Neural Networks and Neurofeedback in Parkinson’s Disease

Abstract

Aberrant neural network synchrony in basal ganglia thalamocortical circuits has been implicated in the pathophysiology of Parkinson’s disease. Manipulating these abnormal activation patterns may therefore offer a novel avenue for treating this disabling condition. Evidence suggests that network activity can be normalized with both dopaminergic drug treatment and deep brain stimulation (DBS), and protocols that directly target specific oscillatory patterns (―closed-loop DBS‖) are under development. Another potential avenue for the modulation of specific neural activation patterns is neurofeedback. This noninvasive technique entails providing a continuous update of one’s neural activity so that volitional control of selected brain regions, networks, or rhythms can be learned. This could be accompanied by specific therapeutic changes in behavior and clinical symptomatology in disease, according to the neural circuits that are modulated. Most neurofeedback research has used electroencephalography (EEG) but recently neurovascular signals measured with functional magnetic resonance imaging (fMRI) have been targeted as well. In this paper, we discuss the evidence implicating certain rhythms, particularly the beta (10–35 Hz) oscillation, in Parkinson’s disease. We also perform a systematic review evaluating the therapeutic efficacy of neurofeedback in Parkinson’s disease and make suggestions for future research.