Dynamic sensitivity analysis: defining personalised strategies to drive brain state transitions via whole brain modelling
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- dc.contributor.author Vohryzek, Jakub
- dc.contributor.author Cabral, Joana
- dc.contributor.author Castaldo, Francesca
- dc.contributor.author Sanz-Perl, Yonatan
- dc.contributor.author Lord, Louis-David
- dc.contributor.author Fernandes, Henrique M.
- dc.contributor.author Litvak, Vladimir
- dc.contributor.author Kringelbach, Morten L.
- dc.contributor.author Deco, Gustavo
- dc.date.accessioned 2023-03-13T07:44:53Z
- dc.date.available 2023-03-13T07:44:53Z
- dc.date.issued 2023
- dc.description.abstract Traditionally, in neuroimaging, model-free analyses are used to find significant differences between brain states via signal detection theory. Depending on the a priori assumptions about the underlying data, different spatio-temporal features can be analysed. Alternatively, model-based techniques infer features from the data and compare significance from model parameters. However, to assess transitions from one brain state to another remains a challenge in current paradigms. Here, we introduce a “Dynamic Sensitivity Analysis” framework that quantifies transitions between brain states in terms of stimulation ability to rebalance spatio-temporal brain activity towards a target state such as healthy brain dynamics. In practice, it means building a whole-brain model fitted to the spatio-temporal description of brain dynamics, and applying systematic stimulations in-silico to assess the optimal strategy to drive brain dynamics towards a target state. Further, we show how Dynamic Sensitivity Analysis extends to various brain stimulation paradigms, ultimately contributing to improving the efficacy of personalised clinical interventions.
- dc.description.sponsorship The authors declare that they have no conflict of interest. J.V. is supported by the EU H2020 FET Proactive project Neurotwin grant agreement no. 101017716. J.C. is funded by the Portuguese Foundation for Science and Technology grants UIDB/50026/2020, UIDP/50026/2020, la Caixa” Foundation (LCF/BQ/PR22/11920014) and CEECIND/ 03325/2017, Portugal. F.C. is funded by the EU-project euSNN European School of Network Neuroscience (MSCA-ITN-ETN H2020-860563). The Wellcome Centre for Human Neuroimaging is supported by core funding from Wellcome [203147/Z/16/Z]. M.L.K. is supported by the Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117), and Centre for Eudaimonia and Human Flourishing at Linacre College funded by the Pettit and Carlsberg Foundations. G.D. is supported by the Spanish national research project (AEI-PID2019-105772GB I00/AEI/10.13039 /501100011033) funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), State Research Agency (AEI).
- dc.format.mimetype application/pdf
- dc.identifier.citation Vohryzek J, Cabral J, Castaldo F, Sanz-Perl Y, Lord LD, Fernandes HM, et al. Dynamic sensitivity analysis: defining personalised strategies to drive brain state transitions via whole brain modelling. Computational and Structural Biotechnology Journal. 2023;21:335-45. DOI: 10.1016/j.csbj.2022.11.060
- dc.identifier.doi http://dx.doi.org/10.1016/j.csbj.2022.11.060
- dc.identifier.issn 2001-0370
- dc.identifier.uri http://hdl.handle.net/10230/56181
- dc.language.iso eng
- dc.publisher Elsevier
- dc.relation.ispartof Computational and Structural Biotechnology Journal. 2023;21:335-45
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/101017716
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/86056
- dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PID2019-105772GB-I00
- dc.rights © 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (https://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.subject.keyword Spatio-temporal dynamics
- dc.subject.keyword Brain stimulation
- dc.subject.keyword Whole-brain models
- dc.subject.keyword Brain State
- dc.title Dynamic sensitivity analysis: defining personalised strategies to drive brain state transitions via whole brain modelling
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion