A multi-modal, asymmetric, weighted, and signed description of anatomical connectivity.

ABSTRACT: The macroscale connectome is the network of physical, white-matter tracts between brain areas. The connections are generally weighted and their values interpreted as measures of communication efficacy. In most applications, weights are either assigned based on imaging features-e.g. diffusion parameters-or inferred using statistical models. In reality, the ground-truth weights are unknown, motivating the exploration of alternative edge weighting schemes. Here, we explore a multi-modal, regression-based model that endows reconstructed fiber tracts with directed and signed weights. We find that the model fits observed data well, outperforming a suite of null models. The estimated weights are subject-specific and highly reliable, even when fit using relatively few training samples, and the net

SUBMITTER: Tanner J 

PROVIDER: S-EPMC11245624 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature