- An interactive activation model of context effects in letter perception: I. An account of basic findings.James L. McClelland & David E. Rumelhart - 1981 - Psychological Review 88 (5):375-407.details
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The perceptron: A probabilistic model for information storage and organization in the brain.F. Rosenblatt - 1958 - Psychological Review 65 (6):386-408.details
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Understanding normal and impaired word reading: Computational principles in quasi-regular domains.David C. Plaut, James L. McClelland, Mark S. Seidenberg & Karalyn Patterson - 1996 - Psychological Review 103 (1):56-115.details
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Learning and connectionist representations.David E. Rumelhart & Peter M. Todd - 1993 - In David E. Meyer & Sylvan Kornblum (eds.), Attention and Performance XIV: Synergies in Experimental Psychology, Artificial Intelligence, and Cognitive Neuroscience. MIT Press. pp. 3--30.details
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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.details
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Finding Structure in Time.Jeffrey L. Elman - 1990 - Cognitive Science 14 (2):179-211.details
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Feature discovery by competitive learning.David E. Rumelhart & David Zipser - 1985 - Cognitive Science 9 (1):75-112.details
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.J. L. McClelland & D. E. Rumelhart (eds.) - 1987 - MIT Press.details
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(1 other version)When is information explicitly represented?David Kirsh - 1990 - In Philip P. Hanson (ed.), Information, Language and Cognition. University of British Columbia Press.details
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Phonology, reading acquisition, and dyslexia: Insights from connectionist models.Michael W. Harm & Mark S. Seidenberg - 1999 - Psychological Review 106 (3):491-528.details
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(1 other version)Letting structure emerge: connectionist and dynamical systems approaches to cognition.James L. McClelland, Matthew M. Botvinick, David C. Noelle, David C. Plaut, Timothy T. Rogers, Mark S. Seidenberg & Linda B. Smith - 2010 - Trends in Cognitive Sciences 14 (8):348-356.details
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Six principles for biologically based computational models of cortical cognition.Randall C. O'Reilly - 1998 - Trends in Cognitive Sciences 2 (11):455-462.details
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Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.Matt Jones & Bradley C. Love - 2011 - Behavioral and Brain Sciences 34 (4):169-188.details
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(1 other version)A learning algorithm for boltzmann machines.David H. Ackley, Geoffrey E. Hinton & Terrence J. Sejnowski - 1985 - Cognitive Science 9 (1):147-169.details
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(1 other version)When is Information Explicitly Represented?David Kirsh - 1992 - The Vancouver Studies in Cognitive Science:340-365.details
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Probabilistic models of language processing and acquisition.Nick Chater & Christopher D. Manning - 2006 - Trends in Cognitive Sciences 10 (7):335–344.details
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The development of features in object concepts.Philippe G. Schyns, Robert L. Goldstone & Jean-Pierre Thibaut - 1998 - Behavioral and Brain Sciences 21 (1):1-17.details
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Computing the Meanings of Words in Reading: Cooperative Division of Labor Between Visual and Phonological Processes.Michael W. Harm & Mark S. Seidenberg - 2004 - Psychological Review 111 (3):662-720.details
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The Presence of a Symbol.Andy Clark - unknowndetails
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A distributed, developmental model of word recognition and naming.Mark S. Seidenberg & James L. McClelland - 1989 - Psychological Review 96 (4):523-568.details
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SUSTAIN: A Network Model of Category Learning.Bradley C. Love, Douglas L. Medin & Todd M. Gureckis - 2004 - Psychological Review 111 (2):309-332.details
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A Computational and Empirical Investigation of Graphemes in Reading.Conrad Perry, Johannes C. Ziegler & Marco Zorzi - 2013 - Cognitive Science 37 (5):800-828.details
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Nested incremental modeling in the development of computational theories: The CDP+ model of reading aloud.Conrad Perry, Johannes C. Ziegler & Marco Zorzi - 2007 - Psychological Review 114 (2):273-315.details
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Process of recognizing tachistoscopically presented words.David E. Rumelhart & Patricia Siple - 1974 - Psychological Review 81 (2):99-118.details
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