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  1. Toward a modern theory of adaptive networks: Expectation and prediction.Richard S. Sutton & Andrew G. Barto - 1981 - Psychological Review 88 (2):135-170.
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  • Studies of interference in serial verbal reactions.J. R. Stroop - 1935 - Journal of Experimental Psychology 18 (6):643.
  • The Structure and Organization of Memory.L. R. Squire, B. Knowlton & G. Musen - 1993 - Annual Review of Psychology 44:453-495.
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  • Declarative and Nondeclarative Memory: Multiple Brain Systems Supporting Learning and Memory.Larry R. Squire - 1992 - Journal of Cognitive Neuroscience 4:232-243.
    The topic of multiple forms of memory is considered from a biological point of view. Fact-and-event (declarative, explicit) memory is contrasted with a collection of non conscious (non-declarative, implicit) memory abilities including skills and habits, priming, and simple conditioning. Recent evidence is reviewed indicating that declarative and non declarative forms of memory have different operating characteristics and depend on separate brain systems. A brain-systems framework for understanding memory phenomena is developed in light of lesion studies involving rats, monkeys, and humans, (...)
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  • Controlled and automatic human information processing: Perceptual learning, automatic attending, and a general theory.Richard M. Shiffrin & Walter Schneider - 1977 - Psychological Review 84 (2):128-90.
    Tested the 2-process theory of detection, search, and attention presented by the current authors in a series of experiments. The studies demonstrate the qualitative difference between 2 modes of information processing: automatic detection and controlled search; trace the course of the learning of automatic detection, of categories, and of automatic-attention responses; and show the dependence of automatic detection on attending responses and demonstrate how such responses interrupt controlled processing and interfere with the focusing of attention. The learning of categories is (...)
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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.
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  • Controlled and automatic human information processing: I. Detection, search, and attention.Walter Schneider & Richard M. Shiffrin - 1977 - Psychological Review 84 (1):1-66.
  • 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.
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  • 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.
  • Distributed memory and the representation of general and specific information.James L. McClelland & David E. Rumelhart - 1985 - Journal of Experimental Psychology 114 (2):159-188.
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  • Implementations are not conceptualizations: Revising the verb learning model.Brian MacWhinney & Jared Leinbach - 1991 - Cognition 40 (1-2):121-157.
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  • Toward an instance theory of automatization.Gordon D. Logan - 1988 - Psychological Review 95 (4):492-527.
  • Forward Models: Supervised Learning with a Distal Teacher.Michael I. Jordan & David E. Rumelhart - 1992 - Cognitive Science 16 (3):307-354.
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  • Connectionist Models and Linguistic Theory: Investigations of Stress Systems in Language.Prahlad Gupta & David S. Touretzky - 1994 - Cognitive Science 18 (1):1-50.
    We question the widespread assumption that linguistic theory should guide the formulation of mechanistic accounts of human language processing. We develop a pseudo‐linguistic theory for the domain of linguistic stress, based on observation of the learning behavior of a perceptron exposed to a variety of stress patterns. There are significant similarities between our analysis of perception stress learning and metrical phonology, the linguistic theory of human stress. Both approaches attempt to identify salient characteristics of the stress systems under examination without (...)
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  • 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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  • Structure and Content in Language Production: A Theory of Frame Constraints in Phonological Speech Errors.Gary S. Dell, Cornell Juliano & Anita Govindjee - 1993 - Cognitive Science 17 (2):149-195.
    Theories of language production propose that utterances are constructed by a mechanism that separates linguistic content from linguistic structure, Linguistic content is retrieved from the mental lexicon, and is then inserted into slots in linguistic structures or frames. Support for this kind of model at the phonological level comes from patterns of phonological speech errors. W present an alternative account of these patterns using a connectionist or parallel distributed proceesing (PDP) model that learns to produce sequences of phonological features. The (...)
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  • Connectionist Models of Language Production: Lexical Access and Grammatical Encoding.Gary S. Dell, Franklin Chang & Zenzi M. Griffin - 1999 - Cognitive Science 23 (4):517-542.
    Theories of language production have long been expressed as connectionist models. We outline the issues and challenges that must be addressed by connectionist models of lexical access and grammatical encoding, and review three recent models. The models illustrate the value of an interactive activation approach to lexical access in production, the need for sequential output in both phonological and grammatical encoding, and the potential for accounting for structural effects on errors and structural priming from learning.
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  • On the control of automatic processes: A parallel distributed processing account of the Stroop effect.Jonathan D. Cohen, Kevin Dunbar & James L. McClelland - 1990 - Psychological Review 97 (3):332-361.
  • From conceptual roles to structural relations: Bridging the syntactic cleft.Kathryn Bock, Helga Loebell & Randal Morey - 1992 - Psychological Review 99 (1):150-171.
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  • Framing sentences.K. Bock - 1990 - Cognition 35 (1):1-39.
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  • Acquisition of cognitive skill.John R. Anderson - 1982 - Psychological Review 89 (4):369-406.
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  • .J. L. McClelland & D. E. Rumelhart (eds.) - 1987 - MIT Press.
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  • Mechanisms of Implicit Learning: Connectionist Models of Sequence Processing.Axel Cleeremans - 1993 - MIT Press.
    What do people learn when they do not know that they are learning? Until recently, all of the work in the area of implicit learning focused on empirical questions and methods. In this book, Axel Cleeremans explores unintentional learning from an information-processing perspective. He introduces a theoretical framework that unifies existing data and models on implicit learning, along with a detailed computational model of human performance in sequence-learning situations.
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  • Finite state automata and simple recurrent networks.Axel Cleeremans & David Servan-Schreiber - unknown
    We explore a network architecture introduced by Elman (1988) for predicting successive elements of a sequence. The network uses the pattern of activation over a set of hidden units from time-step 25-1, together with element t, to predict element t + 1. When the network is trained with strings from a particular finite-state grammar, it can learn to be a perfect finite-state recognizer for the grammar. When the network has a minimal number of hidden units, patterns on the hidden units (...)
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  • {Finding structure in time}.J. Elman - 1993 - {Cognitive Science} 48:71-99.
     
