Theoretical analysis predicts an optimal therapeutic strategy in distinct parkinsonian landscapes of the striatum

Abstract

Parkinsons disease (PD) results from a loss of dopaminergic neurons. The age of disease onset, its progression and symptoms vary significantly between patients, pointing to a complex relationship between neuron loss and PD etiology. Yet, our understanding of the clinical variability remains incomplete. Here, we use biophysical modelling to characterize the dopaminergic landscape in the healthy and denervated striatum. Based on currently proposed mechanisms causing PD, we model three distinct denervation patterns, and show notable differences in the dopaminergic network as denervation progresses. We find local and global differences in the activity of two types of striatal neurons depending on the denervation pattern. Finally, we identify an optimal cellular strategy for maintaining normal dopamine signaling when neurons degenerate stochastically within our model. Our results derive a conceptual framework in which the clinical variability of PD is rooted in distinct denervation patterns and forms testable predictions for future PD research.