• DocumentCode
    3584106
  • Title

    MVPA Permutation Schemes: Permutation Testing for the Group Level

  • Author

    Etzel, Joset A.

  • fYear
    2015
  • Firstpage
    65
  • Lastpage
    68
  • Abstract
    Permutation tests are widely used for significance testing in fMRI MVPA (multivariate pattern analysis) studies, but the precise way in which the tests are carried out varies, and test design is non-trivial because of complex, auto correlated, and stratified dataset structures. Previously, we described permutation tests for single-subject datasets, recommending adoption of "dataset-wise" schemes, in which examples are relabeled prior to cross-validation. Here, we extend that work by describing permutation schemes for group analyses: datasets with more than one participant. Group-level MVPA is most often performed with either cross-validation on the subjects or within-subjects cross-validation, each of which requires a different strategy for permutation testing, as illustrated here.
  • Keywords
    Accuracy; Conferences; Neuroimaging; Pattern analysis; Pattern recognition; Support vector machines; Testing; MVPA; classification; cross-validation; fMRI; permutation; significance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition in NeuroImaging (PRNI), 2015 International Workshop on
  • Type

    conf

  • DOI
    10.1109/PRNI.2015.29
  • Filename
    7270849