Neural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF.

ABSTRACT: Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions. Here, we introduce an efficient and accessible implementation of the DMF model: the FastDMF. By leveraging analytical and numerical advances-including a novel estimation of the feedback inhibition control parameter and a Bayesian optimization algorithm-t

SUBMITTER: Herzog R 

PROVIDER: S-EPMC11674928 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature