Letting structure emerge: connectionist and dynamical systems approaches to cognition

[1]  J. Tenenbaum,et al.  Probabilistic models of cognition: exploring representations and inductive biases , 2010, Trends in Cognitive Sciences.

[2]  K. Plunkett,et al.  A neurocomputational account of taxonomic responding and fast mapping in early word learning. , 2010, Psychological review.

[3]  Naomi H. Feldman,et al.  The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference. , 2009, Psychological review.

[4]  Harald Maurer,et al.  Paul Smolensky, Géraldine Legendre: The Harmonic Mind. From Neural Computation to Optimality-Theoretic Grammar. Vol. 1: Cognitive Architecture. Vol. 2: Linguistic and Philosophical Implications , 2009 .

[5]  James L. McClelland,et al.  A connectionist model of a continuous developmental transition in the balance scale task , 2009, Cognition.

[6]  J. Tenenbaum,et al.  Structured statistical models of inductive reasoning. , 2009, Psychological review.

[7]  Joe Pater The harmonic mind : from neural computation to optimality-theoretic grammar , 2009 .

[8]  T. Griffiths Probabilistic models of cognition 1 Running head : PROBABILISTIC MODELS OF COGNITION Probabilistic models of cognition : Exploring the laws of thought , 2009 .

[9]  Linda B. Smith,et al.  Cue salience and infant perseverative reaching: tests of the dynamic field theory. , 2009, Developmental science.

[10]  James L. McClelland,et al.  When Should We Expect Indirect Effects in Human Contingency Learning , 2009 .

[11]  James L. McClelland,et al.  Semantic Cognition : Its Nature , Its Development , and Its Neural Basis , 2008 .

[12]  Matthew Botvinick,et al.  Goal-directed decision making in prefrontal cortex: a computational framework , 2008, NIPS.

[13]  James L. McClelland,et al.  A simple model from a powerful framework that spans levels of analysis , 2008, Behavioral and Brain Sciences.

[14]  B. Hopkins,et al.  Postural change effects on infants' AB task performance: visual, postural, or spatial? , 2007, Journal of experimental child psychology.

[15]  Mark S. Seidenberg,et al.  Graded semantic and phonological similarity effects in priming: evidence for a distributed connectionist approach to morphology. , 2007, Journal of experimental psychology. General.

[16]  Geoffrey E. Hinton,et al.  Reducing the Dimensionality of Data with Neural Networks , 2006, Science.

[17]  Linda B Smith,et al.  Young infants reach correctly in A-not-B tasks: on the development of stability and perseveration. , 2006, Infant behavior & development.

[18]  Matthew M Botvinick,et al.  Short-term memory for serial order: a recurrent neural network model. , 2006, Psychological review.

[19]  Géraldine Legendre,et al.  The harmonic mind: From neural computation to optimality-theoretic grammar (Vol. 2: Linguistic and philosophical implications). , 2006 .

[20]  J. Tenenbaum,et al.  Poverty of the Stimulus? A Rational Approach , 2006 .

[21]  James L. McClelland,et al.  Alternatives to the combinatorial paradigm of linguistic theory based on domain general principles of human cognition , 2005 .

[22]  Linda B. Smith,et al.  From the lexicon to expectations about kinds: a role for associative learning. , 2005, Psychological review.

[23]  James L. McClelland,et al.  Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks , 2005, Machine Learning.

[24]  P. Smolensky,et al.  Optimality Theory: Constraint Interaction in Generative Grammar , 2004 .

[25]  James L. McClelland,et al.  Semantic Cognition: A Parallel Distributed Processing Approach , 2004 .

[26]  Alison Gopnik,et al.  Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers , 2004, Cogn. Sci..

[27]  D. Plaut,et al.  Doing without schema hierarchies: a recurrent connectionist approach to normal and impaired routine sequential action. , 2004, Psychological review.

[28]  J. Elman Distributed representations, simple recurrent networks, and grammatical structure , 1991, Machine Learning.

[29]  James L. McClelland,et al.  Structure and deterioration of semantic memory: a neuropsychological and computational investigation. , 2004, Psychological review.

[30]  S. Pinker,et al.  The past and future of the past tense , 2002, Trends in Cognitive Sciences.

[31]  James L. McClelland,et al.  Rules or connections in past-tense inflections: what does the evidence rule out? , 2002, Trends in Cognitive Sciences.

[32]  David C. Plaut,et al.  A connectionist model of sentence comprehension and production , 2002 .

[33]  Han L. J. van der Maas,et al.  Evidence for the Phase Transition from Rule I to Rule II on the Balance Scale Task , 2001 .

[34]  J. Hay Lexical frequency in morphology: Is everything relative? , 2001 .

