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@ARTICLE{Laird:15664,
      author       = {Laird, A.R. and Fox, P.M. and Eickhoff, S.B. and Turner,
                      J.A. and Ray, K.L. and McKay, D.R. and Glahn, D.C. and
                      Beckmann, C.F. and Smith, S.M. and Fox, P.T.},
      title        = {{B}ehavioral {I}nterpretations of {I}ntrinsic
                      {C}onnectivity {N}etworks},
      journal      = {Journal of cognitive neuroscience},
      volume       = {23},
      issn         = {0898-929X},
      address      = {Cambridge, Mass.},
      publisher    = {MIT Pr. Journals},
      reportid     = {PreJuSER-15664},
      pages        = {4022 - 4037},
      year         = {2011},
      note         = {This work was supported by NIMH grants R01-MH074457 (P. T.
                      F. and A. R. L.) and R01-MH084812 (A. R. L. and J. A. T.)
                      and the Helmholz Initiative on Systems-Biology (S. B. E.).},
      abstract     = {An increasingly large number of neuroimaging studies have
                      investigated functionally connected networks during rest,
                      providing insight into human brain architecture. Assessment
                      of the functional qualities of resting state networks has
                      been limited by the task-independent state, which results in
                      an inability to relate these networks to specific mental
                      functions. However, it was recently demonstrated that
                      similar brain networks can be extracted from resting state
                      data and data extracted from thousands of task-based
                      neuroimaging experiments archived in the BrainMap database.
                      Here, we present a full functional explication of these
                      intrinsic connectivity networks at a standard low order
                      decomposition using a neuroinformatics approach based on the
                      BrainMap behavioral taxonomy as well as a stratified,
                      data-driven ordering of cognitive processes. Our results
                      serve as a resource for functional interpretations of brain
                      networks in resting state studies and future investigations
                      into mental operations and the tasks that drive them.},
      keywords     = {Brain: physiology / Brain Mapping: methods /
                      Classification: methods / Cluster Analysis / Databases,
                      Factual / Humans / Nerve Net: physiology / Neural Pathways:
                      physiology / Psychomotor Performance: physiology / J
                      (WoSType)},
      cin          = {INM-2},
      ddc          = {400},
      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 / Psychology, Experimental},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:21671731},
      UT           = {WOS:000296758500028},
      doi          = {10.1162/jocn_a_00077},
      url          = {https://juser.fz-juelich.de/record/15664},
}