A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs

Understand

Determining functional brain connectivity is crucial to understanding the brain and neural differences underlying disorders such as autism.

• Recent studies have used Gaussian graphical models to learn brain connectivity via statistical dependencies across brain regions from neuroimaging.
• However, previous studies often fail to properly incorporate priors tailored to neuroscience, such as preferring shorter connections.
• To remedy this problem, the paper here introduces a novel, weighted-$\ell_1$, multi-task graphical model (W-SIMULE).