TY - JOUR
T1 - Very large fMRI study using the IMAGEN database
T2 - Sensitivity-specificity and population effect modeling in relation to the underlying anatomy
AU - Thyreau, Benjamin
AU - Schwartz, Yannick
AU - Thirion, Bertrand
AU - Frouin, Vincent
AU - Loth, Eva
AU - Vollstädt-Klein, Sabine
AU - Paus, Tomas
AU - Artiges, Eric
AU - Conrod, Patricia J.
AU - Schumann, Gunter
AU - Whelan, Robert
AU - Poline, Jean Baptiste
N1 - Funding Information:
Support was provided by the IMAGEN project , which receives research funding from the European Community's Sixth Framework Programme ( LSHM-CT-2007-037286 ). The funding sources had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.
PY - 2012/5/15
Y1 - 2012/5/15
N2 - In this paper we investigate the use of classical fMRI Random Effect (RFX) group statistics when analyzing a very large cohort and the possible improvement brought from anatomical information. Using 1326 subjects from the IMAGEN study, we first give a global picture of the evolution of the group effect t-value from a simple face-watching contrast with increasing cohort size. We obtain a wide activated pattern, far from being limited to the reasonably expected brain areas, illustrating the difference between statistical significance and practical significance. This motivates us to inject tissue-probability information into the group estimation, we model the BOLD contrast using a matter-weighted mixture of Gaussians and compare it to the common, single-Gaussian model. In both cases, the model parameters are estimated per-voxel for one subgroup, and the likelihood of both models is computed on a second, separate subgroup to reflect model generalization capacity. Various group sizes are tested, and significance is asserted using a 10-fold cross-validation scheme. We conclude that adding matter information consistently improves the quantitative analysis of BOLD responses in some areas of the brain, particularly those where accurate inter-subject registration remains challenging.
AB - In this paper we investigate the use of classical fMRI Random Effect (RFX) group statistics when analyzing a very large cohort and the possible improvement brought from anatomical information. Using 1326 subjects from the IMAGEN study, we first give a global picture of the evolution of the group effect t-value from a simple face-watching contrast with increasing cohort size. We obtain a wide activated pattern, far from being limited to the reasonably expected brain areas, illustrating the difference between statistical significance and practical significance. This motivates us to inject tissue-probability information into the group estimation, we model the BOLD contrast using a matter-weighted mixture of Gaussians and compare it to the common, single-Gaussian model. In both cases, the model parameters are estimated per-voxel for one subgroup, and the likelihood of both models is computed on a second, separate subgroup to reflect model generalization capacity. Various group sizes are tested, and significance is asserted using a 10-fold cross-validation scheme. We conclude that adding matter information consistently improves the quantitative analysis of BOLD responses in some areas of the brain, particularly those where accurate inter-subject registration remains challenging.
KW - Brain mapping: methods
KW - Databasing
KW - Likelihood functions
KW - Linear models
KW - Magnetic resonance imaging
KW - Sensitivity and specificity
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U2 - 10.1016/j.neuroimage.2012.02.083
DO - 10.1016/j.neuroimage.2012.02.083
M3 - Article
C2 - 22425669
AN - SCOPUS:84859098408
VL - 61
SP - 295
EP - 303
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
IS - 1
ER -