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@ARTICLE{Schaefer:840190,
      author       = {Schaefer, Alexander and Kong, Ru and Gordon, Evan M. and
                      Laumann, Timothy O. and Zuo, Xi-Nian and Holmes, Avram J.
                      and Eickhoff, Simon and Yeo, B. T. Thomas},
      title        = {{L}ocal-{G}lobal {P}arcellation of the {H}uman {C}erebral
                      {C}ortex from {I}ntrinsic {F}unctional {C}onnectivity {MRI}},
      journal      = {Cerebral cortex},
      volume       = {},
      issn         = {1460-2199},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {FZJ-2017-07745},
      pages        = {1-20},
      year         = {2017},
      abstract     = {A central goal in systems neuroscience is the parcellation
                      of the cerebral cortex into discrete neurobiological
                      "atoms". Resting-state functional magnetic resonance imaging
                      (rs-fMRI) offers the possibility of in vivo human cortical
                      parcellation. Almost all previous parcellations relied on 1
                      of 2 approaches. The local gradient approach detects abrupt
                      transitions in functional connectivity patterns. These
                      transitions potentially reflect cortical areal boundaries
                      defined by histology or visuotopic fMRI. By contrast, the
                      global similarity approach clusters similar functional
                      connectivity patterns regardless of spatial proximity,
                      resulting in parcels with homogeneous (similar) rs-fMRI
                      signals. Here, we propose a gradient-weighted Markov Random
                      Field (gwMRF) model integrating local gradient and global
                      similarity approaches. Using task-fMRI and rs-fMRI across
                      diverse acquisition protocols, we found gwMRF parcellations
                      to be more homogeneous than 4 previously published
                      parcellations. Furthermore, gwMRF parcellations agreed with
                      the boundaries of certain cortical areas defined using
                      histology and visuotopic fMRI. Some parcels captured
                      subareal (somatotopic and visuotopic) features that likely
                      reflect distinct computational units within known cortical
                      areas. These results suggest that gwMRF parcellations reveal
                      neurobiologically meaningful features of brain organization
                      and are potentially useful for future applications requiring
                      dimensionality reduction of voxel-wise fMRI data.
                      Multiresolution parcellations generated from 1489
                      participants are publicly available},
      cin          = {INM-7},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-7-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571)},
      pid          = {G:(DE-HGF)POF3-571},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:28981612},
      UT           = {WOS:000443545600003},
      doi          = {10.1093/cercor/bhx179},
      url          = {https://juser.fz-juelich.de/record/840190},
}