Evidence map›Paper›PMID 40201337›Full record

ArticleFrontiers in human neuroscience2025

Affective bias predicts changes in depression during deep brain stimulation therapy.

Brian Cui, Madaline M Mocchi, Brian A Metzger, Prathik Kalva, John F Magnotti, Jess G Fiedorowicz, Allison Waters, Christopher K Kovach, Yvonne Y Reed, Raissa K Mathura and 13 more

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2025. 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

23 authors.

Brian CuiDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Madaline M MocchiDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Brian A MetzgerDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Prathik KalvaDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
John F MagnottiDepartment of Neurosurgery, University of Pennsylvania, Philadelphia, PA, United States.
Jess G FiedorowiczOttawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada.
Allison WatersNash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Christopher K KovachDepartment of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, United States.
Yvonne Y ReedDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Raissa K MathuraDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Camille StegerNash Family Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Bailey PascuzziDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Kourtney KanjaDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
Ashan VeerakumarDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Vineet TiruvadiDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Andrea CrowellDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Lydia DenisonDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Christopher J RozellSchool of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States.
Nader PouratianDepartment of Neurosurgery, University of Texas Southwestern, Dallas, TX, United States.
Wayne GoodmanDepartment of Psychiatry, Baylor College of Medicine, Houston, TX, United States.
Patricio Riva PosseDepartment of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States.
Helen S MaybergDepartment of Neurosurgery, Carver College of Medicine, University of Iowa, Iowa City, IA, United States.
Kelly Rowe BijankiDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.

Funding

Electrophysiological Biomarkers to Optimize DBS for DepressionUH3NS103550 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI MAYBERG, HELEN S, RIVA-POSSE, PATRICIO · 2017 to 2023
$7.7M
NINDS NIH HHS UH3 NS103550
6 · The paper itself

Abstract

Introduction: Deep brain stimulation (DBS) is a promising treatment for refractory depression, utilizing surgically implanted electrodes to stimulate specific anatomical targets within the brain. However, limitations of patient-reported and clinician-administered mood assessments pose obstacles in evaluating DBS treatment efficacy. In this study, we investigated whether an affective bias task, which leverages the inherent negative interpretation bias seen in individuals with depression, could serve as a reliable measure of mood changes during DBS therapy in patients with treatment-resistant depression. Methods: Two cohorts of patients ( Results: We observed significant improvements in total affective bias scores over the course of DBS treatment in both cohorts. Pre-DBS, patients exhibited a negative affective bias, which was nearly eliminated post-DBS, with total bias scores approaching those of non-depressed controls. Positive valence trials showed significant improvement post-DBS, while negative valence trials showed no notable change. A control analysis indicated that stimulation status did not significantly affect bias scores, and thus stimulation status was excluded from further modeling. Linear mixed-effects modeling revealed that more negative bias scores were associated with higher HDRS-17 scores, particularly for positive valence stimuli. Additionally, greater time elapsed since DBS implantation was associated with a decrease in HDRS-17 scores, indicating clinical improvement over time. Discussion: Our findings demonstrate that the affective bias task leverages the inherent negative interpretation bias seen in individuals with depression, providing a standardized measure of how these biases change over time. Unlike traditional mood assessments, which rely on subjective introspection, the affective bias task consistently measures changes in mood, offering potential as a tool to monitor mood changes and evaluate the candidacy of DBS treatment in refractory depression.

Indexed as

affective biasdeep brain stimulationfacial emotionmood proxysubcallosal cingulatetreatment-resistant depressionventral capsule striatum

Identifiers

PMID40201337
PMCPMC11977254

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Registered trials

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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 OpenQuestion graph.