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@ARTICLE{Steinkamp:906255,
      author       = {Steinkamp, Simon R. and Fink, Gereon R. and Vossel, Simone
                      and Weidner, Ralph},
      title        = {{S}imultaneous modeling of reaction times and brain
                      dynamics in a spatial cueing task},
      journal      = {Human brain mapping},
      volume       = {43},
      number       = {6},
      issn         = {1065-9471},
      address      = {New York, NY},
      publisher    = {Wiley-Liss},
      reportid     = {FZJ-2022-01326},
      pages        = {hbm.25758},
      year         = {2022},
      abstract     = {Understanding how brain activity translates into behavior
                      is a grand challenge in neuroscientific research.
                      Simultaneous computational modeling of both measures offers
                      to address this question. The extension of the dynamic
                      causal modeling (DCM) framework for blood oxygenation
                      level-dependent (BOLD) responses to behavior (bDCM)
                      constitutes such a modeling approach. However, only very few
                      studies have employed and evaluated bDCM, and its
                      application has been restricted to binary behavioral
                      responses, limiting more general statements about its
                      validity. This study used bDCM to model reaction times in a
                      spatial attention task, which involved two separate runs
                      with either horizontal or vertical stimulus configurations.
                      We recorded fMRI data and reaction times (n= 26) and
                      compared bDCM with classical DCM and a behavioral
                      Rescorla–Wagner model using Bayesian model selection and
                      goodness of fit statistics. Results indicate that bDCM
                      performed equally well as classical DCM when modeling BOLD
                      responses and as good as the Rescorla–Wagner model when
                      modeling reaction times. Although our data revealed
                      practical limitations of the current bDCM approach that
                      warrant further investigation, we conclude that bDCM
                      constitutes a promising method for investigating the link
                      between brain activity and behavior.},
      cin          = {INM-3},
      ddc          = {610},
      cid          = {I:(DE-Juel1)INM-3-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525)},
      pid          = {G:(DE-HGF)POF4-5251},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {34953009},
      UT           = {WOS:000733987000001},
      doi          = {10.1002/hbm.25758},
      url          = {https://juser.fz-juelich.de/record/906255},
}