Clinical Study for Adaptive Deep Brain Stimulation (aDBS)Controlled by Intracerebral Activity in Parkinson's Disease

Overview

Despite its therapeutic effectiveness in Parkinson's disease (PD) the current deep brain stimulation (DBS) strategy could achieve an even better clinical result by adapting to patient's condition. As intracerebral activity analyzed by recording local field potentials (LFPs) from DBS electrodes correlates to PD symptoms, a new stimulation approach would be an "intelligent" adaptive DBS system able to change stimulation settings automatically to the patient's needs using LFPs as control variable.

Despite their proven efficacy in treating Parkinson's disease (PD), deep brain stimulation (DBS) systems could be further optimized to maximize treatment benefits. In particular, because current DBS strategies based on fixed stimulation settings leave the typical parkinsonian motor fluctuations and rapid symptom variations partly uncontrolled, research has focused on developing a novel adaptive DBS (aDBS) system able to adapt moment-by-moment to the patient's clinical condition. aDBS consists of a simple closed-loop model designed to measure and analyze a control variable reflecting the patient's clinical condition to change stimulation settings and send them to an "intelligent" implanted stimulator. Intracerebral activity analyzed by recording local field potentials (LFPs) from electrodes implanted for DBS in the past 15 years has helped in clarifying basal ganglia pathophysiology and its relation to PD symptoms. Many LFP studies have revealed unknown functions of basal ganglia in PD patients during the execution of motor, cognitive, and behavioral task showing the existence of a "code" in LFP oscillations corresponding to the of patient's clinical condition. LFP-clinical correlations should provide the rationale for developing and implementing new aDBS devices able to adapt stimulation parameters moment-by-moment to the individual patient's needs using LFPs as a control variable for feedback.