AUTHOR=Hwang Brian Y. , Salimpour Yousef , Tsehay Yohannes K. , Anderson William S. , Mills Kelly A. TITLE=Perspective: Phase Amplitude Coupling–Based Phase–Dependent Neuromodulation in Parkinson’s Disease JOURNAL=Frontiers in Neuroscience VOLUME=14 YEAR=2020 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2020.558967 DOI=10.3389/fnins.2020.558967 ISSN=1662-453X ABSTRACT=

Deep brain stimulation (DBS) is an effective surgical therapy for Parkinson’s disease (PD). However, limitations of the DBS systems have led to great interest in adaptive neuromodulation systems that can dynamically adjust stimulation parameters to meet concurrent therapeutic demand. Constant high-frequency motor cortex stimulation has not been remarkably efficacious, which has led to greater focus on modulation of subcortical targets. Understanding of the importance of timing in both cortical and subcortical stimulation has generated an interest in developing more refined, parsimonious stimulation techniques based on critical oscillatory activities of the brain. Concurrently, much effort has been put into identifying biomarkers of both parkinsonian and physiological patterns of neuronal activities to drive next generation of adaptive brain stimulation systems. One such biomarker is beta-gamma phase amplitude coupling (PAC) that is detected in the motor cortex. PAC is strongly correlated with parkinsonian specific motor signs and symptoms and respond to therapies in a dose-dependent manner. PAC may represent the overall state of the parkinsonian motor network and have less instantaneously dynamic fluctuation during movement. These findings raise the possibility of novel neuromodulation paradigms that are potentially less invasiveness than DBS. Successful application of PAC in neuromodulation may necessitate phase-dependent stimulation technique, which aims to deliver precisely timed stimulation pulses to a specific phase to predictably modulate to selectively modulate pathological network activities and behavior in real time. Overcoming current technical challenges can lead to deeper understanding of the parkinsonian pathophysiology and development of novel neuromodulatory therapies with potentially less side-effects and higher therapeutic efficacy.