simulations witha deep neural network model, we show that this conclusion does not follow: even a model that is fully recurrent and interactiveshows ultra-rapid superordinate classification patterns when tested with analogs of behavioral tasks such as rapid serial visualpresentation or deadline classification. Moreover, this recurrent model explains recently-observed similarities and differencesin the time-course of classification as estimated by electro-encephlography (EEG) versus human electro-corticography (ECoG),and also account for the well-known basic-level advantage in non-speeded classification. These results provide evidence thatultra-rapid and unconstrained visual object recognition is supported by interactive processes in the brain.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0p28x2nd",
            "frozenauthors": [
                {
                    "first_name": "Qihong",
                    "middle_name": "",
                    "last_name": "Lu",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                },
                {
                    "first_name": "Timothy",
                    "middle_name": "",
                    "last_name": "Rogers",
                    "name_suffix": "",
                    "institution": "University of Wisconsin-Madison",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26559/galley/16195/download/"
                }
            ]
        },
        {
            "pk": 26345,
            "title": "A Nonlinear Dynamical Systems Theory Perspective on Dual-ProcessingAccounts of Decision-Making under Uncertainty",
            "subtitle": null,
            "abstract": "Dual-processing accounts of reasoning havegained renewed attention in the past decade,particularly in the fields of social judgment,learning, and decision-making under uncertainty.Although the various accounts differ, thecommon thread is the distinction between twoqualitatively different types of reasoning:explicit/implicit, rational/affective, fast/slow, etc.Consequently, much research has focused oncharacterizing the two different processes. Lessextensive are the attempts to find mediators thatinfluence which process is used. In this paper, weargue that the missing perspective on these dual-processing theories is rooted in dynamicalsystems theory. By shifting the perspective to thedynamic interaction and transitions betweendifferent types of reasoning, we provide atheoretical framework for dual-processing withan emphasis on phase transitions. As a specialcase, we focus on dual-processing in decision-making and judgment under uncertainty forwhich we will propose suggestions for futureexperimental evaluation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "decision-making under uncertainty;dual-processing; nonlinear dynamical systemstheory; phase transitions"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5c80r0bx",
            "frozenauthors": [
                {
                    "first_name": "Marieke",
                    "middle_name": "M.J.W.",
                    "last_name": "van Rooij",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Luis",
                    "middle_name": "H.",
                    "last_name": "Favela",
                    "name_suffix": "",
                    "institution": "University of Central Florida",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26345/galley/15981/download/"
                }
            ]
        },
        {
            "pk": 26615,
            "title": "A normative theory of visual working memory limitations",
            "subtitle": null,
            "abstract": "There are many benefits to having a highly accurate representation of the environment. Why, then, has evolutionequipped us with a visual working memory (VWM) system that can represent only a handful of items with high accuracy?Here, we offer a normative explanation for this limitation by conceptualizing VWM as a system that balances between twoconflicting goals: keeping memory errors small and spiking activity low. We formalize this trade-off in a loss function andshow that minimization of loss dictates a strategy in which memory precision declines with the number of remembered items.Using psychophysical data from 67 human subjects in 5 delayed-estimation experiments, we show that this normative modelprovides an excellent account of human VWM limitations. These results suggest that human VWM implements an optimalcompromise between two conflicting ecological goals",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1xt3r4j6",
            "frozenauthors": [
                {
                    "first_name": "Ronald",
                    "middle_name": "van den",
                    "last_name": "Berg",
                    "name_suffix": "",
                    "institution": "University of Uppsala",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26615/galley/16251/download/"
                }
            ]
        },
        {
            "pk": 26532,
            "title": "Answering Causal Queries about Singular Cases",
            "subtitle": null,
            "abstract": "Queries about singular causation face two problems: It needsto be decided whether the two observed events are instanti-ations of a generic cause-effect relation. Second, causationneeds to be distinguished from coincidence. We propose acomputational model that addresses both questions. It accessesgeneric causal knowledge either on the individual or the grouplevel. Moreover, the model considers the possibility of a co-incidence by adopting Cheng and Novick’s (2005) power PCmeasure of causal responsibility. This measure delivers theconditional probability that a cause is causally responsible foran effect given that both events have occurred. To take uncer-tainty about both the causal structure and the parameters intoaccount we embedded the causal responsibility measure withinthe structure induction (SI) model developed by Meder et al.(2014). We report the results of three experiments that showthat the SI model better captures the data than the power PCmodel.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "causal inference"
                },
                {
                    "word": "generic causation"
                },
                {
                    "word": "singular cau-sation"
                },
                {
                    "word": "actual causation"
                },
                {
                    "word": "causal responsibility"
                },
                {
                    "word": "causal attribu-tion"
                },
                {
                    "word": "Bayesian modeling"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/78s3p031",
            "frozenauthors": [
                {
                    "first_name": "Simon",
                    "middle_name": "",
                    "last_name": "Stephan",
                    "name_suffix": "",
                    "institution": "University of Gottingen",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "R.",
                    "last_name": "Waldmann",
                    "name_suffix": "",
                    "institution": "University of Gottingen",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26532/galley/16168/download/"
                }
            ]
        },
        {
            "pk": 26143,
            "title": "A Perception-Based Threshold for Bidirectional Texture Functions",
            "subtitle": null,
            "abstract": "For creating photorealistic images, Computer Graphics re-searchers introduced Bidirectional Texture Functions (BTFs),which use view- and illumination-dependent textures for ren-dering. BTFs require massive storage, and several proposalswere made on how to compress them, but very few take intoaccount human perception. We present and discuss an exper-imental study on how decreasing the texture resolution influ-ences perceived quality of the rendered images. In a visualcomparison task, observer quality judgments and gaze datawere collected and analysed to determine the optimal down-sampling of BTF data without significant loss of their per-ceived visual quality.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Perceived image quality; realistic rendering;threshold in image perception; eye tracking."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9w80j8xj",
