Depression is the leading cause of disability worldwide, and for the 1-2 % of treatment-resistant individuals with a chronic, unremitting course, subcallosal cingulate (SCC) deep brain stimulation (DBS) is an evolving experimental strategy. Treatment responses to SCC DBS are highly variable across different clinical centers, and objective standards are needed to help mitigate variable outcomes in future clinical trials. Connectomic DBS modeling is one avenue that holds promise for standardizing and simplifying the administration of SCC DBS. The pioneering work of the first 5 years of R01 MH102238 set the stage for a new era in DBS research, with the initial identification of ?connectomic targeting? for prospective surgical planning. Our novel approach to individualized precision medicine has resulted in substantial improvements to SCC DBS' long-term outcomes, but this model- based strategy was not available in its pivotal industry-sponsored trial, which suffered from suboptimal outcomes. Nonetheless, multiple groups continue to develop SCC DBS. The clinical trial at Mt. Sinai (UH3 NS103550) is combining neuroimaging and electrophysiology to optimize DBS for depression, and this proposal augments that effort, while leveraging the unique clinical datasets associated with its subjects. Our working hypothesis is that forceps minor and the cingulum bundle are the most probable therapeutic targets of SCC DBS. The overall objective of this proposal is therefore to test that connectomic hypothesis with computational rigor and electrophysiological validation.
The first aim will develop a standard biophysical connectome that can be used for customization and optimization of parameters in de novo subjects based on connectomic hypotheses. Results from this aim will be fundamental for processing connectomic DBS strategies within standard clinical workflows and applying SCC DBS technology on a larger scale.
The second aim will refine the SCC DBS biophysical connectome using high-density EEG collected monthly as part of a standard research protocol at Mt. Sinai, and then we will use the connectomic model to delineate specific bioelectric scalp signatures for activation of forceps minor and at least one cingulum bundle.
The third aim will evaluate theoretically optimal directional and current- steering strategies for SCC DBS in two use cases, energy-optimization and isolated/focal target activation. The proposal's outcome will be a validated set of computational tools that can be used for near real-time parameter customization and optimization in SCC DBS. Individualized, deployable model-based strategies for precision DBS are significant because they have a realistic opportunity to simplify the process of parameter selection and help make device programming more objective, and less variable, in future studies of SCC DBS.

Public Health Relevance

Deep brain stimulation (DBS) has the potential to impact positively the lives of individuals with intractable depression. Converging lines of theoretical evidence have identified two fiber bundles in the subcallosal cingulate (SCC) as probable therapeutic targets of SCC DBS, and this study's goal is to test this connectomic hypothesis with computational rigor and electrophysiological validation using the latest computational framework for precision DBS. Rigorous computational standards and tools that can be disseminated to other groups working on SCC DBS can help simplify and objectivity the process of parameter selection in future clinical studies.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Bioengineering of Neuroscience, Vision and Low Vision Technologies Study Section (BNVT)
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Mcmullen, David
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Case Western Reserve University
Biomedical Engineering
Schools of Medicine
United States
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