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

Jean Baptiste Poline, Stephen C. Strother, Ghislaine Dehaene-Lambertz, Gary F. Egan, Jack L Lancaster

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)351-359
Number of pages9
JournalHuman Brain Mapping
Volume27
Issue number5
DOIs
StatePublished - May 2006

Fingerprint

Motivation
Magnetic Resonance Imaging
Linear Models
Brain Mapping
Language Tests
Language
Software
Multivariate Analysis
Education

ASJC Scopus subject areas

  • Clinical Neurology
  • Neuroscience(all)
  • Radiological and Ultrasound Technology

Cite this

Poline, J. B., Strother, S. C., Dehaene-Lambertz, G., Egan, G. F., & Lancaster, J. L. (2006). Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses. Human Brain Mapping, 27(5), 351-359. https://doi.org/10.1002/hbm.20268

Motivation and synthesis of the FIAC experiment : Reproducibility of fMRI results across expert analyses. / Poline, Jean Baptiste; Strother, Stephen C.; Dehaene-Lambertz, Ghislaine; Egan, Gary F.; Lancaster, Jack L.

In: Human Brain Mapping, Vol. 27, No. 5, 05.2006, p. 351-359.

Research output: Contribution to journalArticle

Poline, JB, Strother, SC, Dehaene-Lambertz, G, Egan, GF & Lancaster, JL 2006, 'Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses', Human Brain Mapping, vol. 27, no. 5, pp. 351-359. https://doi.org/10.1002/hbm.20268
Poline, Jean Baptiste ; Strother, Stephen C. ; Dehaene-Lambertz, Ghislaine ; Egan, Gary F. ; Lancaster, Jack L. / Motivation and synthesis of the FIAC experiment : Reproducibility of fMRI results across expert analyses. In: Human Brain Mapping. 2006 ; Vol. 27, No. 5. pp. 351-359.
@article{b4870950ba134cbbb938c40f31d5c20b,
title = "Motivation and synthesis of the FIAC experiment: Reproducibility of fMRI results across expert analyses",
abstract = "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.",
author = "Poline, {Jean Baptiste} and Strother, {Stephen C.} and Ghislaine Dehaene-Lambertz and Egan, {Gary F.} and Lancaster, {Jack L}",
year = "2006",
month = "5",
doi = "10.1002/hbm.20268",
language = "English (US)",
volume = "27",
pages = "351--359",
journal = "Human Brain Mapping",
issn = "1065-9471",
publisher = "Wiley-Liss Inc.",
number = "5",

}

TY - JOUR

T1 - Motivation and synthesis of the FIAC experiment

T2 - Reproducibility of fMRI results across expert analyses

AU - Poline, Jean Baptiste

AU - Strother, Stephen C.

AU - Dehaene-Lambertz, Ghislaine

AU - Egan, Gary F.

AU - Lancaster, Jack L

PY - 2006/5

Y1 - 2006/5

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33646861200&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646861200&partnerID=8YFLogxK

U2 - 10.1002/hbm.20268

DO - 10.1002/hbm.20268

M3 - Article

C2 - 16583364

AN - SCOPUS:33646861200

VL - 27

SP - 351

EP - 359

JO - Human Brain Mapping

JF - Human Brain Mapping

SN - 1065-9471

IS - 5

ER -