Disruption of Striatal Intrinsic Ignition in Huntington's Disease: an In-Silico Perturbational Approach to Emulate Disease Progression and Recovery

Abstract

Huntingtons disease (HD) is a neurodegenerative disorder caused by a single gene that severely affects motor, cognitive, and behavioral functions and is ultimately fatal. While disruptions in the structural integrity of the striatum are well documented, less is known about how the underlying functional impairments relate to the disease. We developed a large-scale modeling framework based on intrinsic ignition to uncover functional anomalies during HD progression. We first measured how much a spontaneous event in one brain region influences the rest of the brain, then systematically perturbed the activity of the striatum to predict the empirical changes in functional connectivity (FC) by re-optimizing the model parameters and conducting in-silico experiments. Results showed that disruption of the activity dynamics in the caudate, and to some extent the putamen, are the key factors that explain a substantial amount of the variance in FC alterations during HD progression. We then assessed the ability to recover whole-brain functional activity by driving the caudate and putamen activity towards a healthy-like regime and found that, by tuning the local bifurcation parameter of caudate and putamen, it is possible to recover whole-brain healthy functional activity, albeit moderately. Surprisingly, although the functional disruptions in the caudate better explained the alterations in FC, the recovery of the dynamics was more effective in the putamen. Overall, our results suggest that the disruptions of the dynamics in the striatum can explain the gross functional connectivity changes in HD. Our study demonstrates that computational modeling is an important tool to reveal the underlying patterns behind the observed data and provides an opportunity to test interventional mechanisms in silico.