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  Network mechanisms underlying the role of oscillations in cognitive tasks

Schmidt, H., Avitabile, D., Montbrió, E., & Roxin, A. (2018). Network mechanisms underlying the role of oscillations in cognitive tasks. PLoS Computational Biology, 14(9): e1006430. doi:10.1371/journal.pcbi.1006430.

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 Creators:
Schmidt, Helmut1, 2, 3, Author              
Avitabile, Daniele 4, 5, Author
Montbrió, Ernest 6, Author
Roxin, Alex 2, 3, Author
Affiliations:
1Methods and Development Group MEG and EEG - Cortical Networks and Cognitive Functions, MPI for Human Cognitive and Brain Sciences, Max Planck Society, Leipzig, DE, ou_2205650              
2Centre de Recerca Matemàtica, Barcelona, Spain, ou_persistent22              
3Barcelona Graduate School of Mathematics, Spain, ou_persistent22              
4School of Mathematical Sciences, University of Nottingham, United Kingdom, ou_persistent22              
5MathNeuro Team, Institut national de recherche en informatique et en automatique (INRIA), Sophia Antipolis, France, ou_persistent22              
6Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Spain, ou_persistent22              

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Free keywords: Human; Human experiment; Nerve cell; Oscillation; Spike; Working memory
 Abstract: Oscillatory activity robustly correlates with task demands during many cognitive tasks. However, not only are the network mechanisms underlying the generation of these rhythms poorly understood, but it is also still unknown to what extent they may play a functional role, as opposed to being a mere epiphenomenon. Here we study the mechanisms underlying the influence of oscillatory drive on network dynamics related to cognitive processing in simple working memory (WM), and memory recall tasks. Specifically, we investigate how the frequency of oscillatory input interacts with the intrinsic dynamics in networks of recurrently coupled spiking neurons to cause changes of state: the neuronal correlates of the corresponding cognitive process. We find that slow oscillations, in the delta and theta band, are effective in activating network states associated with memory recall. On the other hand, faster oscillations, in the beta range, can serve to clear memory states by resonantly driving transient bouts of spike synchrony which destabilize the activity. We leverage a recently derived set of exact mean-field equations for networks of quadratic integrate-and-fire neurons to systematically study the bifurcation structure in the periodically forced spiking network. Interestingly, we find that the oscillatory signals which are most effective in allowing flexible switching between network states are not smooth, pure sinusoids, but rather burst-like, with a sharp onset. We show that such periodic bursts themselves readily arise spontaneously in networks of excitatory and inhibitory neurons, and that the burst frequency can be tuned via changes in tonic drive. Finally, we show that oscillations in the gamma range can actually stabilize WM states which otherwise would not persist.

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Language(s): eng - English
 Dates: 2018-02-062018-08-132018-09-06
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1006430
PMID: 30188889
PMC: PMC6143269
Other: eCollection 2018
 Degree: -

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Project name : -
Grant ID : MDM- 2014-0445 ; MTM2015-71509-C2-1-R
Funding program : María de Maeztu Programme for Units of Excellence
Funding organization : Spanish Ministry of Economy and Competitiveness
Project name : Complex Oscillatory Systems: Modeling and Analysis / COSMOS
Grant ID : 642563
Funding program : Horizon 2020
Funding organization : European Commission (EC)
Project name : Spanish National Project Complexity of Brain States
Grant ID : PSI2016-75688-P
Funding program : -
Funding organization : Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF)
Project name : -
Grant ID : PCIN-2015-127 ; BFU2012-33413
Funding program : -
Funding organization : Spanish Ministry of Economy and Competitiveness
Project name : -
Grant ID : -
Funding program : CERCA Programme
Funding organization : Generalitat de Catalunya

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Title: PLoS Computational Biology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 14 (9) Sequence Number: e1006430 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1