dc.contributor.author
Ritter, Petra
dc.contributor.author
Born, Jan
dc.contributor.author
Brecht, Michael
dc.contributor.author
Dinse, Hubert R.
dc.contributor.author
Heinemann, Uwe
dc.contributor.author
Pleger, Burkhard
dc.contributor.author
Schmitz, Dietmar
dc.contributor.author
Schreiber, Susanne
dc.contributor.author
Villringer, Arno
dc.contributor.author
Kempter, Richard
dc.date.accessioned
2018-06-08T04:19:03Z
dc.date.available
2015-05-11T10:33:42.744Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/17039
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-21219
dc.description.abstract
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.
en
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit
dc.title
State-dependencies of learning across brain scales
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
Front. Comput. Neurosci. - 9 (2015), Artikel Nr. 1
dcterms.bibliographicCitation.doi
10.3389/fncom.2015.00001
dcterms.bibliographicCitation.url
http://dx.doi.org/10.3389/fncom.2015.00001
refubium.affiliation
Charité - Universitätsmedizin Berlin
de
refubium.mycore.fudocsId
FUDOCS_document_000000022398
refubium.note.author
Der Artikel wurde in einer Open-Access-Zeitschrift publiziert.
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000004890
dcterms.accessRights.openaire
open access