Presented By: Biomedical Engineering
PhD Defense: Charles Lu
Precision Neuromodulation of Sensorimotor Systems
NOTICE: This event will be held via Zoom. The link will be placed below.
Zoom: https://umich-health.zoom.us/j/95667535536
Therapeutic neuromodulation has an established history for clinical indications, such as deep brain stimulation for movement disorders and spinal cord stimulation for pain, despite an incomplete understanding of its mechanism of action. Novel neuroprosthetics have the potential to enable wholly new therapies, including sensory restoration and treatment of affective disorders. In order to fully realize the potential of these interventions, precise parameterization of stimulation, informed by better understanding of underlying processes, is required. This dissertation explores the temporal and spatial determinants of outcomes for stimulation within the context of clinical and experimental sensorimotor neuromodulation.
The first study of the dissertation defines a new functional target for subthalamic deep brain stimulation for Parkinson disease treatment. While optimal sites of stimulation are often analyzed as discrete points in space, therapeutic tissue activation is known to activate entire volumes of surrounding tissue. To identify markers of these volumes, we used machine learning tools to identify associations between features of wideband neural recordings and regions of clinically validated stimulation regions derived from patient-specific tissue activation models. The study identified several electrophysiological markers of therapeutic activation regions, providing a tool for efficient optimization of stimulation programming.
Despite the importance of spatially precise stimulation, conventional stereotactic methods are limited by intrinsic sources of error. The second study assessed a novel form of lead localization utilizing local impedance at deep brain sites. We demonstrated that in vivo impedance measurements generally match patterns observed in electrostatic simulations and showed that these values can be efficiently estimated using diffusion tensor data. Impedances measured using a clinical macroelectrode provided spatial information at the resolution of millimeters and could be used to roughly localize deep brain trajectories, presenting a prototype method to complement existing targeting technologies.
The final study evaluated a novel form of deep brain stimulation for modulation of pain. Previous rodent studies show that stimulation of zona incerta can provide analgesic effect, and clinical evidence suggests that stimulation of a nearby nucleus, nominally used to treat motor manifestations of Parkinson disease, often also results in improvement of pain symptoms. We directly tested the analgesic effect of zona incerta stimulation in humans and demonstrated that stimulation at the physiological spiking frequency of zona incerta selectively reduces perceived heat pain.
Chair: Dr. Parag G. Patil
Zoom: https://umich-health.zoom.us/j/95667535536
Therapeutic neuromodulation has an established history for clinical indications, such as deep brain stimulation for movement disorders and spinal cord stimulation for pain, despite an incomplete understanding of its mechanism of action. Novel neuroprosthetics have the potential to enable wholly new therapies, including sensory restoration and treatment of affective disorders. In order to fully realize the potential of these interventions, precise parameterization of stimulation, informed by better understanding of underlying processes, is required. This dissertation explores the temporal and spatial determinants of outcomes for stimulation within the context of clinical and experimental sensorimotor neuromodulation.
The first study of the dissertation defines a new functional target for subthalamic deep brain stimulation for Parkinson disease treatment. While optimal sites of stimulation are often analyzed as discrete points in space, therapeutic tissue activation is known to activate entire volumes of surrounding tissue. To identify markers of these volumes, we used machine learning tools to identify associations between features of wideband neural recordings and regions of clinically validated stimulation regions derived from patient-specific tissue activation models. The study identified several electrophysiological markers of therapeutic activation regions, providing a tool for efficient optimization of stimulation programming.
Despite the importance of spatially precise stimulation, conventional stereotactic methods are limited by intrinsic sources of error. The second study assessed a novel form of lead localization utilizing local impedance at deep brain sites. We demonstrated that in vivo impedance measurements generally match patterns observed in electrostatic simulations and showed that these values can be efficiently estimated using diffusion tensor data. Impedances measured using a clinical macroelectrode provided spatial information at the resolution of millimeters and could be used to roughly localize deep brain trajectories, presenting a prototype method to complement existing targeting technologies.
The final study evaluated a novel form of deep brain stimulation for modulation of pain. Previous rodent studies show that stimulation of zona incerta can provide analgesic effect, and clinical evidence suggests that stimulation of a nearby nucleus, nominally used to treat motor manifestations of Parkinson disease, often also results in improvement of pain symptoms. We directly tested the analgesic effect of zona incerta stimulation in humans and demonstrated that stimulation at the physiological spiking frequency of zona incerta selectively reduces perceived heat pain.
Chair: Dr. Parag G. Patil
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