Dagnino, Paulina ClaraGaladí, Javier AlejandroCàmara, EstelaDeco, GustavoEscrichs, Anira2024-09-162024-09-162024Dagnino 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_003662472-1751http://hdl.handle.net/10230/61097Contemplative 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.application/pdfengThis 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.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1162/netn_a_00366MeditationfMRIBrain statesWhole-brain modelingStimulationinfo:eu-repo/semantics/openAccess