Towards a scalable effective connectivity estimation in fMRI

The multivariate Ornstein-Uhlenbeck (mOU) approach for effective connectivity (EC) yields estimates in broad agreement with advanced Dynamic Causal Modeling (DCM) when hemodynamic response variability stays within the physiological range in healthy adults.

• Why it matters: Whole-brain, high-resolution directed EC estimation has been elusive because mechanistic models like DCM do not scale, while linear inversion methods often fail to recover key EC features reliably.
• What they did: Using Human Connectome Project S1200 release data, the authors adapt mOU EC estimation and compare it against advanced DCM, focusing on cases where hemodynamic response spatial variability is within the physiological range.
• The result: With low computational cost, mOU scales to large cohorts and high-resolution parcellations, outperforms functional connectivity for single-subject connectome fingerprinting, and enables directed mapping of hierarchical and modular brain organization.