http://www.nitrc.org/forum/forum.php?forum_id=2810 <table border="0" width="100%"><tr><td align="left"/></tr></table> <p><b>Very large fMRI study using the IMAGEN database: Sensitivity-specificity and population effect modeling in relation to the underlying anatomy.</b></p> <p>Neuroimage. 2012 Mar 10;</p> <p>Authors: Thyreau B, Schwartz Y, Thirion B, Frouin V, Loth E, Vollstädt-Klein S, Paus T, Artiges E, Conrod PJ, Schumann G, Whelan R, Poline JB</p> <p>Abstract<br/> 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.<br/> </p><p>PMID: 22425669 [PubMed - as supplied by publisher]</p> en-us Copyright 2000-2026 NITRC OSI Sun, 26 Apr 2026 18:08:46 GMT http://blogs.law.harvard.edu/tech/rss NITRC RSS generator