Continuous, Tract-Constrained Directional Vector Fields from rDCM Effective Connectivity Using Mixture Density Networks

Effective connectivity estimates from dynamic causal modeling (rDCM) are typ-ically represented as dense directed matrices. However, these matrices do notdirectly specify a continuous, geometric description of how directed influenceis routed through 3D white matter anatomy. Because these estimates are ex-pressed as abstract parcel to parcel weights, they may require fusion with addi-tional data, such as diffusion MRI tractography in order to define anatomicallyplausible pathways. I present a solution for fusing whole-cortex estimates fromregression dynamic causal modeling (Schaefer-400) with a dense tractographyatlas (HCP-1065)