Vohryzek, Jakub;
Cabral, Joana;
Castaldo, Francesca;
Sanz-Perl, Yonatan;
Lord, Louis-David;
Fernandes, Henrique M;
Litvak, Vladimir;
... Deco, Gustavo; + view all
(2023)
Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling.
Computational and Structural Biotechnology Journal
, 21
pp. 335-345.
10.1016/j.csbj.2022.11.060.
Preview |
PDF
1-s2.0-S2001037022005530-main.pdf - Published Version Download (2MB) | Preview |
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.
| Type: | Article |
|---|---|
| Title: | Dynamic sensitivity analysis: Defining personalised strategies to drive brain state transitions via whole brain modelling |
| Location: | Netherlands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.csbj.2022.11.060 |
| Publisher version: | https://doi.org/10.1016/j.csbj.2022.11.060 |
| Language: | English |
| Additional information: | © 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 (http://creativecommons. org/licenses/by/4.0/). |
| Keywords: | Spatio-temporal dynamics, Brain stimulation, Whole-brain models, Brain State |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10164155 |
Archive Staff Only
 |
View Item |
