Affective bias predicts changes in depression during deep brain stimulation therapy
- PMID: 40201337
- PMCID: PMC11977254
- DOI: 10.3389/fnhum.2025.1539857
Affective bias predicts changes in depression during deep brain stimulation therapy
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 (n = 8, n = 2) undergoing DBS for treatment-resistant depression at different academic medical centers completed an affective bias task at multiple time points before and after DBS implantation. The affective bias task involved rating the emotional content of a series of static photographic stimuli of facial expressions throughout their DBS treatment. Patients' ratings were compared with those of non-depressed controls to calculate affective bias scores. Linear mixed-effects modeling was used to assess changes in bias scores over time and their relationship with depression severity measured by the Hamilton Depression Rating Scale (HDRS-17).
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.
Keywords: affective bias; deep brain stimulation; facial emotion; mood proxy; subcallosal cingulate; treatment-resistant depression; ventral capsule striatum.
Copyright © 2025 Cui, Mocchi, Metzger, Kalva, Magnotti, Fiedorowicz, Waters, Kovach, Reed, Mathura, Steger, Pascuzzi, Kanja, Veerakumar, Tiruvadi, Crowell, Denison, Rozell, Pouratian, Goodman, Riva Posse, Mayberg and Bijanki.
Conflict of interest statement
KB and MM are inventors of a planned patent on the electrophysiology biomarker reported in the current manuscript. KB is inventor of an issued patent on an unrelated method of electrical stimulation to treat depression, anxiety, and pain. WG has received donated devices from Medtronic and has consulting agreements with Biohaven Pharmaceuticals. CR is an inventor on a filed patent related to electrophysiology biomarkers of depression recovery and serves on the scientific advisory board (with equity) in Motif Neurotech, Inc. HM received consulting and IP licensing fees from Abbott Laboratories. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
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References
-
- American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Arlington, VA: American Psychiatric Publishing, Inc. 10.1176/appi.books.9780890425596 - DOI
-
- Bates D., Mächler M., Bolker B., Walker S. (2015). Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. 10.18637/jss.v067.i01 - DOI
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