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  • Implicit memory: History and current status.Daniel L. Schacter - 1987 - Journal of Experimental Psychology 13 (3):501-18.
    Je lui ai associÉ un court extrait d'une revue de questions portant sur le même thème. Implicit memory is revealed when previous experiences facilitate perf on a task that does not require conscious or intentional recollection of those expces. Explicit memory is revealed when perf on a task requires conscious recolelction of previous expces. Il s'agit de defs descriptives qui n'impliquent pas l'existence de deux systs de mÉmo sÉparÉs. Historiquement Descartes est le premier ˆ faire mention de phÉnomènes de mÉmo (...)
     
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  • Implicit learning and tacit knowledge: An essay on the cognitive unconscious.Arthur S. Reber - 1993 - Oxford University Press.
    In this new volume in the Oxford Psychology Series, the author presents a highly readable account of the cognitive unconscious, focusing in particular on the problem of implicit learning. Implicit learning is defined as the acquisition of knowledge that takes place independently of the conscious attempts to learn and largely in the absence of explicit knowledge about what was acquired. One of the core assumptions of this argument is that implicit learning is a fundamental, "root" process, one that lies at (...)
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  • Is lexical processing just an ACT.Kim Kirsner & Craig Speelman - 1993 - In A. Collins, S. Gathercole, Martin A. Conway & P. E. Morris (eds.), Theories of Memory. Lawrence Erlbaum. pp. 303--326.
  • Toward an Instance Theory of Automatization.G. D. Logan - 1987 - Bulletin of the Psychonomic Society 25 (5):342-342.
  • Memory and working with memory: Evaluation of a component process model and comparisons with other models.Morris Moscovitch - 1994 - In Memory Systems. MIT Press. pp. 94.
  • Implicit memory.Kim Kirsner - 1998 - In K. Kirsner & G. Speelman (eds.), Implicit and Explicit Mental Processes. Lawrence Erlbaum. pp. 13--36.
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  • Controlled and automatic human information processing: I.Walter E. Schneider & Richard M. Shiffrin - 1977 - Detection, Search, and Attention. Psychological Review 84:1-66.
  • Memory systems of 1999.Daniel L. Schacter, Anthony D. Wagner & Randy L. Buckner - 2000 - In Tulving Endel & Craik Fergus I. M. (eds.), The Oxford handbook of memory. Oxford University Press.
    D. L. Schacter and E. Tulving (1994) argued for distinctions among 5 major memory systems: working memory, semantic memory, episodic memory, the perceptual representation system (PRS), and procedural memory. This chapter considers whether and in what way recent neuroimaging research has enhanced or changed the understanding of each of the 5 major systems that had been identified on cognitive and neuropsychological grounds by Schacter and Tulving. The logic and criteria introduced by Schacter and Tulving for identifying memory systems are first (...)
     
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