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@ARTICLE{Chen:893853,
      author       = {Chen, Ji and Wensing, Tobias and Hoffstaedter, Felix and
                      Cieslik, Edna C. and Müller, Veronika I. and Patil,
                      Kaustubh R. and Aleman, André and Derntl, Birgit and
                      Gruber, Oliver and Jardri, Renaud and Kogler, Lydia and
                      Sommer, Iris E. and Eickhoff, Simon B. and Nickl-Jockschat,
                      Thomas},
      title        = {{N}eurobiological substrates of the positive formal thought
                      disorder in schizophrenia revealed by seed connectome-based
                      predictive modeling},
      journal      = {NeuroImage: Clinical},
      volume       = {30},
      issn         = {2213-1582},
      address      = {[Amsterdam u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2021-02877},
      pages        = {102666 -},
      year         = {2021},
      abstract     = {Formal thought disorder (FTD) is a core symptom cluster of
                      schizophrenia, but its neurobiological substrates remain
                      poorly understood. Here we collected resting-state fMRI data
                      from 276 subjects at seven sites and employed
                      machine-learning to investigate the neurobiological
                      correlates of FTD along positive and negative symptom
                      dimensions in schizophrenia. Three a priori,
                      meta-analytically defined FTD-related brain regions were
                      used as seeds to generate whole-brain resting-state
                      functional connectivity (rsFC) maps, which were then
                      compared between schizophrenia patients and controls. A
                      repeated cross-validation procedure was realized within the
                      patient group to identify clusters whose rsFC patterns to
                      the seeds were repeatedly observed as significantly
                      associated with specific FTD dimensions. These repeatedly
                      identified clusters (i.e., robust clusters) were
                      functionally characterized and the rsFC patterns were used
                      for predictive modeling to investigate predictive capacities
                      for individual FTD dimensional-scores. Compared with
                      controls, differential rsFC was found in patients in
                      fronto-temporo-thalamic regions. Our cross-validation
                      procedure revealed significant clusters only when assessing
                      the seed-to-whole-brain rsFC patterns associated with
                      positive-FTD. RsFC patterns of three fronto-temporal
                      clusters, associated with higher-order cognitive processes
                      (e.g., executive functions), specifically predicted
                      individual positive-FTD scores (p = 0.005), but not other
                      positive symptoms, and the PANSS general psychopathology
                      subscale (p > 0.05). The prediction of positive-FTD was
                      moreover generalized to an independent dataset (p = 0.013).
                      Our study has identified neurobiological correlates of
                      positive FTD in schizophrenia in a network associated with
                      higher-order cognitive functions, suggesting a dysexecutive
                      contribution to FTD in schizophrenia. We regard our findings
                      as robust, as they allow a prediction of individual-level
                      symptom severity.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5252 - Brain Dysfunction and Plasticity (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5252},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {34215141},
      UT           = {WOS:000670324000006},
      doi          = {10.1016/j.nicl.2021.102666},
      url          = {https://juser.fz-juelich.de/record/893853},
}