[35]  Linda B. Smith,et al.  Tests of a dynamic systems account of the A-not-B error: the influence of prior experience on the spatial memory abilities of two-year-olds. , 2001, Child development.

[36]  E. Thelen,et al.  The dynamics of embodiment: A field theory of infant perseverative reaching , 2001, Behavioral and Brain Sciences.

[37]  Steven Johnson,et al.  Emergence: The Connected Lives of Ants, Brains, Cities, and Software , 2001 .

[38]  Kathy Hirsh-Pasek,et al.  An Emergentist Coalition Model for Word Learning , 2000 .

[39]  Roberta Michnick Golinkoff,et al.  Becoming a word learner : a debate on lexical acquisition , 2000 .

[40]  Esther Thelen,et al.  Motor memory is a factor in infant perseverative errors , 2000 .

[41]  David C. Plaut,et al.  Are non-semantic morphological effects incompatible with a distributed connectionist approach to lexical processing? , 2000 .

[42]  Douglas L. T. Rohde,et al.  Language acquisition in the absence of explicit negative evidence: how important is starting small? , 1999, Cognition.

[43]  Mark S. Seidenberg,et al.  Impairments in verb morphology after brain injury: a connectionist model. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[44]  Linda B. Smith,et al.  Knowing in the context of acting: the task dynamics of the A-not-B error. , 1999, Psychological review.

[45]  B. MacWhinney Models of the emergence of language. , 1998, Annual review of psychology.

[46]  James L. McClelland,et al.  Familiarity breeds differentiation: a subjective-likelihood approach to the effects of experience in recognition memory. , 1998, Psychological review.

[47]  James L. McClelland,et al.  Understanding normal and impaired word reading: computational principles in quasi-regular domains. , 1996, Psychological review.

[48]  Linda B. Smith,et al.  A Dynamic Systems Approach to the Development of Cognition and Action , 2007, Journal of Cognitive Neuroscience.

[49]  James L. McClelland,et al.  Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. , 1995, Psychological review.

[50]  R. Baillargeon How Do Infants Learn About the Physical World? , 1994 .

[51]  E. Bates,et al.  Continuity in lexical and morphological development: a test of the critical mass hypothesis , 1994, Journal of Child Language.

[52]  Javier R. Movellan,et al.  Learning Continuous Probability Distributions with Symmetric Diffusion Networks , 1993, Cogn. Sci..

[53]  Peter M. Todd,et al.  Learning and connectionist representations , 1993 .

[54]  Mark F. St. John,et al.  The Story Gestalt: A Model of Knowledge-Intensive Processes in Text Comprehension , 1992, Cogn. Sci..

[55]  Michael W. Montgomery,et al.  The quantitative description of action disorganisation after brain damage: a case study , 1991 .

[56]  James L. McClelland,et al.  A computational model of semantic memory impairment: modality specificity and emergent category specificity. , 1991, Journal of experimental psychology. General.

[57]  James L. McClelland,et al.  Learning and Applying Contextual Constraints in Sentence Comprehension , 1990, Artif. Intell..

[58]  R Ratcliff,et al.  Connectionist models of recognition memory: constraints imposed by learning and forgetting functions. , 1990, Psychological review.

[59]  Jeffrey L. Elman,et al.  Finding Structure in Time , 1990, Cogn. Sci..

[60]  R. Morris Parallel Distributed Processing: Implications for Psychology and Neurobiology , 1990 .

[61]  Rochel Gelman,et al.  First Principles Organize Attention to and Learning About Relevant Data: Number and the Animate-Inanimate Distinction as Examples , 1990, Cogn. Sci..

[62]  James L. McClelland,et al.  A distributed, developmental model of word recognition and naming. , 1989, Psychological review.

[63]  Michael McCloskey,et al.  Catastrophic Interference in Connectionist Networks: The Sequential Learning Problem , 1989 .

[64]  James L. McClelland Parallel Distributed Processing: Implications for Cognition and Development , 1988 .

[65]  E. Butterfield,et al.  Are children's rule-assessment classifications invariant across instances of problem types? , 1986, Child development.

[66]  E. Markman,et al.  Categories and induction in young children , 1986, Cognition.

[67]  Geoffrey E. Hinton,et al.  Schemata and Sequential Thought Processes in PDP Models , 1986 .

[68]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[69]  Joan L. Bybee Morphology: A study of the relation between meaning and form , 1985 .

[70]  F. Keil Constraints on knowledge and cognitive development. , 1981 .

[71]  J. Bates Cerebral control of movement. , 1968, Electroencephalography and clinical neurophysiology.

[72]  D. Denny-Brown,et al.  cerebral control of movement , 1966 .

[73]  Noam Chomsky,et al.  वाक्यविन्यास का सैद्धान्तिक पक्ष = Aspects of the theory of syntax , 1965 .

[74]  J. Piaget The construction of reality in the child , 1954 .