Estimation and validation of individualized dynamic brain models with resting state fMRI.

ABSTRACT: A key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by individual-level human brain activity or used data-driven statistical characterizations of individuals that are not mechanistic. We aim to bridge this gap through the development of a new modeling approach termed Mesoscale Individualized Neurodynamic (MINDy) modeling, wherein we fit nonlinear dynamical systems models directly to human brain imaging data. The MINDy framework is able to produce these data-driven network models for hundreds to thousands of interacting brain regions in just 1-3 ​min per subject. We demonstrate that the models are valid

SUBMITTER: Singh MF 

PROVIDER: S-EPMC7875185 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature