Joint Estimation of Brain Connectivity and Propagation of Neurodegeneration

Motivation: Models of propagation of neurodegeneration encode hypotheses on the mechanisms of pathology spread via the brain’s connectome. However, they fail to accurately capture pathology patterns, partly due to errors in tractography-estimated connectomes. Goal(s): We use this link between pathology and connectivity to help resolve errors in connectivity estimation. Specifically, we use disease-related pathology to jointly estimate brain connectivity and pathology propagation. Approach: We introduce a new algorithm to use an estimate of the false-positive potential (FPP) of each connection to constrain the pathology-informed connectome-optimisation. Results: Combining FPP and pathology-informed optimisation yields substantial improvement to both the connectome and the connectome-based prediction of pathology. Impact: By jointly estimating pathology and the connectome, we advance both disease understanding and understanding of structural connectivity. The work is a first demonstration of the general idea of using pathology to inform on brain connectivity.