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Dissociable neural systems of sequence learning
Although current theories all point to distinct neural systems for sequence learning, no consensus has been reached on which factors crucially define this distinction. Dissociable judgment-linked versus motor-linked and implicit versus explicit neural systems have been proposed. This paper reviews t...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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University of Finance and Management in Warsaw
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3367868/ https://www.ncbi.nlm.nih.gov/pubmed/22679463 http://dx.doi.org/10.2478/v10053-008-0105-1 |
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author | Gheysen, Freja Fias, Wim |
author_facet | Gheysen, Freja Fias, Wim |
author_sort | Gheysen, Freja |
collection | PubMed |
description | Although current theories all point to distinct neural systems for sequence learning, no consensus has been reached on which factors crucially define this distinction. Dissociable judgment-linked versus motor-linked and implicit versus explicit neural systems have been proposed. This paper reviews these two distinctions, yet concludes that these traditional dichotomies prove insufficient to account for all data on sequence learning and its neural organization. Instead, a broader theoretical framework is necessary providing a more continuous means of dissociating sequence learning systems. We argue that a more recent theory, dissociating multidimensional versus unidimensional neural systems, might provide such framework, and we discuss this theory in relation to more general principles of associative learning and recent imaging findings. |
format | Online Article Text |
id | pubmed-3367868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | University of Finance and Management in Warsaw |
record_format | MEDLINE/PubMed |
spelling | pubmed-33678682012-06-07 Dissociable neural systems of sequence learning Gheysen, Freja Fias, Wim Adv Cogn Psychol Research Article Although current theories all point to distinct neural systems for sequence learning, no consensus has been reached on which factors crucially define this distinction. Dissociable judgment-linked versus motor-linked and implicit versus explicit neural systems have been proposed. This paper reviews these two distinctions, yet concludes that these traditional dichotomies prove insufficient to account for all data on sequence learning and its neural organization. Instead, a broader theoretical framework is necessary providing a more continuous means of dissociating sequence learning systems. We argue that a more recent theory, dissociating multidimensional versus unidimensional neural systems, might provide such framework, and we discuss this theory in relation to more general principles of associative learning and recent imaging findings. University of Finance and Management in Warsaw 2012-05-21 /pmc/articles/PMC3367868/ /pubmed/22679463 http://dx.doi.org/10.2478/v10053-008-0105-1 Text en Copyright: © 2012 University of Finance and Management in Warsaw http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Gheysen, Freja Fias, Wim Dissociable neural systems of sequence learning |
title | Dissociable neural systems of sequence learning |
title_full | Dissociable neural systems of sequence learning |
title_fullStr | Dissociable neural systems of sequence learning |
title_full_unstemmed | Dissociable neural systems of sequence learning |
title_short | Dissociable neural systems of sequence learning |
title_sort | dissociable neural systems of sequence learning |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3367868/ https://www.ncbi.nlm.nih.gov/pubmed/22679463 http://dx.doi.org/10.2478/v10053-008-0105-1 |
work_keys_str_mv | AT gheysenfreja dissociableneuralsystemsofsequencelearning AT fiaswim dissociableneuralsystemsofsequencelearning |