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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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This event also will be offered virtually. Please click here to join via Zoom.
“Teasing Apart the 'Target' of Brain Stimulation for Depression with Computation”
Bryan Howell, Ph.D.
Research Assistant Professor
Department of Biomedical Engineering
Duke University
ABSTRACT
Depression is a condition characterized by persistent negative mood and has become the leading cause of disability worldwide. About one third of people with depression fail to respond to standard treatments, and 1−2% of depressed individuals have a severe unremitting form that requires surgical intervention. One evolving surgical option for depression is subcallosal cingulate (SCC) deep brain stimulation (DBS). Good outcomes in SCC DBS are achieved when placing the stimulating electrode within the confluence of nearby white matter, but it’s still unclear which fiber tracts and what proportions need to be activated to produce an optimal antidepressant response. Additionally, activation of SCC white matter produces no immediately adjustable behaviors, so dosing must be monitored under expert psychiatric care. Without a behavioral readout, computational modeling has served a role in defining candidate targets for stimulation, and our working hypothesis is that activation of forceps minor and the cingulum bundles by SCC DBS are sufficient to produce a therapeutic response. Detailed MR-based head models of SCC DBS were used to tailor energy delivery to each target tract in 7 subjects undergoing SCC DBS, and we studied potentials evoked by 2 Hz stimuli using 256-sensor EEG. In 6 of the 7 subjects, we observed a two-state response. Each cingulum bundle drove a lateralized, quasi-static response approximately 30 ms in duration when 50% or more of the pathway was activated, but this response was terminated or subdued when less than 10% of forceps minor was co-activated. With co-activation, a state shift occurred, propagating a bilaterally symmetric wave from anterior to posterior over 150 ms. If reproducible over a larger population, these bioelectronic signatures of connectomic engagement could provide a cost-effective method for target confirmation in studies of future and past cohorts. Lesson learned from developing SCC DBS inspire a new frontier of data-driven, personalized strategies of neuromodulation for depression.
BIOGRAPHY
Bryan Howell (PhD) is a graduate from the University of Michigan with broad experience in prosthetic devices used for brain stimulation. He completed his PhD in Biomedical Engineering at Duke University in 2015, with work focused on developing new electrode designs for neuromodulation, and undertook fellowships in deep brain stimulation for depression at Case Western Reserve University and Emory University. He is now a Research Assistant Professor in the Department of Biomedical Engineering at Duke University.
Dr. Howell’s research focuses on applications of neuromodulation for depression, namely with deep brain stimulation (DBS) and transcranial electrical stimulation (tES). These two experimental techniques show promise as an alternative treatment option and adjunct when standard approaches fall short, but their clinical outcomes are still too variable for widespread adoption. By combining computation, neuroimaging, and electrophysiology, we study these techniques at multiple scales, translating theory into new strategies by understanding how applied electromagnetic fields interact with the neural milieu. We currently have funding to study the bioelectronic signatures of connectomic perturbations in DBS for depression, and are running a feasibility study in humans that combines tES with transcranial magnetic stimulation (TMS) to test interferential and combinatorial approaches for noninvasive brain stimulation.
