Affective bias predicts changes in depression during deep brain stimulation therapy

Brian Cui ¹ Madaline Mocchi ¹ Brian Metzger ¹ Prathik Kalva ¹ John F Magnotti ² Jess Fiedorowicz ³ Allison Waters ⁴ Christopher K. Kovach ⁵ Yvonne Reed ¹ Raissa Mathura ¹ Camille Steger ⁶ Bailey Pascuzzi ¹ Kourtney Kanja ¹ Ashan Veerakumar ⁶ Vineet Tiruvadi, MD, PhD ⁶ Andrea Crowell ⁶ Lydia Denison ⁶ Christopher J Rozell ⁷ Nader Pouratian ⁸ Wayne Goodman ⁹ Patricio Riva Posse ⁶ Helen S. Mayberg ⁴ Kelly Rowe Bijanki ^1*

• ¹ Department of Neurosurgery, Baylor College of Medicine, Houston, United States
• ² Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States
• ³ Ottawa Hospital Research Institute (OHRI), Ottawa, Ontario, Canada
• ⁴ Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York, United States
• ⁵ Department of Neurosurgery, Carver College of Medicine, The University of Iowa, Iowa City, Iowa, United States
• ⁶ Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, Georgia, United States
• ⁷ School of Electrical and Computer Engineering, College of Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States
• ⁸ University of Texas Southwestern Medical Center, Dallas, Texas, United States
• ⁹ Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, United States

Deep brain stimulation (DBS) is a promising treatment for refractory depression, utilizing surgically-implanted electrodes to stimulate specific neuroanatomical targets. 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 leveraging the inherent negative interpretation bias in individuals with depression as a reliable measure of mood changes during DBS therapy in patients with treatment-resistant depression. 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 involves 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 mixedeffects 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). 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. Our findings demonstrate that the affective bias task utilizes 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 efficacy of DBS treatment in refractory depression.