Cross-modal searchlight classification: Methodological challenges and recommended solutions

Samuel A. Nastase, Yaroslav O. Halchenko, Ben Davis, Uri Hasson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Multivariate cross-classification is a powerful tool for decoding abstract or supramodal representations from distributed neural populations. However, this approach introduces several methodological challenges not encountered in typical multivariate pattern analysis and information-based brain mapping. In the current report, we review these challenges, recommend solutions, and evaluate alternative approaches where possible. We address these challenges with reference to an example fMRI data set where participants were presented with brief series of auditory and visual stimuli of varying predictability with the aim of decoding predictability across auditory and visual modalities. In analyzing this data set, we highlight four particular challenges: response normalization, cross-validation, direction of cross-validation, and permutation testing.

Original languageEnglish (US)
Title of host publicationPRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467365307
DOIs
StatePublished - Aug 24 2016
Externally publishedYes
Event6th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2016 - Trento, Italy
Duration: Jun 22 2016Jun 24 2016

Publication series

NamePRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging

Other

Other6th International Workshop on Pattern Recognition in Neuroimaging, PRNI 2016
CountryItaly
CityTrento
Period6/22/166/24/16

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Biomedical Engineering

Keywords

  • MVPA
  • cross-classification
  • cross-modal
  • fMRI

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  • Cite this

    Nastase, S. A., Halchenko, Y. O., Davis, B., & Hasson, U. (2016). Cross-modal searchlight classification: Methodological challenges and recommended solutions. In PRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging [7552355] (PRNI 2016 - 6th International Workshop on Pattern Recognition in Neuroimaging). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRNI.2016.7552355