IS A COMPUTATIONAL MODEL USEFUL TO UNDERSTAND THE EFFECT OF DEEP BRAIN STIMULATION IN PARKINSON'S DISEASE?

Abstract

A growing number of computational models have been proposed over the last few years to help explain the therapeutic effect of deep brain stimulation (DBS) on motor disorders in Parkinson's disease (PD). However, none of these has been able to explain in a convincing manner the physiological mechanisms underlying DBS. Can these models really contribute to improving our understanding? The model by Rubin and Terman [31] represents one of the most comprehensive and biologically plausible models of DBS published recently. We examined the validity of the model, replicated its simulations and tested its robustness. While our simulations partially reproduced the results presented by Rubin and Terman [31], several issues were raised including the high complexity of the model in its non simplified form, the lack of robustness of the model with respect to small perturbations, the nonrealistic representation of the thalamus and the absence of time delays. Computational models are indeed necessary, but they may not be sufficient in their current forms to explain the effect of chronic electrical stimulation on the activity of the basal ganglia (BG) network in PD.