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@ARTICLE{Eickhoff:15399,
      author       = {Eickhoff, S.B. and Bzdok, D. and Laird, A.R. and Roski, C.
                      and Caspers, S. and Zilles, K. and Fox, P.T.},
      title        = {{C}o-activation patterns distinguish cortical modules,
                      their connectivity and functional differentiation},
      journal      = {NeuroImage},
      volume       = {57},
      issn         = {1053-8119},
      address      = {Orlando, Fla.},
      publisher    = {Academic Press},
      reportid     = {PreJuSER-15399},
      pages        = {938 - 949},
      year         = {2011},
      note         = {This work was partly funded by the Human Brain Project
                      (R01-MH074457-01A1; S.B.E., A.R.L., and P.T.F), the
                      Initiative and Networking Fund of the Helmholtz Association
                      within the Helmholtz Alliance on Systems Biology (Human
                      Brain Model; K.Z., S.B.E.), the DFG (IRTG 1328, S.B.E.,
                      D.B.) and the Helmholtz Alliance for Mental Health in an
                      Aging Society (HelMA; K.Z.).},
      abstract     = {The organization of the cerebral cortex into distinct
                      modules may be described along several dimensions, most
                      importantly, structure, connectivity and function.
                      Identification of cortical modules by differences in
                      whole-brain connectivity profiles derived from diffusion
                      tensor imaging or resting state correlations has already
                      been shown. These approaches, however, carry no task-related
                      information. Hence, inference on the functional relevance of
                      the ensuing parcellation remains tentative. Here, we
                      demonstrate, that Meta-Analytic Connectivity Modeling (MACM)
                      allows the delineation of cortical modules based on their
                      whole-brain co-activation pattern across databased
                      neuroimaging results. Using a model free approach, two
                      regions of the medial pre-motor cortex, SMA and pre-SMA were
                      differentiated solely based on their functional
                      connectivity. Assessing the behavioral domain and paradigm
                      class meta-data of the experiments associated with the
                      clusters derived from the co-activation based parcellation
                      moreover allows the identification of their functional
                      characteristics. The ensuing hypotheses about functional
                      differentiation and distinct functional connectivity between
                      pre-SMA and SMA were then explicitly tested and confirmed in
                      independent datasets using functional and resting state
                      fMRI. Co-activation based parcellation thus provides a new
                      perspective for identifying modules of functional
                      connectivity and linking them to functional properties,
                      hereby generating new and subsequently testable hypotheses
                      about the organization of cortical modules.},
      keywords     = {Algorithms / Brain: anatomy $\&$ histology / Brain:
                      physiology / Brain Mapping: methods / Cluster Analysis /
                      Humans / Image Processing, Computer-Assisted: methods /
                      Magnetic Resonance Imaging / Neural Pathways: anatomy $\&$
                      histology / Neural Pathways: physiology / J (WoSType)},
      cin          = {INM-2},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-2-20090406},
      pnm          = {Funktion und Dysfunktion des Nervensystems (FUEK409) /
                      89571 - Connectivity and Activity (POF2-89571)},
      pid          = {G:(DE-Juel1)FUEK409 / G:(DE-HGF)POF2-89571},
      shelfmark    = {Neurosciences / Neuroimaging / Radiology, Nuclear Medicine
                      $\&$ Medical Imaging},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:21609770},
      pmc          = {pmc:PMC3129435},
      UT           = {WOS:000292717900028},
      doi          = {10.1016/j.neuroimage.2011.05.021},
      url          = {https://juser.fz-juelich.de/record/15399},
}