ORCID
- Fouragnan, Elsa: 0000-0003-1485-0332
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.
DOI
10.1126/sciadv.aav4962
Publication Date
2019-07-01
Publication Title
Science advances
Volume
5
Issue
7
First Page
eaav4962
Last Page
eaav4962
Embargo Period
2019-08-28
Organisational Unit
School of Psychology
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Queirazza, F., Fouragnan, E., Steele, J., Cavanagh, J., & Philiastides, M. (2019) 'Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression', Science advances, 5(7), pp. eaav4962-eaav4962. Available at: https://doi.org/10.1126/sciadv.aav4962
