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Fast Sequences of Non-spatial State Representations in Humans

Fast internally generated sequences of neural representations are suggested to support learning and online planning. However, these sequences have only been studied in the context of spatial tasks and never in humans. Here, we recorded magnetoencephalography (MEG) while human subjects performed a no...

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Detalles Bibliográficos
Autores principales: Kurth-Nelson, Zeb, Economides, Marcos, Dolan, Raymond J., Dayan, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cell Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942698/
https://www.ncbi.nlm.nih.gov/pubmed/27321922
http://dx.doi.org/10.1016/j.neuron.2016.05.028
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author Kurth-Nelson, Zeb
Economides, Marcos
Dolan, Raymond J.
Dayan, Peter
author_facet Kurth-Nelson, Zeb
Economides, Marcos
Dolan, Raymond J.
Dayan, Peter
author_sort Kurth-Nelson, Zeb
collection PubMed
description Fast internally generated sequences of neural representations are suggested to support learning and online planning. However, these sequences have only been studied in the context of spatial tasks and never in humans. Here, we recorded magnetoencephalography (MEG) while human subjects performed a novel non-spatial reasoning task. The task required selecting paths through a set of six visual objects. We trained pattern classifiers on the MEG activity elicited by direct presentation of the visual objects alone and tested these classifiers on activity recorded during periods when no object was presented. During these object-free periods, the brain spontaneously visited representations of approximately four objects in fast sequences lasting on the order of 120 ms. These sequences followed backward trajectories along the permissible paths in the task. Thus, spontaneous fast sequential representation of states can be measured non-invasively in humans, and these sequences may be a fundamental feature of neural computation across tasks.
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spelling pubmed-49426982016-07-18 Fast Sequences of Non-spatial State Representations in Humans Kurth-Nelson, Zeb Economides, Marcos Dolan, Raymond J. Dayan, Peter Neuron Article Fast internally generated sequences of neural representations are suggested to support learning and online planning. However, these sequences have only been studied in the context of spatial tasks and never in humans. Here, we recorded magnetoencephalography (MEG) while human subjects performed a novel non-spatial reasoning task. The task required selecting paths through a set of six visual objects. We trained pattern classifiers on the MEG activity elicited by direct presentation of the visual objects alone and tested these classifiers on activity recorded during periods when no object was presented. During these object-free periods, the brain spontaneously visited representations of approximately four objects in fast sequences lasting on the order of 120 ms. These sequences followed backward trajectories along the permissible paths in the task. Thus, spontaneous fast sequential representation of states can be measured non-invasively in humans, and these sequences may be a fundamental feature of neural computation across tasks. Cell Press 2016-07-06 /pmc/articles/PMC4942698/ /pubmed/27321922 http://dx.doi.org/10.1016/j.neuron.2016.05.028 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kurth-Nelson, Zeb
Economides, Marcos
Dolan, Raymond J.
Dayan, Peter
Fast Sequences of Non-spatial State Representations in Humans
title Fast Sequences of Non-spatial State Representations in Humans
title_full Fast Sequences of Non-spatial State Representations in Humans
title_fullStr Fast Sequences of Non-spatial State Representations in Humans
title_full_unstemmed Fast Sequences of Non-spatial State Representations in Humans
title_short Fast Sequences of Non-spatial State Representations in Humans
title_sort fast sequences of non-spatial state representations in humans
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4942698/
https://www.ncbi.nlm.nih.gov/pubmed/27321922
http://dx.doi.org/10.1016/j.neuron.2016.05.028
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