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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.
