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@ARTICLE{Kuo:866006,
      author       = {Kuo, Po-Chih and Tseng, Yi-Li and Zilles, Karl and Suen,
                      Summit and Eickhoff, Simon B. and Lee, Juin-Der and Cheng,
                      Philip E. and Liou, Michelle},
      title        = {{L}istening to real-world sounds: f{MRI} data for analyzing
                      connectivity networks},
      journal      = {Data in Brief},
      volume       = {26},
      issn         = {2352-3409},
      address      = {Amsterdam [u.a.]},
      publisher    = {Elsevier},
      reportid     = {FZJ-2019-05266},
      pages        = {104411},
      year         = {2019},
      note         = {We are indebted to the Research Center for Mind, Brain $\&$
                      Learning at the National Chengchi University for the great
                      assistance during fMRI data acquisition. This research was
                      supported by grants MOST-105-2410-H-001-036 and
                      MOST-106-2410-H-001-026 from the Ministry of Science and
                      Technology, Taiwan, and by funding from the European
                      Union’s Horizon 2020 Research and Innovation Programme
                      under Grant Agreement No. 785907 (HBP SGA2).},
      abstract     = {There is a growing interest in functional magnetic
                      resonance imaging (fMRI) studies on connectivity networks in
                      the brain when subjects are under exposure to natural
                      sensory stimulation. Because of a complicated coupling
                      between spontaneous and evoked brain activity under
                      real-world stimulation, there is no critical mapping between
                      the experimental inputs and corresponding brain responses.
                      The dataset contains auditory fMRI scans and T1-weighted
                      anatomical scans acquired under eyes-closed and eyes-open
                      conditions. Within each scanning condition, the subject was
                      presented 12 different sound clips, including human voices
                      followed by animal vocalizations. The dataset is meant to be
                      used to assess brain dynamics and connectivity networks
                      under natural sound stimulation; it also allows for
                      empirical investigation of changes in fMRI responses between
                      eyes-closed and eyes-open conditions, between animal
                      vocalizations and human voices, as well as between the 12
                      different sound clips during auditory stimulation. The
                      dataset is a supplement to the research findings in the
                      paper “Brain dynamics and connectivity networks under
                      natural auditory stimulation” published in NeuroImage.},
      cin          = {INM-7 / INM-1},
      ddc          = {570},
      cid          = {I:(DE-Juel1)INM-7-20090406 / I:(DE-Juel1)INM-1-20090406},
      pnm          = {571 - Connectivity and Activity (POF3-571) / HBP SGA2 -
                      Human Brain Project Specific Grant Agreement 2 (785907)},
      pid          = {G:(DE-HGF)POF3-571 / G:(EU-Grant)785907},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:31646154},
      UT           = {WOS:000495079400133},
      doi          = {10.1016/j.dib.2019.104411},
      url          = {https://juser.fz-juelich.de/record/866006},
}