Literature DB >> 11414006

Simultaneous learning of different regularities in sequence learning tasks: limits and characteristics.

A Buchner1, M C Steffens.   

Abstract

Two experiments are reported which were designed to investigate the generality and the power of the mechanisms underlying sequence learning. In both experiments, participants reacted to systematic sequences of tones. They were informed that there was a tone systematicity. Participants were not told that the interval between a response to a tone and the onset of the subsequent tone (response-signal interval, RSI) also varied according to a fixed regularity. Experiment 1 showed that the unattended RSIs were learned when they were uniquely related to the tone sequence, but not when the relation was ambiguous. Experiment 2 showed that, on the basis of the traditional reaction time performance measure, participants who learned the RSIs by attending to their systematicity could not be distinguished from those in an incidental learning condition in which the RSI systematicity was unattended. However, a model-based analysis of the processes contributing to judgements about the event sequences suggested that the two groups had acquired qualitatively different knowledge.

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Year:  2001        PMID: 11414006     DOI: 10.1007/s004260000052

Source DB:  PubMed          Journal:  Psychol Res        ISSN: 0340-0727


  11 in total

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Journal:  Exp Brain Res       Date:  2013-06-01       Impact factor: 1.972

7.  Incidental learning of temporal structures conforming to a metrical framework.

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Journal:  Front Psychol       Date:  2012-08-23

8.  Early behavioural facilitation by temporal expectations in complex visual-motor sequences.

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Journal:  J Physiol Paris       Date:  2017-03-18

9.  Generalisation of new sequence knowledge depends on response modality.

Authors:  Clive R Rosenthal; Tammy W C Ng; Christopher Kennard
Journal:  PLoS One       Date:  2013-02-05       Impact factor: 3.240

10.  A sequence identification measurement model to investigate the implicit learning of metrical temporal patterns.

Authors:  Benjamin G Schultz; Catherine J Stevens; Peter E Keller; Barbara Tillmann
Journal:  PLoS One       Date:  2013-09-25       Impact factor: 3.240

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