Cross-frequency transfer in a stochastically driven mesoscopic neuronal model

The brain is known to operate in multiple coexisting frequency bands. Increasing experimental evidence suggests that interactions between those distinct bands play a crucial role in brain processes, but the dynamical mechanisms underlying this cross-frequency coupling are still under investigation....

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Autores: Jedynak, Maciej, Pons, Antonio J., García Ojalvo, Jordi
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/25650
Acceso en línea:http://hdl.handle.net/10230/25650
http://dx.doi.org/10.3389/fncom.2015.00014
Access Level:acceso abierto
Palabra clave:Neurones
Cognició
Jansen-Rit model
Ornstein-Uhlenbeck noise
Cross-frequency coupling
Driven oscillators
Mesoscopic brain dynamics
Neural mass model
Neuronal oscillations
Stochastic
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spelling Cross-frequency transfer in a stochastically driven mesoscopic neuronal modelJedynak, MaciejPons, Antonio J.García Ojalvo, JordiNeuronesCognicióJansen-Rit modelOrnstein-Uhlenbeck noiseCross-frequency couplingDriven oscillatorsMesoscopic brain dynamicsNeural mass modelNeuronal oscillationsStochasticThe brain is known to operate in multiple coexisting frequency bands. Increasing experimental evidence suggests that interactions between those distinct bands play a crucial role in brain processes, but the dynamical mechanisms underlying this cross-frequency coupling are still under investigation. Two approaches have been proposed to address this issue. In the first one distinct nonlinear oscillators representing the brain rhythms involved are coupled actively (bidirectionally), whereas in the second one the oscillators are coupled unidirectionally and thus the driving between them is passive. Here we elaborate the latter approach by implementing a stochastically driven network of coupled neural mass models that operate in the alpha range. This model exhibits a broadband power spectrum with 1/f(b) form, similar to those observed experimentally. Our results show that such a model is able to reproduce recent experimental observations on the effect of slow rocking on the alpha activity associated with sleep. This suggests that passive driving can account for cross-frequency transfer in the brain, as a result of the complex nonlinear dynamics of its underlying oscillators.This work was supported by the European Commission through the FP7 Marie Curie Initial Training Network 289146 (NETT: Neural Engineering Transformative Technologies), and the Ministerio de Economia y Competividad (Spain, project FIS2012-37655). JGO acknowledges support from the ICREA Academia programme.Frontiers201620162015info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/25650http://dx.doi.org/10.3389/fncom.2015.00014reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésFrontiers in computational neuroscience. 2015;9:14info:eu-repo/grantAgreement/ES/3PN/FIS2012-37655© 2015 Jedynak, Pons and Garcia-Ojalvo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or 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.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/256502026-06-12T07:21:37Z
dc.title.none.fl_str_mv Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
title Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
spellingShingle Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
Jedynak, Maciej
Neurones
Cognició
Jansen-Rit model
Ornstein-Uhlenbeck noise
Cross-frequency coupling
Driven oscillators
Mesoscopic brain dynamics
Neural mass model
Neuronal oscillations
Stochastic
title_short Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
title_full Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
title_fullStr Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
title_full_unstemmed Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
title_sort Cross-frequency transfer in a stochastically driven mesoscopic neuronal model
dc.creator.none.fl_str_mv Jedynak, Maciej
Pons, Antonio J.
García Ojalvo, Jordi
author Jedynak, Maciej
author_facet Jedynak, Maciej
Pons, Antonio J.
García Ojalvo, Jordi
author_role author
author2 Pons, Antonio J.
García Ojalvo, Jordi
author2_role author
author
dc.subject.none.fl_str_mv Neurones
Cognició
Jansen-Rit model
Ornstein-Uhlenbeck noise
Cross-frequency coupling
Driven oscillators
Mesoscopic brain dynamics
Neural mass model
Neuronal oscillations
Stochastic
topic Neurones
Cognició
Jansen-Rit model
Ornstein-Uhlenbeck noise
Cross-frequency coupling
Driven oscillators
Mesoscopic brain dynamics
Neural mass model
Neuronal oscillations
Stochastic
description The brain is known to operate in multiple coexisting frequency bands. Increasing experimental evidence suggests that interactions between those distinct bands play a crucial role in brain processes, but the dynamical mechanisms underlying this cross-frequency coupling are still under investigation. Two approaches have been proposed to address this issue. In the first one distinct nonlinear oscillators representing the brain rhythms involved are coupled actively (bidirectionally), whereas in the second one the oscillators are coupled unidirectionally and thus the driving between them is passive. Here we elaborate the latter approach by implementing a stochastically driven network of coupled neural mass models that operate in the alpha range. This model exhibits a broadband power spectrum with 1/f(b) form, similar to those observed experimentally. Our results show that such a model is able to reproduce recent experimental observations on the effect of slow rocking on the alpha activity associated with sleep. This suggests that passive driving can account for cross-frequency transfer in the brain, as a result of the complex nonlinear dynamics of its underlying oscillators.
publishDate 2015
dc.date.none.fl_str_mv 2015
2016
2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/25650
http://dx.doi.org/10.3389/fncom.2015.00014
url http://hdl.handle.net/10230/25650
http://dx.doi.org/10.3389/fncom.2015.00014
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Frontiers in computational neuroscience. 2015;9:14
info:eu-repo/grantAgreement/ES/3PN/FIS2012-37655
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Frontiers
publisher.none.fl_str_mv Frontiers
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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