Multivariate methods for tracking cognitive states

Kenneth A. Norman, Joel R. Quamme, Ehren L. Newman

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter focuses on multi-voxel pattern analysis (MVPA), which involves applying pattern-classification algorithms to multi-voxel patterns of brain activity, and training these classifiers to detect the spatially distributed neural correlates of specific cognitive states. It begins with a general overview of the MVPA approach. It then shows how MVPA can be used to address theoretically meaningful questions about memory. Finally, it discusses these findings and points out some future directions of research.

Original languageEnglish (US)
Title of host publicationNeuroimaging of Human Memory
Subtitle of host publicationLinking Cognitive Processes to Neural Systems
PublisherOxford University Press
ISBN (Electronic)9780191696077
ISBN (Print)9780199217298
DOIs
StatePublished - Mar 22 2012

All Science Journal Classification (ASJC) codes

  • Psychology(all)

Keywords

  • Brain activity
  • MVPA
  • Memory
  • Multi-voxel pattern analysis
  • Pattern-classification algorithms

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  • Cite this

    Norman, K. A., Quamme, J. R., & Newman, E. L. (2012). Multivariate methods for tracking cognitive states. In Neuroimaging of Human Memory: Linking Cognitive Processes to Neural Systems Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199217298.003.0017