Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses

被引:27
作者
Poline, JB
Strother, SC
Dehaene-Lambertz, G
Egan, GF
Lancaster, JL
机构
[1] CEA, DRM, SHFJ, DSV,INSERM,U562, F-91406 Orsay, France
[2] UNAF, Serv Hosp Frederic Joliot, CEA, Orsay, France
[3] Baycrest Ctr Geriatr Care, Rotman Res Inst, Toronto, ON, Canada
[4] Univ Melbourne, Howard Florey Inst, Parkville, Vic 3052, Australia
[5] Univ Melbourne, Ctr Neurosci, Parkville, Vic 3052, Australia
[6] Univ Texas, Hlth Sci Ctr, Res Imaging Ctr, San Antonio, TX USA
关键词
D O I
10.1002/hbm.20268
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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 neuro-scientists 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.
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页码:351 / 359
页数:9
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