Language

English

Publication Date

1-1-2026

Journal

Frontiers in Psychiatry

DOI

10.3389/fpsyt.2026.1808486

PMID

42147009

PMCID

PMC13171579

PubMedCentral® Posted Date

4-30-2026

PubMedCentral® Full Text Version

Post-print

Abstract

Background: Despite growing evidence supporting deep brain stimulation (DBS) for treatment- resistant depression (TRD), how stimulation delivered across hemispheres or across multiple targets interact to shape large-scale network activity remains poorly characterized.

Objective: Using a unique opportunity to simultaneously stimulate the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS) in subjects with TRD while recording neural activity across putative prefrontal networks underlying depression via intracranial electrodes, we investigated whether bilateral or multi-target stimulation has additive, synergistic/super-additive, or antagonistic/sub-additive effects on power modulation across depression-related brain networks.

Methods: Four DBS leads, and ten stereo-electroencephalography (sEEG) leads were implanted in depression-related prefrontal brain regions in three subjects with TRD. Power modulation in response to unilateral and bilateral stimulation, as well as interaction classes of combinatorial stimulations, were evaluated across various combinations of frequency bands and region of interests (ROI) using marginal predictions from a linear mixed-effects model which were then used as input for machine learning classifiers to predict the additive interaction class of combinatorial stimulations.

Results: Bilateral and multi-target stimulation produced additive or sub-additive interactions in most cases. A decision tree classifier identified ROI as the most important feature for predicting interaction class, followed by stimulation target and spectral frequency band.

Keywords

additive interaction, deep brain stimulation, local field potential, multi-target stimulation, stereo-electroencephalography, treatment resistant depression

Published Open-Access

yes

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