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

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperReviewResearchpeer-review

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 languageEnglish
JournalComputational and Structural Biotechnology Journal
Volume21
Pages (from-to)335-345
Number of pages11
ISSN2001-0370
DOIs
Publication statusPublished - Jan 2023

Keywords

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

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