• DocumentCode
    183326
  • Title

    Data-driven multisubject neuroimaging analyses for naturalistic stimuli

  • Author

    Biessmann, Felix ; Gaebler, Michael ; Lamke, Jan-Peter ; Ui Jong Ju ; Hetzer, Stefan ; Wallraven, Christian ; Muller, Klaus-Robert

  • Author_Institution
    Amazon Dev. Center, Berlin, Germany
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A central question in neuroscience is how the brain reacts to real world sensory stimuli. Naturalistic and complex (e.g. movie) stimuli are increasingly used in empirical research but their analysis often relies on considerable human efforts to label or extract stimulus features. Here we present data-driven analysis strategies that help to obtain interpretable results from multisubject neuroimaging data when complex movie stimuli are used. These analyses a) enable localization and visualization of brain activity using standard statistical parametric maps in the subspace of brain activity shared between subjects and b) facilitate interpretation of intersubject correlations. We show experimental results obtained from 50 subjects.
  • Keywords
    biomedical MRI; brain; data analysis; feature extraction; medical image processing; neurophysiology; statistical analysis; brain activity localization; brain activity subspace; brain activity visualization; data-driven multisubject neuroimaging data analysis; empirical research; functional magnetic resonance imaging; intersubject correlations; naturalistic stimuli; neuroscience; real world sensory stimuli; standard statistical parametric maps; stimulus feature extraction; Brain; Correlation; Decoding; Motion pictures; Neuroimaging; Three-dimensional displays; Videos; CCA; Canonical Correlation Analysis; Hyperscanning; Intersubject Correlation; Multisubject Neuroimaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition in Neuroimaging, 2014 International Workshop on
  • Conference_Location
    Tubingen
  • Print_ISBN
    978-1-4799-4150-6
  • Type

    conf

  • DOI
    10.1109/PRNI.2014.6858511
  • Filename
    6858511