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Intrinsic connectivity patterns of striatal subfields predict individual dimensions of psychopathology and are associated with cholinergic and serotonergic neurotransmission in schizophrenia

Neuropsychopharmacology volume 51, pages 956–967 (2026)Cite this article

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Abstract

Symptoms of schizophrenia may reflect different pathophysiological processes in the striatum, but the links between striatal subfield connectivity, symptom dimensions, and molecular architectures remain unclear. Using connectivity profiles from 12 striatal subfields to predict negative, positive, affective, and cognitive symptoms in schizophrenia, we identified consistent connectivity features through cross-validations and validated with leave-one-site-out analysis and an independent dataset. Feature importance scores for brain parcels linked through consistent connectivity features that predicted symptoms were spatially correlated with density maps of 19 receptors/transporters from prior molecular imaging in healthy populations using partial least squares. We found that the connectivity profiles of the rostral and ventral striatal subfields significantly predicted affective and cognitive symptoms, respectively, and these predictions were generalized to the independent sample. Feature importance scores for brain parcels connected to the ventral striatum (predicting cognitive symptoms) were spatially correlated with density maps of both the vesicular acetylcholine transporter and the serotonin 1 A receptor. By contrast, importance scores for parcels linked to rostral striatal connectivity (predicting affective symptoms) were specifically associated with the spatial distribution of the serotonin 1 A receptor. Here, we show specific striatal connectivity patterns related to symptom dimensions and indicate multiple neurotransmitter systems to underlie the reward-related disturbances in schizophrenia.

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Fig. 1: Study overview.
Fig. 2: Prediction of symptom dimensions by the functional profiles of each of the 12 striatal subfields using linear regression models with Lasso penalty.
Fig. 3: Feature selection, independent validation, and interpretation of the selected overlapping connectivity features based on their relative importance in generalizing symptom predictions and functional characterization of the involved brain regions.
Fig. 4: Neurotransmitter distribution pattern in the association with the selected connectivity profile for the right rostral and ventral striatal subfields that predicted affective and cognitive symptoms.

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Data availability

Information for the main sample used in the present study have been included in the Supplementary Materials. The raw data of the main sample recruited from 7 international institutions are protected and are not publicly available due to data privacy. These data can be accessed upon reasonable request to the principal investigator of each data collection institution. Derived data supporting the findings of this study are available from the corresponding author (chen.ji@sjtu.edu.cn) upon request. The B-SNIP data that support the findings of this study are publicly available on the database of the NIMH Data Archive (NDA, https://nda.nih.gov/); a data access request must be approved to protect the confidentiality of participants. The density maps of 19 neurotransmitter receptors and transporters for the partial least square regression analysis are available at https://github.com/netneurolab/hansen_receptors. Source data are provided with this paper. MATLAB scripts to run the main analyses have been made publicly available via the Open Science Framework and can be accessed at https://osf.io/auy4n. Matlab scripts written to perform additional post-hoc analyses are available from the authors upon request. Code used to perform sparse canonical correlation analysis is available at https://github.com/cedricx/sCCA/tree/master/sCCA/code/final.

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Funding

This work was supported by the National Natural Science Foundation of China (No. 82201658 & No. 82371506 [to J.C.]), the Shanghai Rising-Star Program (24QA2704700 [to J.C.]), the STI2030-Major Projects (No. 2022ZD0214000 [to J.C.]), and the German Center for Mental Health (to T.N.-J.).

Author information

Author notes

  1. These authors contributed equally: Zhiqiu He, Wenli He.

Authors and Affiliations

  1. Department of Mental Health, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu & Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang, China

    Zhiqiu He & Wenli He

  2. Experimental Research Center for Medical and Psychological Science, School of Psychology, Third Military Medical University, Chongqing, China

    Zhiyi Chen

  3. Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China

    Wei Wei

  4. Center for Educational Science and Technology, Beijing Normal University, Zhuhai, China

    Xiaojin Liu

  5. Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany

    Juergen Dukart, Felix Hoffstaedter, Kaustubh R. Patil & Simon B. Eickhoff

  6. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Juergen Dukart, Felix Hoffstaedter, Kaustubh R. Patil & Simon B. Eickhoff

  7. Center for Brain Health and Brain Technology, Global Institute of Future Technology, Shanghai Jiao Tong University, Shanghai, China

    Weidong Li & Ji Chen

  8. Schizophrenia and Bipolar Disorder Program, McLean Hospital, Belmont, MA, 02478, USA

    Justin T. Baker

  9. Department of Psychiatry, Harvard Medical School, Boston, MA, 02114, USA

    Justin T. Baker

  10. Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, USA

    Avram J. Holmes

  11. Department of Psychiatry and Psychotherapy, Otto-von-Guericke University, Magdeburg, Germany

    Thomas Nickl-Jockschat

  12. German Center for Mental Health (DZPG), partner site Halle-Jena-Magdeburg, Center for Intervention and Research on adaptive and maladaptive brain Circuits underlying mental health (C-I-R-C), Halle-Jena-Magdeburg, Germany

    Thomas Nickl-Jockschat

  13. Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical Faculty, University of Tübingen, Tübingen, Germany

    Birgit Derntl & Lydia Kogler

  14. German Center for Mental Health (DZPG), Mannheim, Germany

    Birgit Derntl & Lydia Kogler

  15. Univ Lille, INSERM U1172, Lille Neuroscience & Cognition Centre, Plasticity & SubjectivitY team & CHU Lille, Fontan Hospital, CURE platform, Lille, France

    Renaud Jardri

  16. Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Germany

    Oliver Gruber

  17. Department of Neuroscience, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    André Aleman

  18. Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    Iris E. Sommer

  19. Department of Psychiatry, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China

    Yunrong Lu

  20. School of Psychology, Shanghai Jiao Tong University, Shanghai, China

    Ji Chen

Authors
  1. Zhiqiu He
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  2. Wenli He
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  3. Zhiyi Chen
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  4. Wei Wei
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  5. Xiaojin Liu
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  6. Juergen Dukart
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  7. Weidong Li
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  8. Justin T. Baker
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  9. Avram J. Holmes
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  10. Felix Hoffstaedter
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  11. Thomas Nickl-Jockschat
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  12. Birgit Derntl
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  13. Lydia Kogler
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  14. Renaud Jardri
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  15. Oliver Gruber
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  16. André Aleman
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  17. Iris E. Sommer
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  18. Kaustubh R. Patil
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  19. Yunrong Lu
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  20. Simon B. Eickhoff
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  21. Ji Chen
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Contributions

J.C. and Y.L. conceptualized the study and designed the research. J.C., Y.L., and S.B.E interpreted the results and provided critical revisions of the manuscript. Z.H., W.H., W.W., and Z.C. analyzed the data and made figures; Z.H. and J.C. wrote the original draft. X.L. provided striatal parcellation atlases. T.N.J., B.D., L.K., R.J., O.G., A.A., I.E.S., provided the data. J.D., W.L., J.T.B., A.J.H., F.H., K.R.P., and Y.L. provided guidance on result interpretation and edited the paper. All authors approved the final version of the manuscript for submission.

Corresponding authors

Correspondence to Yunrong Lu or Ji Chen.

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He, Z., He, W., Chen, Z. et al. Intrinsic connectivity patterns of striatal subfields predict individual dimensions of psychopathology and are associated with cholinergic and serotonergic neurotransmission in schizophrenia. Neuropsychopharmacol. 51, 956–967 (2026). https://doi.org/10.1038/s41386-026-02354-w

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