            "frozenauthors": [
                {
                    "first_name": "Banafsheh",
                    "middle_name": "",
                    "last_name": "Azari",
                    "name_suffix": "",
                    "institution": "Bauhaus-Universit ̈at Weimar",
                    "department": ""
                },
                {
                    "first_name": "Sven",
                    "middle_name": "",
                    "last_name": "Bertel",
                    "name_suffix": "",
                    "institution": "Bauhaus-Universit ̈at Weimar",
                    "department": ""
                },
                {
                    "first_name": "Charles",
                    "middle_name": "A.",
                    "last_name": "Wuethrich",
                    "name_suffix": "",
                    "institution": "Bauhaus-Universit ̈at Weimar",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26143/galley/15779/download/"
                }
            ]
        },
        {
            "pk": 26501,
            "title": "A performance model for early word learning",
            "subtitle": null,
            "abstract": "The emergence of language around a child’s first birthday isone of the greatest transformations in human development.Does this transition require a fundamental shift in the child’sknowledge or beliefs, or could it instead be attributable to moregradual changes in processing abilities? We present a simplemodel of cognitive performance that supports the second con-clusion. The premise of this model is that any cognitive op-eration requires multiple steps, each of which require sometime to complete and have some probability of failure. Weuse meta-analysis to estimate these parameters for two com-ponents of simple ostensive word learning: social cue use andword recognition. When combined in our model, these esti-mates suggest that learning should be very difficult for chil-dren younger than around a year, especially with gaze alone.This model takes a first step towards quantifying performancelimitations for cognitive development and may be broadly ap-plicable to other developmental changes.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Speed of processing; development; word learning;meta-analysis"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9nb618qs",
            "frozenauthors": [
                {
                    "first_name": "Michael",
                    "middle_name": "C.",
                    "last_name": "Frank",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Molly",
                    "middle_name": "L.",
                    "last_name": "Lewis",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Kyle",
                    "middle_name": "",
                    "last_name": "MacDonald",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26501/galley/16137/download/"
                }
            ]
        },
        {
            "pk": 26189,
            "title": "A perspective on all cognition? A study of everyday environments from the\nperspective of distributed cognition.",
            "subtitle": null,
            "abstract": "Distributed cognition is a perspective that primarily has been\napplied to complex socio-technical systems such as flight\ndecks of commercial airliners, or operating rooms where\nprofessionals perform cognitive tasks in environments\nspecifically designed for this. For some scholars distributed\ncognition is exactly this kind of specialized cognitive system.\nOn the other hand it has been claimed by some workers in the\nfield that distributed cognition is not a kind of cognition but a\nperspective on all cognition. We have therefore studied an\nenvironment very different from the systems previously\nstudied, namely single people’s homes. We find that there are\nmany similarities between the home and the specialized\nsocio-technical environments. To us this suggests that the\nspecially designed complex environments can be seen as\nspecialized cases of the general principles of distributed\ncognition which are not reflections of “particular work\npractices” but of general features of human cognition.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "everyday cognition; distributed cognition;\nmemory practices."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/63z0d071",
            "frozenauthors": [
                {
                    "first_name": "Nils",
                    "middle_name": "",
                    "last_name": "Dahlbäck",
                    "name_suffix": "",
                    "institution": "Linköping University",
                    "department": ""
                },
                {
                    "first_name": "Mattias",
                    "middle_name": "",
                    "last_name": "Kristiansson",
                    "name_suffix": "",
                    "institution": "Linköping University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26189/galley/15825/download/"
                }
            ]
        },
        {
            "pk": 26666,
            "title": "A Preliminary Model of Situation Awareness in a Cognitive Architecture.",
            "subtitle": null,
            "abstract": "Although maintaining situation awareness (SA) is a critical skill for many complex tasks, there have thus far beenfew rigorous computational approaches to modeling SA behavior and performance. We developed a preliminary computationalmodel of SA focused on remembering the locations of static objects in the visual field. We built this model on the foundationof the ACT-R cognitive architecture, using its declarative memory and vision modules to specify the process of scanning thefield and remembering object locations. In the current work, we demonstrate how this model accounts for human behavior andperformance in two recent experiments: one, a study of object location memory with identities similar to air-traffic control callsigns; and another, a study of remembering the location of shapes of varying size, color, and pattern.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/28g7g1km",
            "frozenauthors": [
                {
                    "first_name": "Ehsan",
                    "middle_name": "",
                    "last_name": "Khosroshahi",
                    "name_suffix": "",
                    "institution": "Drexel University",
                    "department": ""
                },
                {
                    "first_name": "Dario",
                    "middle_name": "",
                    "last_name": "Salvucci",
                    "name_suffix": "",
                    "institution": "Drexel University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26666/galley/16302/download/"
                }
            ]
        },
        {
            "pk": 26251,
            "title": "A rational speech-act model of projective content",
            "subtitle": null,
            "abstract": "Certain content of a linguistic construction can project whenthe construction is embedded in entailment-canceling environ-ments. For example, the conclusion that John smoked in thepast from the utterance John stopped smoking still holds forJohn didn’t stop smoking, in which the original utterance isembedded under negation. There are two main approaches toaccount for projection phenomena. The semantic approach addsrestrictions of the common ground to the conventional meaning.The pragmatic approach tries to derive projection from generalconversational principles. In this paper we build a probabilisticmodel of language understanding in which the listener jointlyinfers the world state and what common ground the speakerhas assumed. We take change-of-state verbs as an exampleand model its projective content under negation. Under certainassumptions, the model predicts the projective behavior and itsinteraction with the question under discussion (QUD), withoutany special semantic treatment of projective content.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Presupposition; projection; Bayesian pragmatics"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0vf8t36v",
            "frozenauthors": [
                {
                    "first_name": "Ciyang",
