Evidence map›Paper›PMID 42428124›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Stimulation-evoked orbitofrontal activity as a biomarker for DBS personalization in depression.

Layth S Mattar, Lily Chamakura, Amirreza Alijanpourotaghsara, Sameer Rajesh, Atefeh Ghazavi, Evangelia Tsolaki, Victoria Gates, Anusha Allawala, Nicole R Provenza, Kala Bailey and 8 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Layth S MattarBaylor College of Medicine, Department of Neurosurgery.ORCID 0009-0002-8631-7174
Lily ChamakuraCarnegie Mellon University, Neuroscience Institute.ORCID 0000-0001-6235-9623
Amirreza AlijanpourotaghsaraUniversity of Texas Southwestern Medical Center, Department of Neurological Surgery.ORCID 0000-0001-6942-9997
Sameer RajeshUniversity of Texas Southwestern Medical Center, Department of Neurological Surgery.
Atefeh GhazaviUniversity of Texas Southwestern Medical Center, Department of Neurological Surgery.ORCID 0000-0002-8021-3393
Evangelia TsolakiUniversity of California, Los Angeles, Department of Neurological Surgery.
Victoria GatesBaylor College of Medicine, Department of Neurosurgery.
Anusha AllawalaUniversity of California, San Francisco, Department of Neurological Surgery.ORCID 0000-0003-0830-583X
Nicole R ProvenzaBaylor College of Medicine, Department of Neurosurgery.ORCID 0000-0002-6952-5417
Kala BaileyUniversity of Texas Southwestern Medical Center, Department of Psychiatry.
Sanjay MathewTexas A&M University Naresh K. Vashisht College of Medicine, Department of Psychiatry and Behavioral Sciences, Bryan, TX.
Denise OswaltPerelman School of Medicine, Department of Neurosurgery.ORCID 0000-0001-6260-5636
Garrett P BanksBaylor College of Medicine, Department of Neurosurgery.ORCID 0000-0001-6292-977X
Wayne K GoodmanBaylor College of Medicine, Department of Psychiatry and Behavioral Sciences.
Sameer A ShethBaylor College of Medicine, Department of Neurosurgery.ORCID 0000-0001-8770-8965
Sarah R HeilbronnerBaylor College of Medicine, Department of Neurosurgery.ORCID 0000-0003-0893-5364
Nader PouratianUniversity of Texas Southwestern Medical Center, Department of Neurological Surgery.ORCID 0000-0002-0426-3241
Eleonora BartoliBaylor College of Medicine, Department of Neurosurgery.ORCID 0000-0002-5824-5065

Funding

Deep brain stimulation for depression using directional current steering an individualized network targetingUH3NS103549 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GOODMAN, WAYNE K, POURATIAN, NADER · 2017 to 2025
$8.7M
NINDS NIH HHS UH3 NS103549
6 · The paper itself

Abstract

Finding suitable therapies for treatment-refractory neuropsychiatric disorders constitutes a major goal for translational neuroscience. Deep brain stimulation shows promise for treatment resistant depression, but treatment efficacy varies substantially across patients. Objective, electrophysiologically driven strategies to optimize deep brain stimulation for treatment resistant depression could greatly improve clinical efficacy by minimizing the trial-and-error approach needed to personalize stimulation settings. This may not only reduce the delay between the start of the treatment and symptom improvement, but also enable acute, real-time verification of circuit engagement, advancing our understanding of the mechanism mediating antidepressant effects. Here, we investigate whether cerebro-cerebral evoked potentials elicited through different deep brain stimulation configurations could be used to guide stimulation personalization for treatment resistant depression. Cerebro-cerebral evoked potentials offer a fast, objective way to identify regions engaged by stimulation, revealing the effective connectivity pattern of the stimulated location. Data were collected from eight patients with treatment resistant depression who received dual bilateral deep brain stimulation devices targeting the subcallosal cingulate and ventral capsule/ventral striatum. During an initial in-hospital monitoring period, single-pulse electrical stimulation was delivered through the deep brain stimulation devices and cerebro-cerebral evoked potentials were recorded through temporary stereo-electroencephalography probes across fronto-temporal regions. Patients underwent several outpatient stimulation programming sessions over the course of 9 months to identify the stimulation configurations leading to the greatest improvement in depressive symptoms. We retrospectively analysed cerebro-cerebral evoked potentials obtained in response to stimulation of different stimulation configurations to identify features distinguishing the clinically effective configurations. The deep brain stimulation configurations leading to the greatest improvement in depressive symptoms were associated with significantly larger evoked potentials in the orbitofrontal cortex and showed an increased number of evoked potentials across dorsal and ventral prefrontal regions. Waveform similarity analysis revealed a gradient in therapeutic effects, such that multiple alternative stimulation configurations led to similar symptom improvement. The vast deep brain stimulation parameter space might contain a configuration subspace defined by comparable therapeutic effects. In addition, evoked potentials obtained from single-pulse and from bursts of high-frequency stimulation displayed similar spatial patterns, suggesting that either method might be able to identify the configuration best engaging the circuit mediating the clinical response. Together, these findings provide proof-of-principle evidence that stimulation-evoked prefrontal responses reflect network engagement associated with antidepressant effects. Cerebro-cerebral evoked potentials may offer an objective and acute strategy to guide contact selection in deep brain stimulation for treatment resistant depression.

Indexed as

biomarkercerebro-cerebral evoked potentialsdeep brain stimulationintracranial EEGorbitofrontal cortexTreatment-resistant depression

Identifiers

PMID42428124
PMCPMC13345399

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.