Title

Pallidal stimulation in Parkinson disease differentially modulates local and network β activity

Document Type

Article

Date of Original Version

7-31-2018

Abstract

β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. Objectives. We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex. Approach. We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open. Main results. DBS significantly suppressed low β power within the GPi (-26.98% ± 15.14%), p < 0.05) without modulation of sensorimotor cortical β power (low or high). In contrast, stimulation suppressed pallidocortical high β coherence (-38.89% ± 6.19%, p = 0.02) and dWPLI (-61.40% ± 8.75%, p = 0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex. Significance. We highlight the role of DBS in desynchronizing network activity, particularly in the high β band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low β oscillations locally within the basal ganglia and high β oscillations across the BGTC motor circuit.

Publication Title, e.g., Journal

Journal of Neural Engineering

Volume

15

Issue

5

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