Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses
Article first published online: 31 MAR 2006
Copyright © 2006 Wiley-Liss, Inc.
Human Brain Mapping
Volume 27, Issue 5, pages 351–359, May 2006
How to Cite
Poline, J.-B., Strother, S. C., Dehaene-Lambertz, G., Egan, G. F. and Lancaster, J. L. (2006), Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses. Hum. Brain Mapp., 27: 351–359. doi: 10.1002/hbm.20268
- Issue published online: 13 APR 2006
- Article first published online: 31 MAR 2006
- IFR49 (http://www.ifr49.org), with special thanks to I. Denghien and N. Terrien (IFR49), S. Dodel (IFR49 and Madic), the other members of Madic and the UNAF laboratory in Orsay
The Functional Imaging Analysis Contest (FIAC) culminated in the FIAC Workshop held at the 11th Annual Meeting of the Organization for Human Brain Mapping in Toronto in 2005. This special issue summarizes various analyses used by contestants with a single functional magnetic resonance imaging (fMRI) study, a cortical-language study using sentence repetition. The results from the cognitive neuroscientists who developed the test-base language study, and report their data analysis, are complemented by expert analyses of the same test-base data by most of the major groups actively developing fMRI software packages. Analyses include many variants of the general linear model (GLM), cutting-edge spatial- and temporal-wavelets, permutation-based, and ICA approaches. A number of authors also include surface-based approaches. Several articles describe the important emerging areas of diagnostics for GLM analysis, multivariate predictive modeling, and functional connectivity analysis. While the FIAC did not achieve all of its goals, it helped identify new activation regions in the test-base data, and more important, through this special issue it illustrates the significant methods-driven variability that potentially exists in the literature. Variable results from different methods reported here should provide a cautionary note and motivate the Human Brain Mapping community to explore more thoroughly the methodologies they use for analyzing fMRI data. Hum Brain Mapp 27:351–359, 2006. © 2006 Wiley-Liss, Inc.