Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling

Jakub Vohryzek; Joana Cabral; Francesca Castaldo; Yonatan Sanz-Perl; Louis David Lord; Henrique M. Fernandes; Vladimir Litvak; Morten L. Kringelbach; Gustavo Deco

doi:10.1016/j.csbj.2022.11.060

Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling

Jakub Vohryzek^*, Joana Cabral, Francesca Castaldo, Yonatan Sanz-Perl, Louis David Lord, Henrique M. Fernandes, Vladimir Litvak, Morten L. Kringelbach, Gustavo Deco

^*Corresponding author for this work

Department of Clinical Medicine - Center for Music In the Brain

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Review › Research › peer-review

16 Citations (Scopus)

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.

Original language	English
Journal	Computational and Structural Biotechnology Journal
Volume	21
Pages (from-to)	335-345
Number of pages	11
ISSN	2001-0370
DOIs	https://doi.org/10.1016/j.csbj.2022.11.060
Publication status	Published - Jan 2023

Keywords

Brain State
Brain stimulation
Spatio-temporal dynamics
Whole-brain models

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10.1016/j.csbj.2022.11.060Licence: CC BY

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title = "Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling",

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.",

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doi = "10.1016/j.csbj.2022.11.060",

language = "English",

volume = "21",

pages = "335--345",

journal = "Computational and Structural Biotechnology Journal",

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Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling. / Vohryzek, Jakub; Cabral, Joana; Castaldo, Francesca et al.
In: Computational and Structural Biotechnology Journal, Vol. 21, 01.2023, p. 335-345.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Review › Research › peer-review

TY - JOUR

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T2 - Defining personalised strategies to drive brain state transitions via whole brain modelling

AU - Vohryzek, Jakub

AU - Cabral, Joana

AU - Castaldo, Francesca

AU - Sanz-Perl, Yonatan

AU - Lord, Louis David

AU - Fernandes, Henrique M.

AU - Litvak, Vladimir

AU - Kringelbach, Morten L.

AU - Deco, Gustavo

PY - 2023/1

Y1 - 2023/1

N2 - 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.

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Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling

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