Inducing a meditative state by artificial perturbations: a mechanistic understanding of brain dynamics underlying meditation
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- dc.contributor.author Dagnino, Paulina Clara
- dc.contributor.author Galadí, Javier Alejandro
- dc.contributor.author Càmara, Estela
- dc.contributor.author Deco, Gustavo
- dc.contributor.author Escrichs, Anira
- dc.date.accessioned 2024-09-16T10:34:15Z
- dc.date.available 2024-09-16T10:34:15Z
- dc.date.issued 2024
- dc.description.abstract Contemplative neuroscience has increasingly explored meditation using neuroimaging. However, the brain mechanisms underlying meditation remain elusive. Here, we implemented a mechanistic framework to explore the spatiotemporal dynamics of expert meditators during meditation and rest, and controls during rest. We first applied a model-free approach by defining a probabilistic metastable substate (PMS) space for each condition, consisting of different probabilities of occurrence from a repertoire of dynamic patterns. Moreover, we implemented a model-based approach by adjusting the PMS of each condition to a whole-brain model, which enabled us to explore in silico perturbations to transition from resting-state to meditation and vice versa. Consequently, we assessed the sensitivity of different brain areas regarding their perturbability and their mechanistic local-global effects. Overall, our work reveals distinct whole-brain dynamics in meditation compared to rest, and how transitions can be induced with localized artificial perturbations. It motivates future work regarding meditation as a practice in health and as a potential therapy for brain disorders.
- dc.description.sponsorship P.D. was supported by the AGAUR FI-SDUR Grant (no. 2022 FISDU 00229) and by the AGAUR research support grant (ref. 2021 SGR 00917) funded by the Department of Research and Universities of the Generalitat of Catalunya. J.G. was supported by the Spanish Agencia Estatal de Investigación of the Ministerio de Ciencia e Innovación (FJC2021-047765-I). A.E. and G.D. were supported by the Grant PID2022-136216NB-I00 funded by MICIU/AEI/10.13039/501100011033 and by “ERDF A way of making Europe,” ERDF, EU. G.D. was also supported by the project NEurological MEchanismS of Injury, and Sleep-like cellular dynamics (NEMESIS) (ref. 101071900) funded by the EU ERC Synergy Horizon Europe. A.E. was also supported by the project eBRAIN-Health - Actionable Multilevel Health Data (id 101058516), funded by the EU Horizon Europe.
- dc.format.mimetype application/pdf
- dc.identifier.citation Dagnino PC, Galadí JA, Càmara E, Deco G, Escrichs A. Inducing a meditative state by artificial perturbations: a mechanistic understanding of brain dynamics underlying meditation. Network Neuroscience. 2024 Feb 12;8(2):517-40. DOI: 10.1162/netn_a_00366
- dc.identifier.doi http://dx.doi.org/10.1162/netn_a_00366
- dc.identifier.issn 2472-1751
- dc.identifier.uri http://hdl.handle.net/10230/61097
- dc.language.iso eng
- dc.publisher MIT Press
- dc.relation.ispartof Network Neuroscience. 2024 Feb 12;8(2):517-40
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/101058516
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2022-136216NB-100
- dc.relation.projectID info:eu-repo/grantAgreement/H2020/101071900
- dc.rights This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/legalcode
- dc.subject.keyword Meditation
- dc.subject.keyword fMRI
- dc.subject.keyword Brain states
- dc.subject.keyword Whole-brain modeling
- dc.subject.keyword Stimulation
- dc.title Inducing a meditative state by artificial perturbations: a mechanistic understanding of brain dynamics underlying meditation
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion