Revealing representational content with pattern-information fMRI--an introductory guide

Soc Cogn Affect Neurosci. 2009 Mar;4(1):101-9. doi: 10.1093/scan/nsn044. Epub 2009 Jan 17.


Conventional statistical analysis methods for functional magnetic resonance imaging (fMRI) data are very successful at detecting brain regions that are activated as a whole during specific mental activities. The overall activation of a region is usually taken to indicate involvement of the region in the task. However, such activation analysis does not consider the multivoxel patterns of activity within a brain region. These patterns of activity, which are thought to reflect neuronal population codes, can be investigated by pattern-information analysis. In this framework, a region's multivariate pattern information is taken to indicate representational content. This tutorial introduction motivates pattern-information analysis, explains its underlying assumptions, introduces the most widespread methods in an intuitive way, and outlines the basic sequence of analysis steps.

Publication types

  • Research Support, N.I.H., Intramural
  • Review

MeSH terms

  • Brain / physiology*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / statistics & numerical data
  • Mental Processes / physiology
  • Pattern Recognition, Automated
  • Research Design