                    "middle_name": "",
                    "last_name": "Qing",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Noah",
                    "middle_name": "D.",
                    "last_name": "Goodman",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Lassiter",
                    "name_suffix": "",
                    "institution": "Stanford University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26251/galley/15887/download/"
                }
            ]
        },
        {
            "pk": 26197,
            "title": "Are children flexible speakers?\nEffects of typicality and listener needs in children’s event descriptions",
            "subtitle": null,
            "abstract": "Do children take into account their addressees’ needs in\nspontaneous production? Developmental evidence for speaker\nadjustments is mixed. Some studies show that children are\noften under-informative when communicating with ignorant\naddressees but other studies demonstrate successes in\nchildren’s ability to integrate another person’s perspective.\nWe asked whether children adapt their event descriptions\ndepending on (a) the typicality of event components, and (b)\nthe listener’s visual access to the events. We found that\nchildren’s ability to use information about the listener’s visual\nperspective to make specific adjustments to event descriptions\nemerged only in highly interactive contexts, in which\nparticipants collaborated towards mutual goals.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "referential communication; event cognition;\nlanguage production; instruments; perspective-taking;\npragmatics"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3s13v7sg",
            "frozenauthors": [
                {
                    "first_name": "Myrto",
                    "middle_name": "",
                    "last_name": "Grigoroglou",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                },
                {
                    "first_name": "Anna",
                    "middle_name": "",
                    "last_name": "Papafragou",
                    "name_suffix": "",
                    "institution": "University of Delaware",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26197/galley/15833/download/"
                }
            ]
        },
        {
            "pk": 26217,
            "title": "A Recurrent Network Approach to Modeling Linguistic Interaction",
            "subtitle": null,
            "abstract": "What capacities enable linguistic interaction? While severalproposals have been advanced, little progress has been made incomparing and articulating them within an integrative frame-work. In this paper, we take initial steps towards a connec-tionist framework designed to systematically compare differ-ent cognitive models of social interactions. The frameworkwe propose couples two simple-recurrent network systems(Chang, 2002) to explore the computational underpinnings ofinteraction, and apply this modeling framework to predict thesemantic structure derived from transcripts of an experimen-tal joint decision task (Bahrami et al., 2010; Fusaroli et al.,2012). In an exploratory application of this framework, wefind (i) that the coupled network approach is capable of learn-ing from noisy naturalistic input but (ii) that integration of pro-duction and comprehension does not increase the network per-formance. We end by discussing the value of looking to tra-ditional parallel distributed processing as flexible models forexploring computational mechanisms of conversation.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "language; interaction; neural networks; produc-tion; comprehension"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8dw7x2f2",
            "frozenauthors": [
                {
                    "first_name": "Rick",
                    "middle_name": "",
                    "last_name": "Dale",
                    "name_suffix": "",
                    "institution": "University of California, Merced",
                    "department": ""
                },
                {
                    "first_name": "Riccardo",
                    "middle_name": "",
                    "last_name": "Fusaroli",
                    "name_suffix": "",
                    "institution": "Aarhus University",
                    "department": ""
                },
                {
                    "first_name": "Joanna",
                    "middle_name": "",
                    "last_name": "Ra ̧czaszek-Leonardi",
                    "name_suffix": "",
                    "institution": "Polish Academy of Sciences",
                    "department": ""
                },
                {
                    "first_name": "Morten",
                    "middle_name": "H.",
                    "last_name": "Christiansen",
                    "name_suffix": "",
                    "institution": "Cornell University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26217/galley/15853/download/"
                }
            ]
        },
        {
            "pk": 26216,
            "title": "Are Financial Advisors Money Doctors or Charlatans? Evidence on Trust, Advice,\nand Risk Taking in Delegated Asset Management",
            "subtitle": null,
            "abstract": "We test the effects of advice and trust on risk-taking in three\nonline experiments designed to elucidate under what\nconditions financial advice may increase risk-taking,\nirrespective of advisor performance. In our study, investors\nmade 100 decisions, selecting between one of two alternatives:\nrisky or conservative. We manipulate the suggestion of an\nadvisor (risky vs. non-risky investments), the fee of the advice,\nas well as the trustworthiness of the advisor (by increasing the\ntransparency of the advice presented) to test the effect of the\nadvice on risk-taking. The results show that individuals\nasymmetrically follow the advice they received, with a bias\ntowards following more risky than conservative advice.\nMoreover, trusted advice was more persuasive irrespective of\nwhat the advisor suggested and even the fee is higher.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Advice taking; Financial advice; Money doctors;\nRisk taking; Trust"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4tk0335v",
            "frozenauthors": [
                {
                    "first_name": "Qizhang",
                    "middle_name": "",
                    "last_name": "Sun",
                    "name_suffix": "",
                    "institution": "University of Lugano",
                    "department": ""
                },
                {
                    "first_name": "Michael",
                    "middle_name": "",
                    "last_name": "Gibbert",
                    "name_suffix": "",
                    "institution": "University of Lugano",
                    "department": ""
                },
                {
                    "first_name": "Thomas",
                    "middle_name": "T.",
                    "last_name": "Hills",
                    "name_suffix": "",
                    "institution": "University of Warwick",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Nowak",
                    "name_suffix": "",
                    "institution": "University of Lugano",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26216/galley/15852/download/"
                }
            ]
        },
        {
            "pk": 26396,
            "title": "Are Symptom Clusters Explanatory?\nA Study in Mental Disorders and Non-Causal Explanation",
            "subtitle": null,
            "abstract": "Three experiments investigate whether and why people accept\nexplanations for symptoms that appeal to mental disorders,\nsuch as: “She experiences delusions because she has\nschizophrenia.” Such explanations are potentially puzzling, as\nmental disorder diagnoses are made on the basis of symptoms,\nand the DSM implicitly rejects a commitment to some\ncommon, underlying cause. Do laypeople nonetheless\nconceptualize mental disorder classifications in causal terms?\nOr is this an instance of non-causal explanation? Experiment 1\nshows that such explanations are indeed found explanatory.\nExperiment 2 presents participants with novel disorders that\nare stipulated to involve or not involve an underlying cause\nacross symptoms and people. Disorder classifications are\nfound more explanatory when a causal basis is stipulated, or\nwhen participants infer that one is present (even after it’s\ndenied in the text). Finally, Experiment 3 finds that merely\nhaving a principled, but non-causal, basis for defining\nsymptom clusters is insufficient to reach the explanatory\npotential of categories with a stipulated common cause. We\ndiscuss the implications for accounts of explanation and for\npsychiatry.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "explanation"
