Vineet Tiruvadi Biomedical Engineering PhD Proposal Date: February 17th, 2017 Time: 9AM - 10AM Location: Emory School of Medicine P178   Advisors: Dr. Helen Mayberg, MD, Dept. of Psychiatry, Emory University Dr. Robert Butera, PhD, Dept. of Electrical and Computer Engineering and BME, Georgia Tech   Committee Members: Dr. Christopher Rozell, PhD, Dept. of Electrical and Computer Engineering, Georgia Tech Dr. Warren Grill, PhD, Dept. of Biomedical Engineering, Duke University Dr. Robert Gross, MD, PhD, Dept. of Neurosurgery, Emory University Dr. Donald Rainnie, PhD, Dept. of Psychiatry, Emory University   “Brain Network Dynamics in Deep Brain Stimulation for Clinical Depression” Treatment resistant depression (TRD) is a life-threatening mood disorder that is being treated using investigational deep brain stimulation (DBS). Our lab stimulates white matter tracts passing through the subcallosal cingulate cortex (SCCwm) with a prototype bidirectional DBS device in TRD patients, enabling an unprecedented level of both stimulation and recording electrophysiology study directly in human subjects. In this project, my goal is to study SCCwm-centric network oscillations associated with depression recovery through DBS. Core needs in SCCwm-DBS include the identification of a biometric that can objectively inform DBS management and a clarification of the precise brain regions being directly modulates by SCCwm. I hypothesize that SCCwm-DBS rapidly modulates alpha rhythms in brain regions connected through SCCwm and that SCC oscillations themselves reflect long-term recovery from depression. I propose to (1) model the recording capabilities of the prototype DBS device, (2) identify SCC oscillations that reflect depression state, and (3) characterize network-level alpha rhythm dynamics induced by precise SCCwm-DBS. The potential deliverables of this proposal include (1) a quantitative characterization of clinical DBS electrophysiology limitations, (2) an objective biometric of clinical state for systematic DBS programming and management in TRD patients, and (3) an electrophysiology-based classifier to confirm precise SCCwm-DBS stimulation.