ArticleAnnals of general psychiatry2026
The prefrontal-striatal signatures of reduced model-based learning in depressed patients.
Article in Annals of general psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Efficacy and EEG-ECG mechanisms of taVNS combined with TEAS for negative symptoms of schizophrenia: a protocol for a 2 × 2 factorial randomized controlled trial.European archives of psychiatry and clinical neuroscience · 2026Article
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7 authors.
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Abstract
backgroundAnhedonia 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.
methodsWe 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.
resultsDepressed 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.
conclusionsThis 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.
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