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@ARTICLE{Rehme:203085,
      author       = {Rehme, Anne and Volz, L. and Feis, D. L. and Eickhoff,
                      Simon and Fink, Gereon Rudolf and Grefkes, Christian},
      title        = {{I}ndividual prediction of chronic motor outcome in the
                      acute post-stroke stage: {B}ehavioral parameters versus
                      functional imaging},
      journal      = {Human brain mapping},
      volume       = {36},
      number       = {11},
      issn         = {1065-9471},
      address      = {New York, NY},
      publisher    = {Wiley-Liss},
      reportid     = {FZJ-2015-05120},
      pages        = {4553-4565},
      year         = {2015},
      abstract     = {Several neurobiological factors have been found to
                      correlate with functional recovery after brain lesions.
                      However, predicting the individual potential of recovery
                      remains difficult. Here we used multivariate support vector
                      machine (SVM) classification to explore the prognostic value
                      of functional magnetic resonance imaging (fMRI) to predict
                      individual motor outcome at 4–6 months post-stroke. To
                      this end, 21 first-ever stroke patients with hand motor
                      deficits participated in an fMRI hand motor task in the
                      first few days post-stroke. Motor impairment was quantified
                      assessing grip force and the Action Research Arm Test.
                      Linear SVM classifiers were trained to predict good versus
                      poor motor outcome of unseen new patients. We found that
                      fMRI activity acquired in the first week post-stroke
                      correctly predicted the outcome for $86\%$ of all patients.
                      In contrast, the concurrent assessment of motor function
                      provided $76\%$ accuracy with low sensitivity $(<60\%).$
                      Furthermore, the outcome of patients with initially moderate
                      impairment and high outcome variability could not be
                      predicted based on motor tests. In contrast, fMRI provided
                      $87.5\%$ prediction accuracy in these patients.
                      Classifications were driven by activity in ipsilesional
                      motor areas and contralesional cerebellum. The accuracy of
                      subacute fMRI data (two weeks post-stroke), age, time
                      post-stroke, lesion volume, and location were at
                      $50\%-chance-level.$ In conclusion, multivariate decoding of
                      fMRI data with SVM early after stroke enables a robust
                      prediction of motor recovery. The potential for recovery is
                      influenced by the initial dysfunction of the active motor
                      system, particularly in those patients whose outcome cannot
                      be predicted by behavioral tests.},
      cin          = {INM-3 / INM-1},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-3-20090406 / I:(DE-Juel1)INM-1-20090406},
      pnm          = {572 - (Dys-)function and Plasticity (POF3-572) / 573 -
                      Neuroimaging (POF3-573) / HBP - The Human Brain Project
                      (604102)},
      pid          = {G:(DE-HGF)POF3-572 / G:(DE-HGF)POF3-573 /
                      G:(EU-Grant)604102},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000364219500023},
      pubmed       = {pmid:26381168},
      doi          = {10.1002/hbm.22936},
      url          = {https://juser.fz-juelich.de/record/203085},
}