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Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain

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dc.contributor.author Wang, Peng
dc.contributor.author Kong, Ru
dc.contributor.author Kong, Xiaolu
dc.contributor.author Liégeois, Raphaël
dc.contributor.author Orban, Csaba
dc.contributor.author Deco, Gustavo
dc.contributor.author Yeo, Thomas BT
dc.date.accessioned 2019-01-21T17:39:39Z
dc.date.available 2019-01-21T17:39:39Z
dc.date.issued 2019
dc.identifier.citation Wang P, Kong R, Kong X, Liégeois R, Orban C, Deco G, Van den Heuvel MP, Yeo BTT. Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain. Science Advances. 2019 Jan 09;5(1):eaat7854. DOI: 10.1126/sciadv.aat7854
dc.identifier.issn 2375-2548
dc.identifier.uri http://hdl.handle.net/10230/36350
dc.description.abstract We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminarspecific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain.
dc.description.sponsorship This work was supported by Singapore MOE Tier 2 (MOE2014-T2-2-016), NUS Strategic Research (DPRT/944/09/14), NUS SOM Aspiration Fund (R185000271720), Singapore NMRC (CBRG/0088/2015), NUS YIA, and the Singapore National Research Foundation (NRF) Fellowship (Class of 2017). Our research also used resources provided by the Center for Functional Neuroimaging Technologies, P41EB015896, and instruments supported by 1S10RR023401, 1S10RR019307, and 1S10RR023043 from the Athinoula A. Martinos Center for Biomedical Imaging at the Massachusetts General Hospital. Our computational work for this article was partially performed on resources of the National Supercomputing Centre, Singapore (www.nscc.sg). Data were provided by the HCP, WU-Minn Consortium (Principal Investigators: D. Van Essen and K. Ugurbil; 1U54MH091657) funded by the 16 NIH institutes and centers that support the NIH Blueprint for Neuroscience Research and by the McDonnell Center for Systems Neuroscience at Washington University.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher American Association for the Advancement of Science (AAAS)
dc.relation.ispartof Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain. Science Advances. 2019 Jan 09;5(1):eaat7854
dc.rights Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1126/sciadv.aat7854
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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