The prefrontal–striatal signatures of reduced model-based learning in depressed patients

Anhedonia is the core symptom of major depressive disorder (MDD). Accumulating evidence indicates that an imbalance between model-based (MB) and model-free (MF) reinforcement learning (RL) characterizes MDD, but the underlying neural substrates remain unclear. We examined whether alterations in MB and MF reward prediction error (RPE) neural signature underlie deficits in RL in depressed patients. We used a two-stage Markov decision task (MDT) in combination with computational modeling to examine model-based and model-free learning. A total of 49 MDD and 41 matched HC individuals performed the MDT. 19 MDD and 21 HC individuals underwent functional neuroimaging during the MDT. The stress-RL deficits model was tested using a mediation model with MB and MF RL as mediators between stress and depressive/anhedonic symptoms. Depressed patients showed RL deficits, with less reliance on MB strategies and more reliance on MF strategies. MB and MF RL deficits mediated the relationship between stress and anhedonic symptoms, with specific striatal signatures (i.e., RPEMF signals in VTA and caudate) mediating stress and anhedonia symptoms across MDD and HC groups. This study showed deficits in model-based RL for depressed patients, with underlying neural deficits in prefrontal-striatal RPE signals, which would be promising for improving therapeutic practice in depression.