Mixed-effects and fMRI studies

K J Friston, K E Stephan, T E Lund, A Morcom, S Kiebel

Research output: Contribution to journalArticlepeer-review

Abstract

This note concerns mixed-effect (MFX) analyses in multisession functional magnetic resonance imaging (fMRI) studies. It clarifies the relationship between mixed-effect analyses and the two-stage "summary statistics" procedure (Holmes, A.P., Friston, K.J., 1998. Generalisability, random effects and population inference. NeuroImage 7, S754) that has been adopted widely for analyses of fMRI data at the group level. We describe a simple procedure, based on restricted maximum likelihood (ReML) estimates of covariance components, that enables full mixed-effects analyses in the context of statistical parametric mapping. Using this procedure, we compare the results of a full mixed-effects analysis with those obtained from the simpler two-stage procedure and comment on the situations when the two approaches may give different results. (C) 2004 Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)244-252
Number of pages9
JournalNeuroImage
Volume24
Issue number1
DOIs
Publication statusPublished - 1 Jan 2005

Keywords

  • hierarchical observation models
  • mixed-effects analysis
  • random-effects analysis
  • inference
  • ReML
  • EM
  • MAXIMUM-LIKELIHOOD
  • BAYESIAN-INFERENCE
  • EM-ALGORITHM
  • VARIANCE
  • MODELS

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