Brain states and transitions: insights from computational neuroscience

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  • dc.contributor.author Kringelbach, Morten L.
  • dc.contributor.author Deco, Gustavo
  • dc.date.accessioned 2020-11-12T08:40:57Z
  • dc.date.available 2020-11-12T08:40:57Z
  • dc.date.issued 2020
  • dc.description.abstract Within the field of computational neuroscience there are great expectations of finding new ways to rebalance the complex dynamic system of the human brain through controlled pharmacological or electromagnetic perturbation. Yet many obstacles remain between the ability to accurately predict how and where best to perturb to force a transition from one brain state to another. The foremost challenge is a commonly agreed definition of a given brain state. Recent progress in computational neuroscience has made it possible to robustly define brain states and force transitions between them. Here, we review the state of the art and propose a framework for determining the functional hierarchical organization describing any given brain state. We describe the latest advances in creating sophisticated whole-brain computational models with interacting neuronal and neurotransmitter systems that can be studied fully in silico to predict and design novel pharmacological and electromagnetic interventions to rebalance them in disease.en
  • dc.description.sponsorship M.L.K. is supported by the ERC Consolidator Grant CAREGIVING (615539); Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117); and Centre for Eudaimonia and Human Flourishing funded by the Pettit Foundation and Carlsberg Foundation. G.D. is supported by the Spanish Research Project (PID2019-105772GB-I00 AEI FEDER EU), funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI), and European Regional Development Funds (FEDER); HBP SGA3 Human Brain Project Specific Grant Agreement 3 (grant agreement 945539), funded by the EU H2020 FET Flagship program; and SGR Research Support Group (2017 SGR 1545), funded by the Catalan Agency for Management of University and Research Grants (AGAUR).
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Kringelbach ML, Deco G. Brain states and transitions: insights from computational neuroscience. Cell Rep. 2020 Sep 8;32(10):108128. DOI: 10.1016/j.celrep.2020.108128
  • dc.identifier.doi http://dx.doi.org/10.1016/j.celrep.2020.108128
  • dc.identifier.issn 2211-1247
  • dc.identifier.uri http://hdl.handle.net/10230/45738
  • dc.language.iso eng
  • dc.publisher Elsevier
  • dc.relation.ispartof Cell Reports. 2020 Sep 8;32(10):108128
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/615539
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/945539
  • dc.rights © 2020 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.title Brain states and transitions: insights from computational neuroscienceen
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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