Evidence map›Paper›PMID 41572320›Full record

ArticleAnnals of general psychiatry2026

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

Xiaoxia Wang, Xiaoyan Zhou, Dong Zhang, Zongzhang Zhang, YuShun Gong, Zhengzhi Feng, Jing Ming Hou

Abstract read
In one paragraph

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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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xiaoxia WangDepartment of Rehabilitation Medicine, Southwest Hospital, the first affiliated hospital to Army Medical University, Chongqing, China.
Xiaoyan ZhouDepartment of Clinical Psychology, Mental Health Center of Chongqing, Chongqing, China.
Dong ZhangDepartment of Radiology, XinQiao Hospital, Army Medical University, Chongqing, China.
Zongzhang ZhangNational Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China.
YuShun GongDepartment of Medical equipment and Metrology, College of Biomedical Engineering, Army Medical University, Chongqing, China.
Zhengzhi FengDepartment of Clinical Psychology, Southwest Hospital, Army Medical University, Army Medical University, Chongqing, China. fzz@tmmu.edu.cn.
Jing Ming HouDepartment of Rehabilitation Medicine, Southwest Hospital, the first affiliated hospital to Army Medical University, Chongqing, China. jingminghou@tmmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

AnhedoniaFunctional neuroimagingMajor depressive disorderModel-based learningPrefrontal-striatal circuits

Identifiers

PMID41572320
PMCPMC12908330

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.