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

M.C. Mur*, P.A. Bandettini, N. Kriegeskorte

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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 regions 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.
Original languageEnglish
Pages (from-to)101-109
JournalSocial Cognitive and Affective Neuroscience
Publication statusPublished - 1 Jan 2009

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