Whole-brain estimates of directed connectivity for human connectomics

• DOI: 10.1016/j.neuroimage.2020.117491
• Publication Date: 2020-10-24T14:48:29Z
• Authors: Stefan Frässle; Zina M. Manjaly; Cao T. Do; Lars Kasper; Klaas P. Pruessmann; Klaas E. Stephan
• Keywords: Connectomics; Human brain

Connectomics is essential for understanding large-scale brain networks but requires that individual connection estimates are neurobiologically interpretable. In particular, a principle of organization reciprocal connections between cortical areas functionally asymmetric. This challenge fMRI-based connectomics in humans where only undirected functional connectivity routinely available. By contrast, whole-brain effective (directed) computationally challenging, and emerging methods require empirical validation. Here, using motor task at 7T, we demonstrate novel generative model can infer known features network (>200 regions, >40,000 connections) highly efficiently. Furthermore, graph-theoretical analyses directed identify roles more accurately than estimates. These results, which be achieved an entirely unsupervised manner, the feasibility inferring open new avenues human connectomics.