                },
                {
                    "word": "Understanding"
                },
                {
                    "word": "Mental Disorders"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/8jr0r93x",
            "frozenauthors": [
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Wilkenfeld",
                    "name_suffix": "",
                    "institution": "University of California Berkeley",
                    "department": ""
                },
                {
                    "first_name": "Jennifer",
                    "middle_name": "",
                    "last_name": "Asselin",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                },
                {
                    "first_name": "Tania",
                    "middle_name": "",
                    "last_name": "Lombrozo",
                    "name_suffix": "",
                    "institution": "University of California Berkeley",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26396/galley/16032/download/"
                }
            ]
        },
        {
            "pk": 26111,
            "title": "Are There Hidden Costs to Teaching Mathematics with Incorrect Examples?",
            "subtitle": null,
            "abstract": "This study aims to address potential costs of using incorrectworked examples in teaching mathematics. While suchpractice has been shown to be effective in educationalresearch, previous findings in the memory literature suggestthat exposure to an incorrect solution may lead students tolater believe that it is correct due to increased familiarity. Wedesigned a two-session experiment with 1-week delay inwhich students studied correct and incorrect worked outexamples. We found only small changes in students’ ability tosuccessfully distinguish between correct and incorrectsolutions over time. Students did rate the previously studiedincorrect examples as being more correct after the 1-wkdelay, but this did not affect their correctness ratings of newcorrect and incorrect worked examples or their problemsolving accuracy. We conclude that the unique nature ofmathematical problem solving may protect students from thedangers of using incorrect worked examples.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "incorrect examples; worked examples; problemsolving; mathematics learning; illusory truth; source memory"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0bf0495j",
            "frozenauthors": [
                {
                    "first_name": "Min",
                    "middle_name": "Kyung",
                    "last_name": "Hong",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Darren",
                    "middle_name": "J.",
                    "last_name": "Yeo",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Bethany",
                    "middle_name": "",
                    "last_name": "Rittle-Johnson",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                },
                {
                    "first_name": "Lisa",
                    "middle_name": "K.",
                    "last_name": "Fazio",
                    "name_suffix": "",
                    "institution": "Vanderbilt University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26111/galley/15747/download/"
                }
            ]
        },
        {
            "pk": 26085,
            "title": "Are we ON the same page?\nMonolingual and bilingual acquisition of familiar and novel relational language",
            "subtitle": null,
            "abstract": "Verbs and prepositions pose significant challenges in second\nlanguage learning, as languages differ in how they map these\nrelational terms onto events. Second language learners must\nput aside their language-specific lens to uncover how a new\nlanguage operates, perhaps having to rediscover semantic\ndistinctions typically ignored in the first language. The\ncurrent study examines how the acquisition of these novel\nmappings are affected by characteristics of the learner and of\nthe language to be learned. English monolinguals and Dutch-\nEnglish bilinguals learned novel terms that corresponded to\ncontainment and support relations of either English, Dutch, or\nJapanese. Results show that English distinctions are learned\nbest across groups, potentially reflecting predispositions in\nhuman cognition. No differences were found between\nmonolinguals and bilinguals in any language condition. The\ncharacteristics of the language to be learned appear to play a\nprominent role in the acquisition of novel semantic categories.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Cognitive Semantics; Second Language\nLearning; Bilingualism; Event Perception"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5hn767j9",
            "frozenauthors": [
                {
                    "first_name": "Nathan",
                    "middle_name": "",
                    "last_name": "George",
                    "name_suffix": "",
                    "institution": "Penn State University",
                    "department": ""
                },
                {
                    "first_name": "Junko",
                    "middle_name": "",
                    "last_name": "Kanero",
                    "name_suffix": "",
                    "institution": "Temple University",
                    "department": ""
                },
                {
                    "first_name": "Dorothee",
                    "middle_name": "",
                    "last_name": "Chwilla",
                    "name_suffix": "",
                    "institution": "Radboud University",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "J.",
                    "last_name": "Weiss",
                    "name_suffix": "",
                    "institution": "Penn State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26085/galley/15721/download/"
                }
            ]
        },
        {
            "pk": 26170,
            "title": "A Robust Implementation of Episodic Memory for a Cognitive Architecture",
            "subtitle": null,
            "abstract": "The ability to remember events plays an important role in hu-man life. People can replay past events in their heads and makedecisions based on that information. In this paper, we describea novel extension to a cognitive architecture, ICARUS, that en-ables it to store, organize, generalize, and retrieve episodictraces that can help the agent in a variety of manners. Af-ter discussing previous work on the related topic, we reviewICARUS and explain the new extension to the architecture indetail. Then we discuss four architectural implications of thenew capability and list some future work before we conclude.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "episodic memory; cognitive architectures; virtualsensing; expectations; impasse resolution"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3px6f79x",
            "frozenauthors": [
                {
                    "first_name": "David",
                    "middle_name": "Henerey",
                    "last_name": "Menager",
                    "name_suffix": "",
                    "institution": "University of Kansas",
                    "department": ""
                },
                {
                    "first_name": "Dongkyu",
                    "middle_name": "",
                    "last_name": "Choi",
                    "name_suffix": "",
                    "institution": "University of Kansas",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26170/galley/15806/download/"
                }
            ]
        },
        {
