Spatiotemporal Optimization of Deep Brain Stimulation for Parkinson's Disease

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PROJECT SUMMARY AND ABSTRACT The basal ganglia have a rich somatotopy and functional topography composed of motor subcircuits that are thought to be critically important to the pathophysiology of Parkinson's disease (PD) and successful application of deep brain stimulation therapy (DBS) for managing each cardinal motor sign of PD. There is a strong clinical need to better understand these processes and in turn harness them to deliver therapy that is tailored to a patient's own symptomatology and motor control needs on a moment by moment basis. This project will investigate how spatiotemporal optimization of DBS settings can differentially affect neural pathway activation through the brain's motor control network and how those results translate to improving each of the four cardinal motor signs of PD (bradykinesia, rigidity, tremor, and postural instability). Aim 1 will investigate at the single cell, ensemble, and network levels how spatiotemporal parameters of DBS influence information transmission, and critically how the motor control network is able to produce naturalistic movements despite information lesions induced by high-frequency stimulation. Aim 2 will develop and apply a Bayesian Dual Adaptive Control algorithm to investigate how spatiotemporal DBS settings affect electrically-evoked compound action potentials and how those features map onto modulating individual motor signs. Aim 3 will leverage the ground-truth electrophysiological data from high-density microelectrode array recordings at the site of DBS and within the motor control network to validate key parameters used in computational models of neural pathway activation with DBS therapy. The proposed study integrates innovative high-density microelectrode array recordings, closed-loop optimization algorithms, micron-resolution anatomical pathway imaging, and subject-specific computational models of DBS. Together, this project will enhance our understanding of the pathophysiology of PD and provide critical data towards translating next generation personalized and responsive DBS therapies.