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  1. Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory.James L. McClelland, Bruce L. McNaughton & Randall C. O'Reilly - 1995 - Psychological Review 102 (3):419-457.
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  • An integrated theory of language production and comprehension.Martin J. Pickering & Simon Garrod - 2013 - Behavioral and Brain Sciences 36 (4):329-347.
    Currently, production and comprehension are regarded as quite distinct in accounts of language processing. In rejecting this dichotomy, we instead assert that producing and understanding are interwoven, and that this interweaving is what enables people to predict themselves and each other. We start by noting that production and comprehension are forms of action and action perception. We then consider the evidence for interweaving in action, action perception, and joint action, and explain such evidence in terms of prediction. Specifically, we assume (...)
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  • Whatever next? Predictive brains, situated agents, and the future of cognitive science.Andy Clark - 2013 - Behavioral and Brain Sciences 36 (3):181-204.
    Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...)
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  • The emulation theory of representation: Motor control, imagery, and perception.Rick Grush - 2004 - Behavioral and Brain Sciences 27 (3):377-396.
    The emulation theory of representation is developed and explored as a framework that can revealingly synthesize a wide variety of representational functions of the brain. The framework is based on constructs from control theory (forward models) and signal processing (Kalman filters). The idea is that in addition to simply engaging with the body and environment, the brain constructs neural circuits that act as models of the body and environment. During overt sensorimotor engagement, these models are driven by efference copies in (...)
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  • Developmental Changes in Cross‐Situational Word Learning: The Inverse Effect of Initial Accuracy.Stanka A. Fitneva & Morten H. Christiansen - 2017 - Cognitive Science 41 (S1):141-161.
    Intuitively, the accuracy of initial word-referent mappings should be positively correlated with the outcome of learning. Yet recent evidence suggests an inverse effect of initial accuracy in adults, whereby greater accuracy of initial mappings is associated with poorer outcomes in a cross-situational learning task. Here, we examine the impact of initial accuracy on 4-year-olds, 10-year-olds, and adults. For half of the participants most word-referent mappings were initially correct and for the other half most mappings were initially incorrect. Initial accuracy was (...)
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  • Word learning as Bayesian inference.Fei Xu & Joshua B. Tenenbaum - 2007 - Psychological Review 114 (2):245-272.
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  • (1 other version)Finding Structure in Time.Jeffrey L. Elman - 1990 - Cognitive Science 14 (2):179-211.
    Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on processing rather than explicitly (as in a spatial representation). The current report develops a proposal along these lines first described by Jordan (1986) which involves the use of recurrent links in order to provide networks with a dynamic memory. In this approach, hidden unit patterns are fed back to themselves: (...)
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  • The Pursuit of Word Meanings.Jon Scott Stevens, Lila R. Gleitman, John C. Trueswell & Charles Yang - 2017 - Cognitive Science 41 (S4):638-676.
    We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed Pursuit, uses an associative learning mechanism to estimate word-referent probability but pursues and tests the best referent-meaning at any given time. Pursuit is found to perform as well as global models under many conditions extracted from (...)
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  • Incremental interpretation at verbs: restricting the domain of subsequent reference.Gerry T. M. Altmann & Yuki Kamide - 1999 - Cognition 73 (3):247-264.
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  • A computational study of cross-situational techniques for learning word-to-meaning mappings.Jeffrey Mark Siskind - 1996 - Cognition 61 (1-2):39-91.
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  • An integrative account of constraints on cross-situational learning.Daniel Yurovsky & Michael C. Frank - 2015 - Cognition 145 (C):53-62.
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  • The development of a word-learning strategy.Justin Halberda - 2003 - Cognition 87 (1):B23-B34.
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  • The Effects of Feature-Label-Order and Their Implications for Symbolic Learning.Michael Ramscar, Daniel Yarlett, Melody Dye, Katie Denny & Kirsten Thorpe - 2010 - Cognitive Science 34 (6):909-957.
    Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood. We present a formal analysis of symbolic learning—in particular, word learning—in terms of prediction and cue competition, and we consider two possible ways in which symbols might be learned: by learning to predict a label from the features of objects and events in the world, and by learning to predict features from a (...)
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  • Word learning emerges from the interaction of online referent selection and slow associative learning.Bob McMurray, Jessica S. Horst & Larissa K. Samuelson - 2012 - Psychological Review 119 (4):831-877.
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  • Fast mapping word meanings across trials: Young children forget all but their first guess.Athulya Aravind, Jill de Villiers, Amy Pace, Hannah Valentine, Roberta Golinkoff, Kathy Hirsh-Pasek, Aquiles Iglesias & Mary Sweig Wilson - 2018 - Cognition 177 (C):177-188.
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  • The free-energy principle: a unified brain theory?Karl Friston - 2010 - Nature Reviews Neuroscience 11 (2):127–18.
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  • Becoming syntactic.Franklin Chang, Gary S. Dell & Kathryn Bock - 2006 - Psychological Review 113 (2):234-272.
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  • Where are the cookies? Two- and three-year-olds use number-marked verbs to anticipate upcoming nouns.Cynthia Lukyanenko & Cynthia Fisher - 2016 - Cognition 146 (C):349-370.
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  • Looking in the Wrong Direction Correlates With More Accurate Word Learning.Stanka A. Fitneva & Morten H. Christiansen - 2011 - Cognitive Science 35 (2):367-380.
    Previous research on lexical development has aimed to identify the factors that enable accurate initial word-referent mappings based on the assumption that the accuracy of initial word-referent associations is critical for word learning. The present study challenges this assumption. Adult English speakers learned an artificial language within a cross-situational learning paradigm. Visual fixation data were used to assess the direction of visual attention. Participants whose longest fixations in the initial trials fell more often on distracter images performed significantly better at (...)
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  • Learning and applying contextual constraints in sentence comprehension.Mark F. St John & James L. McClelland - 1990 - Artificial Intelligence 46 (1-2):217-257.
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  • Expectancy violations promote learning in young children.Aimee E. Stahl & Lisa Feigenson - 2017 - Cognition 163 (C):1-14.
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  • Beyond associations: Sensitivity to structure in pre-schoolers’ linguistic predictions.Chiara Gambi, Martin J. Pickering & Hugh Rabagliati - 2016 - Cognition 157 (C):340-351.
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  • Learning to use words: Event-related potentials index single-shot contextual word learning.Arielle Borovsky, Marta Kutas & Jeff Elman - 2010 - Cognition 116 (2):289-296.
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  • Predictable locations aid early object name learning.Viridiana L. Benitez & Linda B. Smith - 2012 - Cognition 125 (3):339-352.
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