Towards an efficient validation of dynamical whole-brain models - Aix-Marseille Université Accéder directement au contenu
Article Dans Une Revue Scientific Reports Année : 2022

Towards an efficient validation of dynamical whole-brain models

Résumé

Simulating the resting-state brain dynamics via mathematical whole-brain models requires an optimal selection of parameters, which determine the model’s capability to replicate empirical data. Since the parameter optimization via a grid search (GS) becomes unfeasible for high-dimensional models, we evaluate several alternative approaches to maximize the correspondence between simulated and empirical functional connectivity. A dense GS serves as a benchmark to assess the performance of four optimization schemes: Nelder-Mead Algorithm (NMA), Particle Swarm Optimization (PSO), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Bayesian Optimization (BO). To compare them, we employ an ensemble of coupled phase oscillators built upon individual empirical structural connectivity of 105 healthy subjects. We determine optimal model parameters from two- and three-dimensional parameter spaces and show that the overall fitting quality of the tested methods can compete with the GS. There are, however, marked differences in the required computational resources and stability properties, which we also investigate before proposing CMAES and BO as efficient alternatives to a high-dimensional GS. For the three-dimensional case, these methods generated similar results as the GS, but within less than 6% of the computation time. Our results contribute to an efficient validation of models for personalized simulations of brain dynamics.
Fichier principal
Vignette du fichier
s41598-022-07860-7.pdf (4.85 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Licence : CC BY - Paternité

Dates et versions

hal-04100822 , version 1 (28-09-2023)

Licence

Paternité

Identifiants

Citer

Kevin Wischnewski, Simon Eickhoff, Viktor Jirsa, Oleksandr Popovych. Towards an efficient validation of dynamical whole-brain models. Scientific Reports, 2022, 12 (1), pp.4331. ⟨10.1038/s41598-022-07860-7⟩. ⟨hal-04100822⟩
30 Consultations
4 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More