Error and Deviance Processing in Implicit and Explicit Sequence Learning

In this experiment, we examined the extent to which error-driven learning may operate under implicit learning conditions. We compared error monitoring in a sequence learning task in which stimuli consisted of regular, irregular, or random sequences. Subjects were either informed (explicit condition) or not informed (implicit condition) about the existence of the sequence. For both conditions, reaction times were faster to stimuli from regular sequences than from random sequences, thus supporting the view that sequence learning occurs irrespective of learning condition. Response-locked event-related potentials (ERPs) showed a pronounced ERN/Ne, thereby signaling the detection of committed errors. Deviant stimuli from irregular sequences elicited an N2b component that developed in the course of the experiment, albeit faster for explicit than implicit learners. This observation supports the view that deviant events acquire the status of perceived errors during explicit and implicit learning, and thus, an N2b is generated resembling the ERN/Ne to committed errors. While performing the task, expectations about upcoming events are generated, compared to the actual events, and evaluated on the dimension better or worse than expected. The accuracy of this process improves with learning, as shown by a gradual increase in N2b amplitude as a function of learning. Additionally, a P3b, which is thought to mirror conscious processing of deviant stimuli and is related to updating of working memory representations, was found for explicit learners only.

[1]  D. V. Cramon,et al.  Subprocesses of Performance Monitoring: A Dissociation of Error Processing and Response Competition Revealed by Event-Related fMRI and ERPs , 2001, NeuroImage.

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

[3]  Arthur F. Kramer,et al.  fMRI Studies of Stroop Tasks Reveal Unique Roles of Anterior and Posterior Brain Systems in Attentional Selection , 2000, Journal of Cognitive Neuroscience.

[4]  D. Meyer,et al.  A Neural System for Error Detection and Compensation , 1993 .

[5]  J. G. Snodgrass,et al.  Pragmatics of measuring recognition memory: applications to dementia and amnesia. , 1988, Journal of experimental psychology. General.

[6]  Jonathan D. Cohen,et al.  The neural basis of error detection: conflict monitoring and the error-related negativity. , 2004, Psychological review.

[7]  Martin Eimer,et al.  Chunking processes in the learning of event sequences: Electrophysiological indicators , 2000, Memory & cognition.

[8]  M Eimer,et al.  Explicit and implicit learning of event sequences: evidence from event-related brain potentials. , 1996, Journal of experimental psychology. Learning, memory, and cognition.

[9]  E. Donchin,et al.  Is the P300 component a manifestation of context updating? , 1988, Behavioral and Brain Sciences.

[10]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[11]  B. Kopp,et al.  Brain mechanisms of selective learning: event-related potentials provide evidence for error-driven learning in humans , 2000, Biological Psychology.

[12]  M. Botvinick,et al.  Conflict monitoring and cognitive control. , 2001, Psychological review.

[13]  P Ullsperger,et al.  The P300 to novel and target events: a spatio–temporal dipole model analysis , 1995, Neuroreport.

[14]  Dianne C. Berry Implicit learning: twenty-five years on. A tutorial , 1994 .

[15]  Peter A. Frensch,et al.  One concept, multiple meanings: On how to define the concept of implicit learning. , 1998 .

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

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

[18]  M. Coles,et al.  "Where did I go wrong?" A psychophysiological analysis of error detection. , 1995, Journal of experimental psychology. Human perception and performance.

[19]  L L Jacoby,et al.  Invariance in automatic influences of memory: toward a user's guide for the process-dissociation procedure. , 1998, Journal of experimental psychology. Learning, memory, and cognition.

[20]  Carol A. Seger,et al.  Implicit learning. , 1994, Psychological bulletin.

[21]  C. C. Wood,et al.  Scalp distributions of event-related potentials: an ambiguity associated with analysis of variance models. , 1985, Electroencephalography and clinical neurophysiology.

[22]  Kara D. Federmeier,et al.  A Rose by Any Other Name: Long-Term Memory Structure and Sentence Processing , 1999 .

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

[24]  Clay B. Holroyd,et al.  The neural basis of human error processing: reinforcement learning, dopamine, and the error-related negativity. , 2002, Psychological review.

[25]  F Rösler,et al.  Implicit and explicit learning of event sequences: evidence for distinct coding of perceptual and motor representations. , 2000, Acta psychologica.

[26]  Erich Schröger,et al.  Human Visual System Automatically Encodes Sequential Regularities of Discrete Events , 2010, Journal of Cognitive Neuroscience.

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

[28]  N. Yeung,et al.  On the ERN and the significance of errors. , 2005, Psychophysiology.

[29]  A. Turken,et al.  Response selection in the human anterior cingulate cortex , 1999, Nature Neuroscience.

[30]  K. R. Ridderinkhof,et al.  Electrophysiological correlates of anterior cingulate function in a go/no-go task: Effects of response conflict and trial type frequency , 2003, Cognitive, affective & behavioral neuroscience.

[31]  Thomas F Münte,et al.  Human error monitoring during implicit and explicit learning of a sensorimotor sequence , 2003, Neuroscience Research.

[32]  Kara D. Federmeier,et al.  Electrophysiology reveals semantic memory use in language comprehension , 2000, Trends in Cognitive Sciences.

[33]  K. R. Ridderinkhof,et al.  Error-related brain potentials are differentially related to awareness of response errors: evidence from an antisaccade task. , 2001, Psychophysiology.

[34]  Stefan Koelsch,et al.  Processing Expectancy Violations during Music Performance and Perception: An ERP Study , 2010, Journal of Cognitive Neuroscience.

[35]  W. Schultz Getting Formal with Dopamine and Reward , 2002, Neuron.

[36]  Thomas F Münte,et al.  Differences in incidental and intentional learning of sensorimotor sequences as revealed by event-related brain potentials. , 2003, Brain research. Cognitive brain research.

[37]  Clay B. Holroyd,et al.  Why is there an ERN/Ne on correct trials? Response representations, stimulus-related components, and the theory of error-processing , 2001, Biological Psychology.

[38]  Axel Mecklinger,et al.  ERP correlates of true and false recognition after different retention delays: stimulus- and response-related processes. , 2003, Psychophysiology.

[39]  Clay B. Holroyd,et al.  A note on the oddball N200 and the feedback ERN , 2004 .

[40]  C. Braun,et al.  Event-Related Brain Potentials Following Incorrect Feedback in a Time-Estimation Task: Evidence for a Generic Neural System for Error Detection , 1997, Journal of Cognitive Neuroscience.

[41]  T. Gunter,et al.  Let's face the music: a behavioral and electrophysiological exploration of score reading. , 2003, Psychophysiology.