Progression and differential control of postural and kinetic tremor with deep brain stimulation

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Abstract Essential Tremor (ET), despite being the most common movement disorder affecting 4% of adults over age 40, remains relatively understudied in terms of its pathogenesis, neurophysiology, clinical classification, and optimization of treatments on a patient-specific basis. For the 25-55% of medication-refractory patients whose symptoms have become functionally limiting, surgical management is recommended, most commonly with deep brain stimulation (DBS). However, despite recent advances in DBS lead technology, controversy exists over the optimal target, side effects occur frequently, and up to 73% of patients experience loss of benefit over time. As a result, there is a clear need for refinement and deepened understanding of optimizing treatments for ET. This project will leverage an ongoing prospective clinical study in human patients diagnosed with ET and implanted with directional DBS leads, integrating high-field magnetic resonance imaging, patient- specific pathway activation modeling of DBS, quantitative sensors, and comprehensive electromyography measurements to further understand the neural and muscular mechanisms behind tremor control and progression. Specifically, Aim 1 will identify the cerebello-thalamo-cortical pathways involved in kinetic and postural tremor control with directional DBS leads, pathway activation optimization algorithms, and quantitative sensors. Aim 2 will approach identifying the underlying mechanisms of tremor control from the peripheral muscular end using whole-body electromyography. Finally, Aim 3 will determine how tolerance to stimulation, disease progression, or lead placement contribute to long-term DBS failure in tremor control. While DBS can result in improvement of clinical tremor scores, physicians still have trouble capturing action tremor in the short-term and maintaining therapeutic benefit in the long-term. Understanding the pathways contributing to tremor and to side effects via a model-based, patient-specific programming approach would allow for improved and more consistent control of patients’ symptoms with DBS therapy.