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@ARTICLE{Larivire:1005610,
      author       = {Larivière, Sara and Bayrak, Şeyma and Vos de Wael,
                      Reinder and Benkarim, Oualid and Herholz, Peer and
                      Rodriguez-Cruces, Raul and Paquola, Casey and Hong, Seok-Jun
                      and Misic, Bratislav and Evans, Alan C. and Valk, Sofie L.
                      and Bernhardt, Boris C.},
      title        = {{B}rain{S}tat: {A} toolbox for brain-wide statistics and
                      multimodal feature associations},
      journal      = {NeuroImage},
      volume       = {266},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {FZJ-2023-01560},
      pages        = {119807 -},
      year         = {2023},
      abstract     = {Analysis and interpretation of neuroimaging datasets has
                      become a multidisciplinary endeavor, relying not only on
                      statistical methods, but increasingly on associations with
                      respect to other brain-derived features such as gene
                      expression, histological data, and functional as well as
                      cognitive architectures. Here, we introduce BrainStat - a
                      toolbox for (i) univariate and multivariate linear models in
                      volumetric and surface-based brain imaging datasets, and
                      (ii) multidomain feature association of results with respect
                      to spatial maps of post-mortem gene expression and
                      histology, task-based fMRI meta-analysis, as well as
                      resting-state fMRI motifs across several common surface
                      templates. The combination of statistics and feature
                      associations into a turnkey toolbox streamlines analytical
                      processes and accelerates cross-modal research. The toolbox
                      is implemented in both Python and MATLAB, two widely used
                      programming languages in the neuroimaging and
                      neuroinformatics communities. BrainStat is openly available
                      and complemented by an expandable documentation.},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      5251 - Multilevel Brain Organization and Variability
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {36513290},
      UT           = {WOS:000961144700001},
      doi          = {10.1016/j.neuroimage.2022.119807},
      url          = {https://juser.fz-juelich.de/record/1005610},
}