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@ARTICLE{Paquola:897099,
      author       = {Paquola, Casey and Royer, Jessica and Lewis, Lindsay B and
                      Lepage, Claude and Glatard, Tristan and Wagstyl, Konrad and
                      DeKraker, Jordan and Toussaint, Paule-J and Valk, Sofie L
                      and Collins, Louis and Khan, Ali R and Amunts, Katrin and
                      Evans, Alan C and Dickscheid, Timo and Bernhardt, Boris},
      title        = {{T}he {B}ig{B}rain{W}arp toolbox for integration of
                      {B}ig{B}rain 3{D} histology with multimodal neuroimaging},
      journal      = {eLife},
      volume       = {10},
      issn         = {2050-084X},
      address      = {Cambridge},
      publisher    = {eLife Sciences Publications},
      reportid     = {FZJ-2021-03598},
      pages        = {e70119},
      year         = {2021},
      abstract     = {Neuroimaging stands to benefit from emerging
                      ultrahigh-resolution 3D histological atlases of the human
                      brain; the first of which is ‘BigBrain’. Here, we review
                      recent methodological advances for the integration of
                      BigBrain with multi-modal neuroimaging and introduce a
                      toolbox, ’BigBrainWarp’, that combines these
                      developments. The aim of BigBrainWarp is to simplify
                      workflows and support the adoption of best practices. This
                      is accomplished with a simple wrapper function that allows
                      users to easily map data between BigBrain and standard MRI
                      spaces. The function automatically pulls specialised
                      transformation procedures, based on ongoing research from a
                      wide collaborative network of researchers. Additionally, the
                      toolbox improves accessibility of histological information
                      through dissemination of ready-to-use cytoarchitectural
                      features. Finally, we demonstrate the utility of
                      BigBrainWarp with three tutorials and discuss the potential
                      of the toolbox to support multi-scale investigations of
                      brain organisation.},
      cin          = {INM-1},
      ddc          = {600},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {5254 - Neuroscientific Data Analytics and AI (POF4-525) /
                      HIBALL - Helmholtz International BigBrain Analytics and
                      Learning Laboratory (HIBALL) (InterLabs-0015)},
      pid          = {G:(DE-HGF)POF4-5254 / G:(DE-HGF)InterLabs-0015},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:34431476},
      UT           = {WOS:000697792200001},
      doi          = {10.7554/eLife.70119},
      url          = {https://juser.fz-juelich.de/record/897099},
}