# Deep Brain Stimulation for Depression Using Directional Current Steering and Individualized Network Targeting

> **NIH NIH UH3** · BAYLOR COLLEGE OF MEDICINE · 2022 · $2,930,616

## Abstract

ABSTRACT
The public health burden of Treatment Resistant Depression (TRD) has prompted clinical trials of deep brain
stimulation (DBS) that have, unfortunately, produced inconsistent outcomes. Potential gaps and opportunities
include a need: (1) to better understand the neurocircuitry of the disease; (2) for precision DBS devices that
can target brain networks in a clinically and physiologically validated manner; and (3) for greater insight into
stimulation dose-response relationships. These needs are based on our overarching hypothesis that network-
guided neuromodulation is critical for the efficacy of DBS in TRD. This project aims to address the unmet need
of TRD patients by identifying brain networks critical for treating depression and to use next generation
precision DBS with steering capability to engage these targeted networks and develop a new therapy
for TRD. We use the Boston Scientific (BS) Vercise DBS system, which offers a segmented steerable lead
with multiple independent current sources that allows true directional steering. Moreover, this system
integrates stimulation field modeling (SFM) with MR tractography to predict network engagement. We use an
innovative approach of targeting both subgenual cingulate (SGC) and ventral capsule/ventral striatum
(VC/VS), which we term corticomesolimbic DBS. These targets are hubs in distinct yet partially overlapping
depression networks and emerging basic science literature implicates them in bidirectional modulation of
depression circuits. We also apply a paradigm-shifting approach using intracranial stereo-EEG (sEEG)
subacutely after DBS implant to evaluate the clinical reliability of steering, SFMs, and tractography and to
define and then target the networks mediating symptoms of depression. In Aim 1, in the Epilepsy Monitoring
Unit (EMU), we investigate the capability of Vercise to selectively engage distinct brain networks and compare
the spatial distribution of evoked network activity and modulation with that predicted by SFM and tractography.
In Aim 2, we conduct further studies in the EMU to delineate depression-relevant networks and show
behavioral changes with network-targeted stimulation. We use a variety of tasks to probe different symptom
domains and novel assessment tools (Computerized Adaptive Testing and Automated Facial Affect
Recognition) to enhance classification and model algorithms to optimize stimulation patterns. In Aim 3, we
bring the results from Aims 1 and 2 together, to test the therapeutic potential of corticomesolimbic DBS in 12
subjects with TRD, with a focus on safety, feasibility, and preliminary efficacy in a 8-month open label trial with
a subsequent randomized, blinded withdrawal of stimulation to assess efficacy. The impact of this proposal
includes physiological validation of current “steering” DBS technology to target specific networks, insights into
effects of stimulation parameters on network physiology, an improved understanding of the pathophysiology o...

## Key facts

- **NIH application ID:** 10017324
- **Project number:** 5UH3NS103549-04
- **Recipient organization:** BAYLOR COLLEGE OF MEDICINE
- **Principal Investigator:** Wayne K Goodman
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $2,930,616
- **Award type:** 5
- **Project period:** 2017-09-15 → 2026-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017324

## Citation

> US National Institutes of Health, RePORTER application 10017324, Deep Brain Stimulation for Depression Using Directional Current Steering and Individualized Network Targeting (5UH3NS103549-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10017324. Licensed CC0.

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