Abstract
While cognitive behavioral therapy (CBT) is an effective treatment for major depressive disorder, only up to 45% of depressed patients will respond to it. At present, there is no clinically viable neuroimaging predictor of CBT response. Notably, the lack of a mechanistic understanding of treatment response has hindered identification of predictive biomarkers. To obtain mechanistically meaningful fMRI predictors of CBT response, we capitalize on pretreatment neural activity encoding a weighted reward prediction error (RPE), which is implicated in the acquisition and processing of feedback information during probabilistic learning. Using a conventional mass-univariate fMRI analysis, we demonstrate that, at the group level, responders exhibit greater pretreatment neural activity encoding a weighted RPE in the right striatum and right amygdala. Crucially, using multivariate methods, we show that this activity offers significant out-of-sample classification of treatment response. Our findings support the feasibility and validity of neurocomputational approaches to treatment prediction in psychiatry.
Original language | English |
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Article number | eaav4962 |
Pages (from-to) | 1-15 |
Number of pages | 15 |
Journal | Science Advances |
Volume | 5 |
Issue number | 7 |
DOIs | |
Publication status | Published - 31 Jul 2019 |
ASJC Scopus subject areas
- General
- Physics and Astronomy (miscellaneous)
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Steele, Douglas
- Neuroscience - Clinical Professor (Teaching and Research) of Neuroimaging
Person: Academic