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State-dependencies of learning across brain scales

Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequenc...

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Autores principales: Ritter, Petra, Born, Jan, Brecht, Michael, Dinse, Hubert R., Heinemann, Uwe, Pleger, Burkhard, Schmitz, Dietmar, Schreiber, Susanne, Villringer, Arno, Kempter, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4341560/
https://www.ncbi.nlm.nih.gov/pubmed/25767445
http://dx.doi.org/10.3389/fncom.2015.00001
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author Ritter, Petra
Born, Jan
Brecht, Michael
Dinse, Hubert R.
Heinemann, Uwe
Pleger, Burkhard
Schmitz, Dietmar
Schreiber, Susanne
Villringer, Arno
Kempter, Richard
author_facet Ritter, Petra
Born, Jan
Brecht, Michael
Dinse, Hubert R.
Heinemann, Uwe
Pleger, Burkhard
Schmitz, Dietmar
Schreiber, Susanne
Villringer, Arno
Kempter, Richard
author_sort Ritter, Petra
collection PubMed
description Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.
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spelling pubmed-43415602015-03-12 State-dependencies of learning across brain scales Ritter, Petra Born, Jan Brecht, Michael Dinse, Hubert R. Heinemann, Uwe Pleger, Burkhard Schmitz, Dietmar Schreiber, Susanne Villringer, Arno Kempter, Richard Front Comput Neurosci Neuroscience Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly. Frontiers Media S.A. 2015-02-26 /pmc/articles/PMC4341560/ /pubmed/25767445 http://dx.doi.org/10.3389/fncom.2015.00001 Text en Copyright © 2015 Ritter, Born, Brecht, Dinse, Heinemann, Pleger, Schmitz, Schreiber, Villringer and Kempter. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Ritter, Petra
Born, Jan
Brecht, Michael
Dinse, Hubert R.
Heinemann, Uwe
Pleger, Burkhard
Schmitz, Dietmar
Schreiber, Susanne
Villringer, Arno
Kempter, Richard
State-dependencies of learning across brain scales
title State-dependencies of learning across brain scales
title_full State-dependencies of learning across brain scales
title_fullStr State-dependencies of learning across brain scales
title_full_unstemmed State-dependencies of learning across brain scales
title_short State-dependencies of learning across brain scales
title_sort state-dependencies of learning across brain scales
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4341560/
https://www.ncbi.nlm.nih.gov/pubmed/25767445
http://dx.doi.org/10.3389/fncom.2015.00001
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