TY - JOUR
T1 - Neural correlates of weighted reward prediction error during reinforcement learning classify response to cognitive behavioral therapy in depression
AU - Queirazza, Filippo
AU - Fouragnan, Elsa
AU - Steele, J. Douglas
AU - Cavanagh, Jonathan
AU - Philiastides, Marios G.
PY - 2019/7
Y1 - 2019/7
N2 - 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.
AB - 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.
UR - https://pearl.plymouth.ac.uk/context/psy-research/article/1346/viewcontent/224410.full.pdf
U2 - 10.1126/sciadv.aav4962
DO - 10.1126/sciadv.aav4962
M3 - Article
SN - 2375-2548
VL - 5
SP - eaav4962-eaav4962
JO - Science advances
JF - Science advances
IS - 7
ER -