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  The role of alpha-rhythm states in perceptual learning: Insights from experiments and computational models

Sigala, R., Haufe, S., Roy, D., Dinse, H. R., & Ritter, P. (2014). The role of alpha-rhythm states in perceptual learning: Insights from experiments and computational models. Frontiers in Computational Neuroscience, 8: 36. doi:10.3389/fncom.2014.00036.

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 Creators:
Sigala, R., Author
Haufe, S., Author
Roy, D., Author
Dinse, H. R., Author
Ritter, Petra1, Author           
Affiliations:
1Minerva Research Group Brain Modes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_751546              

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Free keywords: Alpha rhythm; Oscillations; Attention; Memory; Learning; Cognition; Large-scale modeling
 Abstract: During the past two decades growing evidence indicates that brain oscillations in the alpha band (~10 Hz) not only reflect an “idle” state of cortical activity, but also take a more active role in the generation of complex cognitive functions. A recent study shows that more than 60% of the observed inter-subject variability in perceptual learning can be ascribed to ongoing alpha activity. This evidence indicates a significant role of alpha oscillations for perceptual learning and hence motivates to explore the potential underlying mechanisms. Hence, it is the purpose of this review to highlight existent evidence that ascribes intrinsic alpha oscillations a role in shaping our ability to learn. In the review, we disentangle the alpha rhythm into different neural signatures that control information processing within individual functional building blocks of perceptual learning. We further highlight computational studies that shed light on potential mechanisms regarding how alpha oscillations may modulate information transfer and connectivity changes relevant for learning. To enable testing of those model based hypotheses, we emphasize the need for multidisciplinary approaches combining assessment of behavior and multi-scale neuronal activity, active modulation of ongoing brain states and computational modeling to reveal the mathematical principles of the complex neuronal interactions. In particular we highlight the relevance of multi-scale modeling frameworks such as the one currently being developed by “The Virtual Brain” project.

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Language(s): eng - English
 Dates: 2013-01-142014-03-112014-04-04
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fncom.2014.00036
PMID: 24772077
Other: eCollection 2014
 Degree: -

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Title: Frontiers in Computational Neuroscience
  Abbreviation : Front Comput Neurosci
Source Genre: Journal
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Affiliations:
Publ. Info: Lausanne : Frontiers Research Foundation
Pages: - Volume / Issue: 8 Sequence Number: 36 Start / End Page: - Identifier: Other: 1662-5188
CoNE: https://pure.mpg.de/cone/journals/resource/1662-5188