Research article summary (published 29 Apr 2008):

gSRT-Soft: a generic software application and some methodological guidelines to investigate implicit learning through visual-motor sequential tasks.

Full Abstract

Serial reaction time tasks and, more generally, the visual-motor sequential paradigms are increasingly popular tools in a variety of research domains, from studies on implicit learning in laboratory contexts to the assessment of residual learning capabilities of patients in clinical settings. A consequence of this success, however, is the increased variability in paradigms and the difficulty inherent in respecting the methodological principles that two decades of experimental investigations have made more and more stringent. The purpose of the present article is to address those problems. We present a user-friendly application that simplifies running classical experiments, but is flexible enough to permit a broad range of nonstandard manipulations for more specific objectives. Basic methodological guidelines are also provided, as are suggestions for using the software to explore unconventional directions of research. The most recent version of gSRT-Soft may be obtained for free by contacting the authors.

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Author information

Author/s: Chambaron, Stéphanie (S); Ginhac, Dominique (D); Perruchet, Pierre (P);

Affiliation: Cognitive Science Research Unit, Université Libre de Bruxelles, Brussels, Belgium. schambar(-atsign-)ulb.ac.be

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Behavior research methods (Behav Res Methods), published in United States. (Language: eng)

Reference: 2008-May; vol 40 (issue 2) : pp 493-502

Dates: Created 2008/06/04; Completed 2008/07/30;

PMID: 18522060, status: MEDLINE (last retrieval date: 11/6/2008)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Behavioral Sciences - methods Humans Motor Skills Research Design

Research Design Serial Learning Software Task Performance and Analysis

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