Design of a novel closed-loop deep brain stimulation system for Parkinson's disease and obsessive-compulsive disorder

Abstract

We present a novel closed-loop subthalamic nucleus (STN) deep brain stimulation (DBS) scheme for Parkinson's disease (PD) and obsessive-compulsive disorder (OCD). The algorithm is designed to effectuate real-time, adaptive stimulation employing the outcome of the 0-1 test for chaos as a state-specific biomarker. In case of a null outcome, the system identifies optimal patterns of stimulation desynchronizing pathologic neuronal activity with minimal energy consumption, on grounds of a stochastic dynamical model and an appropriately formulated cost function. Simulations are performed utilizing microelectrode recordings (MERs) acquired during 8 and 2 DBS surgical interventions for PD and OCD, respectively.