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