            "pk": 26730,
            "title": "Artificial Language Learning: The Context of Negation",
            "subtitle": null,
            "abstract": "Words are learned in various contexts and over various timescales throughout our lives. The current study exploredthe role of context in the form of negation in artificial language learning. It was predicted that words trained in an entirelynegated context would show lower average correctness in the testing phase than those trained entirely in the affirmative or inthe combined contexts. Eighteen artificial nouns were trained using the prefixes “an-” meaning “not the” or “o-” meaning “the”to mark negation. In the testing phase, participants were tested without the prefix on word stems only. Findings indicatedwords learned solely in the affirmative context led to a higher average correctness while those learned solely in the presence ofnegation showed the least average correctness in the testing phase.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/9bn9x480",
            "frozenauthors": [
                {
                    "first_name": "Ariel",
                    "middle_name": "",
                    "last_name": "Mathis",
                    "name_suffix": "",
                    "institution": "University of Memphis",
                    "department": ""
                },
                {
                    "first_name": "Stephanie",
                    "middle_name": "",
                    "last_name": "Huette",
                    "name_suffix": "",
                    "institution": "University of Memphis",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26730/galley/16366/download/"
                }
            ]
        },
        {
            "pk": 26330,
            "title": "A scaleable spiking neural model of action planning",
            "subtitle": null,
            "abstract": "Past research on action planning has shed light on the neuralmechanisms underlying the selection of simple motor actions,along with the cognitive mechanisms underlying the planningof action sequences in constrained problem solving domains.We extend this research by describing a neural model thatrapidly plans action sequences in relatively unconstrained do-mains by manipulating structured representations of objectsand the actions they typically afford. We provide an analysisthat indicates our model is able to reliably accomplish goalsthat require correctly performing a sequence of up to 5 actionsin a simulated environment. We also provide an analysis ofthe scaling properties of our model with respect to the num-ber of objects and affordances that constitute its knowledgeof the environment. Using simplified simulations we find thatour model is likely to function effectively while picking from10,000 actions related to 25,000 objects.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "planning; affordances; spiking neurons; neural en-gineering framework; semantic pointer architecture"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/3rb9w1r5",
            "frozenauthors": [
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Blouw",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Chris",
                    "middle_name": "",
                    "last_name": "Eliasmith",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                },
                {
                    "first_name": "Bryan",
                    "middle_name": "P.",
                    "last_name": "Tripp",
                    "name_suffix": "",
                    "institution": "University of Waterloo",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26330/galley/15966/download/"
                }
            ]
        },
        {
            "pk": 26649,
            "title": "A shape-heavy vocabulary does not a shape bias make: A comparison of thecontent of English-learning children’s and Spanish-learning children’s typicalvocabularies",
            "subtitle": null,
            "abstract": "We asked why Spanish-monolingual children exhibit a weaker, slower-to-develop shape bias in word-learning con-texts compared to English-monolingual children (Hahn & Cantrell, 2012). Ten English-monolingual adults and nine English-Spanish bilingual adults rated the perceptual similarity of items indicated by subsets of words from the English MCDI andSpanish MCDI, respectively. Consistent with previous research with similar methodology (Samuelson & Smith, 1999), wordsfor shape-similar items predominated in the content of the English MCDI (47.72%; agreement: 70%, p < .05). Interestingly,words for shape-similar items also predominated in the content of the Spanish MCDI (56.67%; agreement: 70%, p < .05).Results suggest that the types of words that children learn play a less important role in the development of the shape biasthan other proposed factors (e.g., syntactical regularities; Smith, 2000). Additional findings and implications for children withvarious language backgrounds will be discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0hn1h153",
            "frozenauthors": [
                {
                    "first_name": "Emily",
                    "middle_name": "",
                    "last_name": "Russell",
                    "name_suffix": "",
                    "institution": "California State University, Northridge",
                    "department": ""
                },
                {
                    "first_name": "Christina",
                    "middle_name": "",
                    "last_name": "Schonberg",
                    "name_suffix": "",
                    "institution": "University of California, Los Angeles",
                    "department": ""
                },
                {
                    "first_name": "Shawntel",
                    "middle_name": "",
                    "last_name": "Barreiro",
                    "name_suffix": "",
                    "institution": "California State University, Northridge",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26649/galley/16285/download/"
                }
            ]
        },
        {
            "pk": 26408,
            "title": "Asking and evaluating natural language questions",
            "subtitle": null,
            "abstract": "The ability to ask questions during learning is a key aspect ofhuman cognition. While recent research has suggested com-mon principles underlying human and machine “active learn-ing,” the existing literature has focused on relatively simpletypes of queries. In this paper, we study how humans constructrich and sophisticated natural language queries to search for in-formation in a large yet computationally tractable hypothesisspace. In Experiment 1, participants were allowed to ask anyquestion they liked in natural language. In Experiment 2, par-ticipants were asked to evaluate questions that they did not gen-erate themselves. While people rarely asked the most informa-tive questions in Experiment 1, they strongly preferred moreinformative questions in Experiment 2, as predicted by an idealBayesian analysis. Our results show that rigorous information-based accounts of human question asking are more widely ap-plicable than previously studied, explaining preferences acrossa diverse set of natural language questions.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Bayesian modeling; active learning; informationsearch; question asking"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4wx34357",
            "frozenauthors": [
                {
                    "first_name": "Anselm",
                    "middle_name": "",
                    "last_name": "Rothe",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Brenden",
                    "middle_name": "M.",
                    "last_name": "Lake",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                },
                {
                    "first_name": "Todd",
                    "middle_name": "M.",
                    "last_name": "Gureckis",
                    "name_suffix": "",
                    "institution": "New York University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26408/galley/16044/download/"
                }
            ]
        },
        {
            "pk": 26470,
            "title": "A speed-accuracy trade-off in children’s processing of scalar implicatures",
