Linking brain dynamics, neural mechanisms, and deep brain stimulation in Parkinson's disease: An integrated perspective

Abstract 

Parkinson's disease (PD) is a neurodegenerative disease as well as a dynamical disease. Its symptoms can be alleviated by high-frequency deep brain stimulation (DBS), which has become standard therapeutic strategy for about two decades. Today, the subthalamic nucleus (STN) is the preferred target for DBS in PD. The physiological mechanisms underlying the effects of this procedure are still far from clear, and several hypotheses have been proposed to explain the effect of DBS. However, no consensus has yet been reached. In this review paper, existing interpretations of DBS effects during STN stimulation in PD are examined. Based on results of a population-based computational model, we argue that the alleviation of PD symptoms originates in the functional decoupling of neurons in the stimulated area. This mechanism, which we call stimulation-induced functional decoupling (SIFD), is then tested against various observations, paradoxes, and modeling results. Finally, we suggest that current hypotheses indeed reflect various facets of SIFD and the resonant properties of STN neurons. This review is the first to propose an explanation of the effects of DBS by integrating and building bridges across several levels of description, including synapses, neuron population, and population network.

Keywords: Deep brain stimulation, Neuronal network modeling, Parkinson's disease, Brain dynamics