Ghost attractors in spontaneous brain activity: recurrent excursions into functionally-relevant BOLD phase-locking states

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• dc.contributor.author Vohryzek, Jakub
• dc.contributor.author Deco, Gustavo
• dc.contributor.author Cessac, Bruno
• dc.contributor.author Kringelbach, Morten L.
• dc.contributor.author Cabral, Joana
• dc.date.accessioned 2020-07-15T10:01:38Z
• dc.date.available 2020-07-15T10:01:38Z
• dc.date.issued 2020
• dc.description.abstract Functionally relevant network patterns form transiently in brain activity during rest, where a given subset of brain areas exhibits temporally synchronized BOLD signals. To adequately assess the biophysical mechanisms governing intrinsic brain activity, a detailed characterization of the dynamical features of functional networks is needed from the experimental side to constrain theoretical models. In this work, we use an open-source fMRI dataset from 100 healthy participants from the Human Connectome Project and analyze whole-brain activity using Leading Eigenvector Dynamics Analysis (LEiDA), which serves to characterize brain activity at each time point by its whole-brain BOLD phase-locking pattern. Clustering these BOLD phase-locking patterns into a set of k states, we demonstrate that the cluster centroids closely overlap with reference functional subsystems. Borrowing tools from dynamical systems theory, we characterize spontaneous brain activity in the form of trajectories within the state space, calculating the Fractional Occupancy and the Dwell Times of each state, as well as the Transition Probabilities between states. Finally, we demonstrate that within-subject reliability is maximized when including the high frequency components of the BOLD signal (>0.1 Hz), indicating the existence of individual fingerprints in dynamical patterns evolving at least as fast as the temporal resolution of acquisition (here TR = 0.72 s). Our results reinforce the mechanistic scenario that resting-state networks are the expression of erratic excursions from a baseline synchronous steady state into weakly-stable partially-synchronized states – which we term ghost attractors. To better understand the rules governing the transitions between ghost attractors, we use methods from dynamical systems theory, giving insights into high-order mechanisms underlying brain function.en
• dc.description.sponsorship This work has been funded by FEDER through the Competitiveness Factors Operational Program (COMPETE), by National funds through the Foundation for Science and Technology (FCT) under the scope of the project UID/Multi/50026; and by the projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000023, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). JC was supported by Portuguese Foundation for Science and Technology CEECIND/03325/2017, Portugal. GD acknowledges funding from the European Union’s Horizon 2020 FET Flagship Human Brain Project under Grant Agreement 785907 HBP SGA2, the Spanish Ministry Project PSI2016-75688-P (AEI/FEDER) and the Catalan Research Group Support 2017 SGR 1545. MK was supported by the European Research Council Consolidator Grant: CAREGIVING (615539), Pettit Foundation, Carlsberg Foundation and Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117). BC was supported by the French Government through the UCA-Jedi project managed by the National Research Agency (ANR-15-IDEX-01) and, in particular, by the interdisciplinary Institute for Modeling in Neuroscience and Cognition (NeuroMod) of the Université Côte d’Azur.
• dc.format.mimetype application/pdf
• dc.identifier.citation Vohryzek J, Deco G, Cessac B, Kringelbach ML. Cabral J. Ghost attractors in spontaneous brain activity: recurrent excursions into functionally-relevant BOLD phase-locking states. Front Syst Neurosci. 2020 Apr 17;14:20. DOI: 10.3389/fnsys.2020.00020
• dc.identifier.doi http://dx.doi.org/10.3389/fnsys.2020.00020
• dc.identifier.issn 1662-5137
• dc.identifier.uri http://hdl.handle.net/10230/45119
• dc.language.iso eng
• dc.publisher Frontiers
• dc.relation.ispartof Frontiers in Systems Neuroscience. 2020 Apr 17;14:20
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/785907
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/PSI2016-75688-P
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/615539
• dc.rights © 2020 Vohryzek, Deco, Cessac, Kringelbach and Cabral. 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) and the copyright owner(s) 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.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword LEiDAen
• dc.subject.keyword Ghost attractorsen
• dc.subject.keyword Dynamic functional connectivityen
• dc.subject.keyword Dynamical system theoryen
• dc.subject.keyword Functional networksen
• dc.subject.keyword Resting-stateen
• dc.title Ghost attractors in spontaneous brain activity: recurrent excursions into functionally-relevant BOLD phase-locking statesen
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion