Temporal effects in sequence learning

Through the use of double task conditions, the sequence learning (SL) paradigm offers unique opportunities to study the relationships between learning and attention. In their original study, Nissen & Bullemer (1987) argued that a secondary tone-counting task prevents SL because it exhausts participants’ attentional resources. Other authors have instead suggested that the detrimental effects of tone-counting are due to scheduling conflicts between performing the main and secondary tasks rather than to attentional load. Frensch & Miner (1994), for instance, suggested that the secondary task impairs sequence learning because it lengthens the response-to-stimulus interval (RSI) and hence makes it less likely for relevant contingencies to be represented together in short-term memory, — a condition for learning. Stadler (1995), on the other hand, argued that the secondary task introduces variability in the RSI and disrupts the organization of the sequence into chunks. Further, according to Willingham, Greenberg & Cannon Thomas (1997) manipulation of the RSI influences performance but not sequence learning per se. The goal of this paper is to further explore and clarify the role of the RSI in the SL paradigm. To do so, we systematically manipulated the RSI, and assessed performance through different objective and subjective measures. In contrast to previous results, we found that increasing the RSI improves explicit SL. We further show how a neural network model based on the Simple Recurrent Network can account for our data, even though the model neither uses decay nor develops chunked, declarative representations of the sequence. These findings suggest that RSI effects in SL are rooted in the temporal dynamics of learning. Temporal effects in sequence learning 3

[1]  Daniel B. Willingham,et al.  A Neuropsychological Theory of Motor Skill Learning , 2004 .

[2]  Axel Buchner,et al.  On the Role of Fragmentary Knowledge in a Sequence Learning Task , 1998 .

[3]  Axel Cleeremans,et al.  Implicit learning: news from the front , 1998, Trends in Cognitive Sciences.

[4]  James L. McClelland,et al.  Learning the structure of event sequences. , 1991, Journal of experimental psychology. General.

[5]  Axel Cleeremans,et al.  Implicit sequence learning: The truth is in the details , 1998 .

[6]  Richard I. Ivry,et al.  Attention and Structure in Sequence Learning , 2004 .

[7]  L. Jacoby A process dissociation framework: Separating automatic from intentional uses of memory , 1991 .

[8]  R. French,et al.  Implicit learning and consciousness: A graded, dynamic perspective , 2002 .

[9]  M. Amorim,et al.  Conscious knowledge and changes in performance in sequence learning: evidence against dissociation. , 1992, Journal of experimental psychology. Learning, memory, and cognition.

[10]  Tim Curran,et al.  Attentional and Nonattentional Forms of Sequence Learning , 1993 .

[11]  S. Kosslyn,et al.  A PET investigation of implicit and explicit sequence learning , 1995 .

[12]  Z. Dienes,et al.  Implicit learning: Below the subjective threshold , 1997 .

[13]  Axel Cleeremans,et al.  Comparing direct and indirect measures of sequence learning , 1996 .

[14]  Thomas Goschke,et al.  Implicit learning and unconscious knowledge: Mental representation, computational mechanisms, and brain structures. , 1997 .

[15]  Nick Chater,et al.  Toward a connectionist model of recursion in human linguistic performance , 1999, Cogn. Sci..

[16]  James L. McClelland On the time relations of mental processes: An examination of systems of processes in cascade. , 1979 .

[17]  Peder J. Johnson,et al.  Assessing implicit learning with indirect tests: Determining what is learned about sequence structure. , 1994 .

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

[19]  Axel Cleeremans,et al.  Can sequence learning be implicit? New evidence with the process dissociation procedure , 2001, Psychonomic bulletin & review.

[20]  James L. McClelland,et al.  The time course of perceptual choice: the leaky, competing accumulator model. , 2001, Psychological review.

[21]  Daniel B. Willingham,et al.  Response-to-stimulus interval does not affect implicit motor sequence learning, but does affect performance , 1997, Memory & cognition.

[22]  Ron Sun,et al.  From implicit skills to explicit knowledge: a bottom-up model of skill learning , 2001, Cogn. Sci..

[23]  J. van Leeuwen,et al.  Sequence Learning , 2001, Lecture Notes in Computer Science.

[24]  P. Frensch,et al.  Effects of presentation rate and individual differences in short-term memory capacity on an indirect measure of serial learning , 1994, Memory & cognition.

[25]  L. Henderson,et al.  Serial reaction time learning and Parkinson's disease: Evidence for a procedural learning deficit , 1995, Neuropsychologia.

[26]  A. Reber,et al.  The dual-task SRT procedure: Fine-tuning the timing , 2001, Psychonomic bulletin & review.

[27]  R. Ratcliff,et al.  Connectionist and diffusion models of reaction time. , 1999, Psychological review.

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

[29]  Thomas Goschke,et al.  Implicit learning of perceptual and motor sequences: Evidence for independent learning systems. , 1998 .

[30]  L. Squire,et al.  Encapsulation of Implicit and Explicit Memory in Sequence Learning , 1998, Journal of Cognitive Neuroscience.

[31]  Josef Perner,et al.  Implicit knowledge in people and connectionist networks , 1996 .

[32]  Edgar Erdfelder,et al.  A Multinomial Model to Assess Fluency and Recollection in a Sequence Learning Task , 1997 .

[33]  Christian Lebiere,et al.  Implicit and explicit learning in a hybrid architecture of cognition , 1999, Behavioral and Brain Sciences.

[34]  Richard S. Sutton,et al.  Learning to predict by the methods of temporal differences , 1988, Machine Learning.

[35]  E. Reingold,et al.  Using direct and indirect measures to study perception without awareness , 1988, Perception & psychophysics.

[36]  Axel Cleeremans,et al.  Mechanisms of Implicit Learning: Connectionist Models of Sequence Processing , 1993 .

[37]  M. A. Stadler,et al.  Role of attention in implicit learning. , 1995 .

[38]  D R Shanks,et al.  Evaluating the relationship between explicit and implicit knowledge in a sequential reaction time task. , 1999, Journal of experimental psychology. Learning, memory, and cognition.

[39]  Scott T. Grafton,et al.  Functional Mapping of Sequence Learning in Normal Humans , 1995, Journal of Cognitive Neuroscience.

[40]  Shanks,et al.  Implicit knowledge in sequential learning tasks , 1998 .

[41]  Michael A. Stadler,et al.  Handbook of implicit learning , 1998 .

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