            "subtitle": null,
            "abstract": "Scalar implicatures—inferences from a weak description (“Iate some of the cookies”) that a stronger alternative is true(“I didn’t eat all”)—are paradigm cases of pragmatic infer-ence. Children’s trouble with scalar implicatures is thus animportant puzzle for theories of pragmatic development, giventheir communicative competence in other domains. Previousresearch has suggested that access to alternatives might be key.Here, we explore children’s reaction times in a new paradigmfor measuring scalar implicature processing. Alongside fail-ures on scalar implicatures with “some,” we replicate previ-ous reports of failures with “none,” and find evidence of aspeed-accuracy trade-off for both quantifiers. Motivated bythese findings, we explore the relationship between accuracyand reaction time with a Drift Diffusion Model. We find evi-dence consistent with the hypothesis that preschoolers lack ac-cess to the alternatives for scalar implicature computation, al-though this set of alternatives may be broader than previouslyassumed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Pragmatics; development; scalar implicature; dif-fusion models"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/12c460pq",
            "frozenauthors": [
                {
                    "first_name": "Rose",
                    "middle_name": "M.",
                    "last_name": "Schneider",
                    "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": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26470/galley/16106/download/"
                }
            ]
        },
        {
            "pk": 26621,
            "title": "Assessing children’s reading comprehension by the component processes tasks",
            "subtitle": null,
            "abstract": "The purposes of this study were to develop a theoretical-based, comprehension process assessment and to measurechildren’s reading comprehension processes. This assessment was based on Hannon & Daneman’s (2001) paradigm and Han-non & Frias’ (2012) component processes tasks, including the memory measure, the inference measure, knowledge access andintegration measure, and modified to two parts in order to assess 4th to 6th graders’ reading comprehension processes. Wereduced the difficulties and complexity of this comprehension measure for younger children. Four-hundred-and-fifty partic-ipants (at 4th to 6th grade level) were recruited from four elementary schools in Chia-Yi, Taiwan. The results show that theCronbach’s alpha coefficients were .75 to .87 and the citerion-reference validity was around .70 to .75 with the Chinese ReadingComprehension Test. There were good item discriminations and difficulties, analysed by the Rash model.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/0d9709wq",
            "frozenauthors": [
                {
                    "first_name": "Chi-Shun",
                    "middle_name": "",
                    "last_name": "Lien",
                    "name_suffix": "",
                    "institution": "National Chung Cheng University",
                    "department": ""
                },
                {
                    "first_name": "Yuhtsuen",
                    "middle_name": "",
                    "last_name": "Tzneg",
                    "name_suffix": "",
                    "institution": "National Chung Cheng University",
                    "department": ""
                },
                {
                    "first_name": "Hsin",
                    "middle_name": "",
                    "last_name": "Chien",
                    "name_suffix": "",
                    "institution": "National Taitung University",
                    "department": ""
                },
                {
                    "first_name": "Chin-Chih",
                    "middle_name": "",
                    "last_name": "Chen",
                    "name_suffix": "",
                    "institution": "National Chung Cheng University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26621/galley/16257/download/"
                }
            ]
        },
        {
            "pk": 26598,
            "title": "Assessing Science Inquiry using MDP Goal Detectors",
            "subtitle": null,
            "abstract": "Complex cognitive tasks, such as science inquiry, often involve a sequence of goals, each of which is pursuedthrough a sequence of actions. Effective assessment of inquiry performance requires identification of these student goals.Markov decision processes (MDPs) have been used to infer goals and beliefs over a single directed sequence of actions (Bakeret al., 2009), but multi-goal complex systems are computationally prohibitive to model. This research investigates the useof targeted MDPs as goal detectors, embedded within a larger hidden Markov model (HMM) that accounts for the transitionbetween goals. This multi-layer approach allows the MDP state spaces to remain small while modeling complex cognition.Because canonical HMM estimation is complicated by the dynamic nature of MDPs, in which action probabilities depend oncontext, we explore several different estimation methods. The approach is applied to log-file data of test-taker interactions witha simulation-based science inquiry assessment.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/4v2533s4",
            "frozenauthors": [
                {
                    "first_name": "Michelle",
                    "middle_name": "",
                    "last_name": "Lamar",
                    "name_suffix": "",
                    "institution": "Educational Testing Service",
                    "department": ""
                },
                {
                    "first_name": "Janet",
                    "middle_name": "Koster van",
                    "last_name": "Groos",
                    "name_suffix": "",
                    "institution": "Educational Testing Service",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26598/galley/16234/download/"
                }
            ]
        },
        {
            "pk": 26692,
            "title": "A subject-object asymmetry in the online processing of ’only’: evidence fromeye-tracking",
            "subtitle": null,
            "abstract": "While most formal semantic accounts of focus-sensitive particles such as ‘only’ acknowledge that their interpretationrequires the integration of contextual information with the linguistic representation, it is less clear how this interaction playsout in real-time. Recent psycholinguistic work in this domain favors an incremental processing story, but divergent resultselsewhere complicate this picture. Our findings from two Visual World eye-tracking studies (n = 33, 32) help resolve thisconflict, and confirm the existence of an adult processing asymmetry: sentences in which ‘only’ associates with the subject(’Only John bought an apple’) take longer to process than object-only sentences (’John only bought an apple’). We find thatcurrent accounts of the representation and exhaustification of propositional alternatives invoked by ’only’ do not explain thiseffect. We suggest that differences at the event-structural level — which propositional alternatives arguably map onto — mightexplain the asymmetry.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/480894sp",
            "frozenauthors": [
                {
                    "first_name": "Pooja",
                    "middle_name": "",
                    "last_name": "Paul",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Tanya",
                    "middle_name": "",
                    "last_name": "Levari",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Dylan",
                    "middle_name": "",
                    "last_name": "Hardenbergh",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                },
                {
                    "first_name": "Jesse",
                    "middle_name": "",
                    "last_name": "Snedeker",
                    "name_suffix": "",
                    "institution": "Harvard University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26692/galley/16328/download/"
                }
            ]
        },
        {
