Learning the structure of event sequences.

How is complex sequential material acquired, processed, and represented when there is no intention to learn? Two experiments exploring a choice reaction time task are reported. Unknown to Ss, successive stimuli followed a sequence derived from a "noisy" finite-state grammar. After considerable practice (60,000 exposures) with Experiment 1, Ss acquired a complex body of procedural knowledge about the sequential structure of the material. Experiment 2 was an attempt to identify limits on Ss ability to encode the temporal context by using more distant contingencies that spanned irrelevant material. Taken together, the results indicate that Ss become increasingly sensitive to the temporal context set by previous elements of the sequence, up to 3 elements. Responses are also affected by priming effects from recent trials. A connectionist model that incorporates sensitivity to the sequential structure and to priming effects is shown to capture key aspects of both acquisition and processing and to account for the interaction between attention and sequence structure reported by Cohen, Ivry, and Keele (1990).

[1]  D. Hebb.  Distinctive features of learning in the higher animal , 1961 .

[2]  M. A. Stadler,et al.  On learning complex procedural knowledge. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[3]  Edward G. Carmines,et al.  Reliability and Validity Assessment , 1979 .

[4]  James L. McClelland,et al.  Finite State Automata and Simple Recurrent Networks , 1989, Neural Computation.

[5]  Frank Restle,et al.  Theory of Serial Pattern Learning: Structural Trees. , 1970 .

[6]  E. Soetens,et al.  Expectancy or Automatic Facilitation? Separating Sequential Effects in Two-Choice Reaction Time , 1985 .

[7]  M. Nissen,et al.  Attentional requirements of learning: Evidence from performance measures , 1987, Cognitive Psychology.

[8]  A. Reber.  Implicit learning and tacit knowledge , 1993 .

[9]  P. J. Jennings,et al.  A Computational Model of Attentional Requirements in Sequence Learning , 1991 .

[10]  J. Elman.  Representation and structure in connectionist models , 1991 .

[11]  R. Remington.  Analysis of sequential effects in choice reaction times. , 1969, Journal of experimental psychology.

[12]  Arthur S. Reber,et al.  Syntactical learning and judgment, still unconscious and still abstract: Comment on Dulany, Carlson, and Dewey , 1985 .

[13]  Jonathan D. Cohen,et al.  A Parallel Distributed Processing Approach to Behavior and Biology in Schizophrenia , 1989 .

[14]  D. Broadbent,et al.  Two modes of learning for interactive tasks , 1988, Cognition.

[15]  H. Hoffman,et al.  Unconscious acquisition of complex procedural knowledge. , 1987 .

[16]  D. J.,et al.  A PARALLEL DISTRIBUTED PROCESSING ( APPROACH TO BEHAVIOR AND BIOLOGY IN SCHIZOPHRENIA , 2022 .

[17]  W. Estes.  The cognitive side of probability learning. , 1976 .

[18]  Geoffrey E. Hinton.  Using fast weights to deblur old memories , 1987 .

[19]  James L. McClelland,et al.  On the control of automatic processes: a parallel distributed processing account of the Stroop effect. , 1990, Psychological review.

[20]  A. Reber.  Implicit learning of artificial grammars , 1967 .

[21]  R. Hyman.  Stimulus information as a determinant of reaction time. , 1953, Journal of experimental psychology.

[22]  J. C. Falmagne,et al.  Stochastic models for choice reaction time with applications to experimental results , 1965 .

[23]  John R. Anderson,et al.  Learning Artificial Grammars With Competitive Chunking , 1990 .

[24]  James L. McClelland,et al.  Distributed memory and the representation of general and specific information. , 1985, Journal of experimental psychology. General.

[25]  D. Schacter.  Implicit memory: History and current status. , 1987 .

[26]  Richard B. Millward,et al.  PROBABILITY LEARNING: CONTINGENT-EVENT SCHEDULES WITH LAGS , 1972 .

[27]  Eugene Galanter,et al.  Handbook of mathematical psychology: I. , 1963 .

[28]  B. Mittelman,et al.  On control. , 1979, Dental management.

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

[30]  Michael I. Jordan.  Attractor dynamics and parallelism in a connectionist sequential machine , 1990 .

[31]  J. Delafresnaye,et al.  Brain mechanisms and learning , 1961 .

[32]  Richard A. Carlson,et al.  On consciousness in syntactic learning and judgment: A reply to Reber, Allen, and Regan , 1985 .

[33]  Pawel Lewicki,et al.  Acquisition of procedural knowledge about a pattern of stimuli that cannot be articulated , 1988, Cognitive Psychology.

[34]  Daniel B. Willingham,et al.  On the development of procedural knowledge. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[35]  Richard I. Ivry,et al.  Attention and structure in sequence learning. , 1990 .

[36]  R. A. Carlson,et al.  A case of syntactical learning and judgment: How conscious and how abstract? , 1984 .

[37]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[38]  James L. McClelland,et al.  Learning Subsequential Structure in Simple Recurrent Networks , 1988, NIPS.

[39]  P. Bertelson.  Sequential Redundancy and Speed in a Serial Two-Choice Responding Task , 1961 .

[40]  D. Broadbent,et al.  On the Relationship between Task Performance and Associated Verbalizable Knowledge , 1984 .

[41]  Richard B. Millward,et al.  Event-recall in probability learning , 1968 .

[42]  James L. McClelland,et al.  Parallel Distributed Processing: Bridging the gap between human and machine intelligence , 1990 .

[43]  D. M. Green,et al.  Detection and recognition. , 1978 .

[44]  Donald Laming,et al.  Subjective probability in choice-reaction experiments ☆ , 1969 .

[45]  G. Miller,et al.  Free recall of redundant strings of letters. , 1958, Journal of experimental psychology.

[46]  Allen Newell,et al.  Human Problem Solving. , 1973 .

[47]  R W Pew,et al.  Levels of analysis in motor control. , 1974, Brain research.