Title:
OSCILLATORY DYNAMICS IN ANTIDEPRESSANT DEEP BRAIN STIMULATION

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Author(s)
Tiruvadi, Vineet Ravi
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Advisor(s)
Butera, Robert J.
Mayberg, Helen S.
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Abstract
Deep brain stimulation (DBS) is a neurosurgical treatment being investigated for severe brain disorders including clinical depression. Our lab precisely targets and electrically stimulates specific white matter tracts within the subcallosal cingulate cortex (SCCwm) region of the brain in order to alleviate depression symptoms. Using a prototype, bi-directional clinical DBS device we were able to record brain oscillations, or rhythms, over months from patients with treatment resistant depression (TRD), enabling an unprecedented level of quantitative study in Depression DBS. Here, I address two major questions in the field: (1) can we use brain recordings to measure how depressed a patient is, and (2) can we use brain recordings to confirm we are adequately stimulating the brain networks associated with successful treatment? Before we could answer these questions, we needed to know (0) can we reliably measure brain activity through the prototype device? We characterized a major limitation in this prototype device, finding that recordings must be analysed carefully to tease out meaningful brain signals. We then developed clinically-informed models using machine-learning approaches to help assess depression severity from long-term brain recordings. Finally, we found measurable brain rhythms that can be used to differentiate the location being stimulated, a 'cortical signature', for SCCwm targeted DBS. Together, these results form a first-order foundation for further engineering and clinical study of Depression DBS.
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Date Issued
2022-08-02
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Dissertation
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