• DocumentCode
    3652767
  • Title

    A validation of a multi-spatialscale method for multivariate pattern analysis

  • Author

    Jessica Bulthe;Job van den Hurk;Nicky Daniels;Bert De Smedt;Hans P. Op de Beeck

  • Author_Institution
    Lab. of Biol. Psycholology, KU Leuven, Leuven, Belgium
  • fYear
    2014
  • fDate
    6/1/2014 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Most fMRI studies using Multi-Voxel Pattern Analysis (MVPA) restrict these analyses to merely one spatial scale. However, recently [1] used a multi-spatial scale method combining three levels of MVPA analysis on fMRI data from 16 subjects who performed a number comparison task: whole-brain MVPA, Regions Of Interest (ROI) based MVPA, and a small radius searchlight. The results of [1] clearly demonstrated the necessity of incorporating different spatial scales in MVPA analysis to draw conclusions on how the neural representations of the effects are distributed across the brain. We tested the validity of the method used in this empirical study by using three simulated fMRI datasets. Both simulated data and the real data [1] confirmed the relevance of analyzing data with MVPA on different spatial scales.
  • Keywords
    "Accuracy","Decoding","Pattern analysis","Biology","Noise","Kernel","Support vector machines"
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition in Neuroimaging, 2014 International Workshop on
  • Type

    conf

  • DOI
    10.1109/PRNI.2014.6858513
  • Filename
    6858513