Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses

Neuroimage. 2007 Mar;35(1):105-20. doi: 10.1016/j.neuroimage.2006.11.054. Epub 2007 Jan 18.


The aim of group fMRI studies is to relate contrasts of tasks or stimuli to regional brain activity increases. These studies typically involve 10 to 16 subjects. The average regional activity statistical significance is assessed using the subject to subject variability of the effect (random effects analyses). Because of the relatively small number of subjects included, the sensitivity and reliability of these analyses is questionable and hard to investigate. In this work, we use a very large number of subject (more than 80) to investigate this issue. We take advantage of this large cohort to study the statistical properties of the inter-subject activity and focus on the notion of reproducibility by bootstrapping. We asked simple but important methodological questions: Is there, from the point of view of reliability, an optimal statistical threshold for activity maps? How many subjects should be included in group studies? What method should be preferred for inference? Our results suggest that i) optimal thresholds can indeed be found, and are rather lower than usual corrected for multiple comparison thresholds, ii) 20 subjects or more should be included in functional neuroimaging studies in order to have sufficient reliability, iii) non-parametric significance assessment should be preferred to parametric methods, iv) cluster-level thresholding is more reliable than voxel-based thresholding, and v) mixed effects tests are much more reliable than random effects tests. Moreover, our study shows that inter-subject variability plays a prominent role in the relatively low sensitivity and reliability of group studies.

MeSH terms

  • Algorithms
  • Brain Mapping
  • Cluster Analysis
  • Cohort Studies
  • Databases, Factual
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Image Processing, Computer-Assisted / statistics & numerical data*
  • Magnetic Resonance Imaging / methods*
  • Magnetic Resonance Imaging / statistics & numerical data*
  • Models, Neurological
  • Models, Statistical
  • Reproducibility of Results
  • Sample Size