            "pk": 26586,
            "title": "Asymmetric derivational priming in recognition of Greek nouns and verbs",
            "subtitle": null,
            "abstract": "We examined differences between the processing of inflectional versus derivational morphology, using Greek nounsand verbs with a primed lexical decision task. Previous work suggested that both noun and verb targets were significantlyprimed by the same grammatical class. However, when preceded by different grammatical class, verb but not noun targetsshowed priming. We attributed the asymmetrical priming to the materials used: noun stimuli were derived by their verbcounterparts, suggesting an important inherent asymmetry between nouns and verbs. To further investigate this suggestion,we used materials with the opposite asymmetry (verbs derived by nouns) expecting an asymmetry in the opposite direction toemerge for derivationally related words. A clear explanation of the asymmetry would allow us conclusions about the (debated)existence of differences in representation and processing between inflectional and derivational morphological relations and thusprovide evidence for or against a fully decompositional view of processing morphologically complex words.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2hb4j4mz",
            "frozenauthors": [
                {
                    "first_name": "Sofia",
                    "middle_name": "",
                    "last_name": "Loui",
                    "name_suffix": "",
                    "institution": "University of Athens",
                    "department": ""
                },
                {
                    "first_name": "Athanassios",
                    "middle_name": "",
                    "last_name": "Protopapas",
                    "name_suffix": "",
                    "institution": "University of Athens",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26586/galley/16222/download/"
                }
            ]
        },
        {
            "pk": 26157,
            "title": "A Tale of Two Disasters: Biases in Risk Communication",
            "subtitle": null,
            "abstract": "Risk communication, where scientists inform policy-makersor the populace of the probability and magnitude of possibledisasters, is essential to disaster management – enablingpeople to make better decisions regarding preventative steps,evacuations, etc. Psychological research, however, hasidentified multiple biases that can affect people’sinterpretation of probabilities and thus risk. For example,availability (Tversky & Kahneman, 1973) is known toconfound probability estimates while the description-experience gap (D-E Gap) (Hertwig & Erev, 2009) shows lowprobability events being over-weighted when described andunder-weighted when learnt from laboratory tasks. This paperexamines how probability descriptions interact with realworld experience of events. Responses from 294 participantsacross 8 conditions showed that people’s responses, given thesame described probabilities and consequences, were alteredby their familiarity with the disaster (bushfire vs earthquake)and its salience to them personally. The implications of thisfor risk communication are discussed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "description-experience gap; risk communication;decision making; availability; bias."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/5mv5t7j9",
            "frozenauthors": [
                {
                    "first_name": "Matthew",
                    "middle_name": "",
                    "last_name": "Welsh",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Sandy",
                    "middle_name": "",
                    "last_name": "Steacy",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Steve",
                    "middle_name": "",
                    "last_name": "Begg",
                    "name_suffix": "",
                    "institution": "University of Adelaide",
                    "department": ""
                },
                {
                    "first_name": "Daniel",
                    "middle_name": "",
                    "last_name": "Navarro",
                    "name_suffix": "",
                    "institution": "The University of New South Wales",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26157/galley/15793/download/"
                }
            ]
        },
        {
            "pk": 26135,
            "title": "A test of two models of probability judgment: quantum versus noisy probability",
            "subtitle": null,
            "abstract": "We test contrasting predictions of two recent models of proba-bility judgment: the quantum probability model (Busemeyeret al., 2011) and the probability theory plus noise model(Costello and Watts, 2014). Both models assume that peo-ple estimate probability using formal processes that follow orsubsume standard probability theory. The quantum probabil-ity model predicts people’s estimates should agree with oneset of probability theory identities, while the probability the-ory plus noise model predicts a specific pattern of violation ofthose identities. Experimental results show just the form of vi-olation predicted by the probability theory plus noise model.These results suggest that people’s probability judgments donot follow quantum probability: instead, they follow the rulesof standard probability theory, with the systematic biases seenin those judgments due to the effects of random noise.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/1w83n9nr",
            "frozenauthors": [
                {
                    "first_name": "Fintan",
                    "middle_name": "J.",
                    "last_name": "Costello",
                    "name_suffix": "",
                    "institution": "University College Dublin",
                    "department": ""
                },
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Watts",
                    "name_suffix": "",
                    "institution": "National University of Ireland Maynooth,",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26135/galley/15771/download/"
                }
            ]
        },
        {
            "pk": 26682,
            "title": "Attentional Enhancement at Event Boundaries",
            "subtitle": null,
            "abstract": "A fundamental aspect of everyday processing involves identifying discrete events within continuously unfoldingsensory experience. However, the processes enabling determination of event boundaries remain poorly understood. Recently,inconsistent conclusions have emerged regarding attentional processes associated with detection of event boundaries. Use ofthe Dwell-Time Paradigm has indicated enhanced attention at event boundaries (e.g., Hard, Recchia, & Tversky, 2011), whereasevidence from the Rapid Serial Visual Presentation paradigm (e.g., Huff, Papenmeier, & Zacks, 2012) indicates impairment.We employed a change-detection procedure similar to the RSVP, except that the change to be detected was uniform across theentire visual field, rather than varying with respect to the viewer’s spatial locus of attention. Changes occurred either at eventboundaries or mid-stream within event segments. With spatial locus of attention rendered irrelevant, participants displayedsignificantly faster reaction time to changes coinciding with event boundaries, implying that viewers selectively target eventboundaries with heightened attention.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/6x48k353",
            "frozenauthors": [
                {
                    "first_name": "Dare",
                    "middle_name": "",
                    "last_name": "Baldwin",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                },
                {
                    "first_name": "Eric",
                    "middle_name": "",
                    "last_name": "Pederson",
                    "name_suffix": "",
                    "institution": "University of Oregon",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26682/galley/16318/download/"
                }
            ]
        },
        {
            "pk": 26606,
            "title": "Attentional Resource Allocation in Multisensory Processing is Task-dependent",
