Virginia Tech professors Brooks Casas and Pearl Chiu of the Fralin Biomedical Research Institute at VTC are pioneering a personalized approach to depression treatment by exploring brain signals that may predict whether someone with depression is likely to see their symptoms improve. Virginia Tech photos
Could the Brain’s Reward System Unlock a Cure for Depression? A groundbreaking study in the Journal of Affective Disorders suggests that the way our brains process rewards may be the key to revolutionizing depression treatment. Scientists Pearl Chiu and Brooks Casas from the Fralin Biomedical Research Institute are delving deep into the neural mechanisms of reward learning, searching for a way to personalize therapies like never before. At the heart of their research lies a crucial brain signal—one that flickers to life when we anticipate rewards. This tiny but powerful spark may hold the secret to helping millions break free from the grip of depression, and Virginia Tech researchers are racing to harness its potential.
Major depression, affecting more than 21 million Americans each year according to the CDC, is a leading cause of disability globally. Despite this prevalence, current treatments often prove inadequate, failing to provide lasting relief for many sufferers.
Professors Pearl Chiu and Brooks Casas of the Fralin Biomedical Research Institute at VTC are pioneering a personalized approach to depression treatment by exploring how our brains process rewards and setbacks.
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Their study, which published in January in the Journal of Affective Disorders, examines two brain signals — prediction error and expected value — that may predict whether someone with depression is likely to see their symptoms improve.
“Major depression isn’t one-size-fits-all,” Chiu said. “People with depression learn and respond to rewards and setbacks differently, often in ways that align with specific symptoms.”
The study pinpointed two critical brain signals—prediction error and expected value—as powerful indicators of a person’s potential to recover from depression. Expected value, which captures the brain’s anticipation of rewards and shapes decision-making, stood out as a reliable predictor of remission across various treatments. Meanwhile, prediction error, which detects discrepancies between expected and actual outcomes to help refine behavior, offered deeper insights into the brain’s adaptive processes.
Together, these signals paint a more intricate picture of how individual learning patterns shape mental health outcomes, opening the door to precision-targeted, symptom-specific therapies that could revolutionize depression treatment.
“This finding underscores the power of the brain’s reward system in forecasting recovery,” Casas said. “By observing how each person responds to rewards and setbacks, we can open new pathways for designing treatments that match individual learning patterns.”
“This brings us closer to truly personalized mental health care,” noted Vansh Bansal, first author of the study and a graduate student with Chiu and Casas.
