Modelling on the very large-scale connectome

In this review, we discuss critical dynamics of simple nonequilibrium models on large connectomes, obtained by diffusion MRI, representing the white matter of the human brain. In the first chapter, we overview graph theoretical and topological analysis of these networks, pointing out that universali...

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Autores: Ódor, Géza, Gastner, Michael T, Kelling, Jeffrey, Deco, Gustavo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/56003
Acceso en línea:http://hdl.handle.net/10230/56003
http://dx.doi.org/10.1088/2632-072X/ac266c
Access Level:acceso abierto
Palabra clave:connectome
brain
criticality
dynamics
Griffiths phase
Kuramoto
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spelling Modelling on the very large-scale connectomeÓdor, GézaGastner, Michael TKelling, JeffreyDeco, GustavoconnectomebraincriticalitydynamicsGriffiths phaseKuramotoIn this review, we discuss critical dynamics of simple nonequilibrium models on large connectomes, obtained by diffusion MRI, representing the white matter of the human brain. In the first chapter, we overview graph theoretical and topological analysis of these networks, pointing out that universality allows selecting a representative network, the KKI-18, which has been used for dynamical simulation. The critical and sub-critical behaviour of simple, two- or three-state threshold models is discussed with special emphasis on rare-region effects leading to robust Griffiths phases (GP). Numerical results of synchronization phenomena, studied by the Kuramoto model, are also shown, leading to a continuous analog of the GP, termed frustrated synchronization. The models presented here exhibit dynamical scaling behaviour with exponents in agreement with brain experimental data if local homeostasis is provided.GÓ is supported by the National Research, Development and Innovation Office NKFIH under Grant No. K128989 and the Project HPC-EUROPA3 (INFRAIA-2016-1-730897) from the EC Research Innovation Action under the H2020 Programme. MTG was supported by the Singapore Ministry of Education (MOE) and Yale-NUS College (through Grant No. R-607-263-043-121). GD is supported by Spanish national research projects (ref. PID2019-105772GB-I00 MCIU AEI) funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI); HBP SGA3 Human Brain Project Specific Grant Agreement 3 (Grant Agreement No. 945539), funded by the EU H2020 FET Flagship Programme; SGR Research Support Group support (ref. 2017 SGR 1545), funded by the Catalan Agency for Management of University and Research Grants (AGAUR); Neurotwin Digital twins for model-driven non-invasive electrical brain stimulation (Grant Agreement ID: 101017716) funded by the EU H2020 FET Proactive programme; euSNN European School of Network Neuroscience (Grant Agreement ID: 860563) funded by the EU H2020MSCA-ITN Innovative Training Networks; CECH The Emerging Human Brain Cluster (Id. 001-P-001682) within the framework of the European Research Development Fund Operational Program of Catalonia 2014-2020; Brain-Connects: Brain Connectivity during Stroke Recovery and Rehabilitation (id. 201725.33) funded by the Fundacio La Marato TV3; Corticity, FLAGERA JTC 2017, (ref. PCI2018-092891) funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI). JK is supported by the Helmholtz Initiative and Networking Funds via the W2/W3 Programme, Project Number W2/W3-026.IOP Publishing Ltd.202320232021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/56003http://dx.doi.org/10.1088/2632-072X/ac266creponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésJournal of Physics: Complexity. 2021;2:045002.info:eu-repo/grantAgreement/EC/H2020/945539info:eu-repo/grantAgreement/EC/H2020/730897info:eu-repo/grantAgreement/EC/H2020/101017716info:eu-repo/grantAgreement/EC/H2020/860563info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00info:eu-repo/grantAgreement/ES/2PE/PCI2018-092891© 2021 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/560032026-06-12T07:21:37Z
dc.title.none.fl_str_mv Modelling on the very large-scale connectome
title Modelling on the very large-scale connectome
spellingShingle Modelling on the very large-scale connectome
Ódor, Géza
connectome
brain
criticality
dynamics
Griffiths phase
Kuramoto
title_short Modelling on the very large-scale connectome
title_full Modelling on the very large-scale connectome
title_fullStr Modelling on the very large-scale connectome
title_full_unstemmed Modelling on the very large-scale connectome
title_sort Modelling on the very large-scale connectome
dc.creator.none.fl_str_mv Ódor, Géza
Gastner, Michael T
Kelling, Jeffrey
Deco, Gustavo
author Ódor, Géza
author_facet Ódor, Géza
Gastner, Michael T
Kelling, Jeffrey
Deco, Gustavo
author_role author
author2 Gastner, Michael T
Kelling, Jeffrey
Deco, Gustavo
author2_role author
author
author
dc.subject.none.fl_str_mv connectome
brain
criticality
dynamics
Griffiths phase
Kuramoto
topic connectome
brain
criticality
dynamics
Griffiths phase
Kuramoto
description In this review, we discuss critical dynamics of simple nonequilibrium models on large connectomes, obtained by diffusion MRI, representing the white matter of the human brain. In the first chapter, we overview graph theoretical and topological analysis of these networks, pointing out that universality allows selecting a representative network, the KKI-18, which has been used for dynamical simulation. The critical and sub-critical behaviour of simple, two- or three-state threshold models is discussed with special emphasis on rare-region effects leading to robust Griffiths phases (GP). Numerical results of synchronization phenomena, studied by the Kuramoto model, are also shown, leading to a continuous analog of the GP, termed frustrated synchronization. The models presented here exhibit dynamical scaling behaviour with exponents in agreement with brain experimental data if local homeostasis is provided.
publishDate 2021
dc.date.none.fl_str_mv 2021
2023
2023
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/10230/56003
http://dx.doi.org/10.1088/2632-072X/ac266c
url http://hdl.handle.net/10230/56003
http://dx.doi.org/10.1088/2632-072X/ac266c
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Journal of Physics: Complexity. 2021;2:045002.
info:eu-repo/grantAgreement/EC/H2020/945539
info:eu-repo/grantAgreement/EC/H2020/730897
info:eu-repo/grantAgreement/EC/H2020/101017716
info:eu-repo/grantAgreement/EC/H2020/860563
info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
info:eu-repo/grantAgreement/ES/2PE/PCI2018-092891
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://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 IOP Publishing Ltd.
publisher.none.fl_str_mv IOP Publishing Ltd.
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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