            "subtitle": null,
            "abstract": "Human information processing is constrained by limited attentional resources. A matter of ongoing debate inmultisensory research is whether attentional resources are shared or distinct across sensory modalities. Previous researchsuggested that the type of tasks that humans perform in separate sensory modalities determines whether attentional resourcesare shared or distinct across sensory modalities. Here, we investigated the relation between attentional resources and theperformed type of tasks in four experiments using a dual task paradigm. We found shared attentional resources for vision,haptics and audition when two purely spatial tasks were performed in separate sensory modalities (Experiment 1 & 2) whilewe found distinct attentional resources for the same sensory modalities when a spatial task was performed together with adiscrimination task (Experiment 3 & 4). Overall, our findings suggest that the distribution of attentional resources is operatingat a task-level independent of the involved sensory modalities.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [],
            "section": "Member Abstracts",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/74b0q8sc",
            "frozenauthors": [
                {
                    "first_name": "Basil",
                    "middle_name": "",
                    "last_name": "Wahn",
                    "name_suffix": "",
                    "institution": "University of Osnabruck",
                    "department": ""
                },
                {
                    "first_name": "Peter",
                    "middle_name": "",
                    "last_name": "Konig",
                    "name_suffix": "",
                    "institution": "University of Osnabruck",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26606/galley/16242/download/"
                }
            ]
        },
        {
            "pk": 26172,
            "title": "Attention and the Development of Inductive Generalization: Evidence from\nRecognition Memory",
            "subtitle": null,
            "abstract": "Induction, the ability to generalize knowledge from known to\nnovel instances, is essential for human learning. This study\ninvestigates how attention allocation during category learning\nand induction affects what information is represented and\nencoded to memory. In Experiment 1 5-year-olds and adults\nlearned rule-based categories. They were then presented with\nan Induction-then-Recognition task. Similar to previous\nresults with familiar categories, children exhibited better\nmemory for items than adults. In Experiment 2, adults learned\nsimilarity-based categories and then were presented with an\nInduction-then-Recognition task. In this condition, adults’\nmemory was as good as children’s memory in Experiment 1.\nThese results indicate that the way categories are represented\naffects the way induction is performed.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Induction; Learning; Memory."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/2w2938z9",
            "frozenauthors": [
                {
                    "first_name": "Tracey",
                    "middle_name": "",
                    "last_name": "Miser",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                },
                {
                    "first_name": "Vladimir",
                    "middle_name": "",
                    "last_name": "Sloutsky",
                    "name_suffix": "",
                    "institution": "The Ohio State University",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26172/galley/15808/download/"
                }
            ]
        },
        {
            "pk": 26319,
            "title": "Attentive and Pre-Attentive Processes in Multiple Object Tracking:A Computational Investigation",
            "subtitle": null,
            "abstract": "The rich literature on multiple object tracking (MOT)conclusively demonstrates that humans are able to visuallytrack a small number of objects. There is considerably lessagreement on what perceptual and cognitive processes areinvolved. While it is clear that MOT is attentionallydemanding, various accounts of MOT performance centrallyinvolve pre-attentional mechanisms as well. In this paper wepresent an account of object tracking in the ARCADIAcognitive system that treats MOT as dependent upon both pre-attentive and attention-bound processes. We show that withminimal addition this model replicates a variety of corephenomena in the MOT literature and provides an algorithmicexplanation of human performance limitations.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "attention; visual cognition; multiple objecttracking; cognitive model"
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/7vr0w165",
            "frozenauthors": [
                {
                    "first_name": "Paul",
                    "middle_name": "",
                    "last_name": "Bello",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Will",
                    "middle_name": "",
                    "last_name": "Bridewell",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                },
                {
                    "first_name": "Christina",
                    "middle_name": "",
                    "last_name": "Wasylyshyn",
                    "name_suffix": "",
                    "institution": "Naval Research Laboratory",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26319/galley/15955/download/"
                }
            ]
        },
        {
            "pk": 26142,
            "title": "Attractivity Weighting: Take-the-Best’s Foolproof Sibling",
            "subtitle": null,
            "abstract": "We describe a prediction method called “Attractivity\nWeighting” (AW). In the case of cue-based paired\ncomparison tasks, AW predicts a weighted average of the cue\nvalues of the most successful cues. In many situations, AW’s\nprediction is based on the cue value of the most successful\ncue, resulting in behavior similar to Take-the-Best (TTB).\nUnlike TTB, AW has a desirable characteristic called “access\noptimality”: Its long-run success is guaranteed to be at least as\ngreat as the most successful cue. While access optimality is a\ndesirable characteristic, concerns may be raised about the\nshort-term performance of AW. To evaluate such concerns,\nwe here present a study of AW’s short-term performance. The\nresults suggest that there is little reason to worry about the\nshort-run performance of AW. Our study also shows that, in\nrandom sequences of paired comparison tasks, the behavior of\nAW and TTB is nearly indiscernible.",
            "language": "eng",
            "license": {
                "name": "",
                "short_name": "",
                "text": null,
                "url": ""
            },
            "keywords": [
                {
                    "word": "Bounded Rationality; Ecological Rationality;\nAttractivity Weighting; Take-the-Best; Meta-induction."
                }
            ],
            "section": "Papers",
            "is_remote": true,
            "remote_url": "https://escholarship.org/uc/item/45j8w37c",
            "frozenauthors": [
                {
                    "first_name": "Paul",
                    "middle_name": "D.",
                    "last_name": "Thorn",
                    "name_suffix": "",
                    "institution": "University of Duesseldorf",
                    "department": ""
                },
                {
                    "first_name": "Gerhard",
                    "middle_name": "",
                    "last_name": "Schurz",
                    "name_suffix": "",
                    "institution": "University of Duesseldorf",
                    "department": ""
                }
            ],
            "date_submitted": null,
            "date_accepted": null,
            "date_published": "2016-01-01T20:00:00+02:00",
            "render_galley": null,
            "galleys": [
                {
                    "label": "PDF",
                    "type": "pdf",
                    "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26142/galley/15778/download/"
                }
            ]
        }
    ]
}