The danger of systematic bias in group-level FMRI-lag-based causality estimation

Neuroimage. 2012 Jan 16;59(2):1228-9. doi: 10.1016/j.neuroimage.2011.08.015. Epub 2011 Aug 16.


Schippers, Renken and Keysers (NeuroImage, 2011) present a simulation of multi-subject lag-based causality estimation. We fully agree that single-subject evaluations (e.g., Smith et al., 2011) need to be revisited in the context of multi-subject studies, and Schippers' paper is a good example, including detailed multi-level simulation and cross-subject statistical modelling. The authors conclude that "the average chance to find a significant Granger causality effect when no actual influence is present in the data stays well below the p-level imposed on the second level statistics" and that "when the analyses reveal a significant directed influence, this direction was accurate in the vast majority of the cases". Unfortunately, we believe that the general meaning that may be taken from these statements is not supported by the paper's results, as there may in reality be a systematic (group-average) difference in haemodynamic delay between two brain areas. While many statements in the paper (e.g., the final two sentences) do refer to this problem, we fear that the overriding message that many readers may take from the paper could cause misunderstanding.

Publication types

  • Comment

MeSH terms

  • Animals
  • Brain / physiology*
  • Brain Mapping / methods*
  • Hemodynamics / physiology*
  • Image Processing, Computer-Assisted / methods*
  • Magnetic Resonance Imaging*