Group-wise FMRI activation detection on corresponding cortical landmarks

Abstract

Group-wise activation detection in task-based fMRI has been widely used because of its robustness to noises and statistical power to deal with variability of individual brains. However, current group-wise fMRI activation detection methods typically rely on the spatial alignment established by coregistration of individual brains' fMRI images into the same template space, which has difficulty in dealing with the remarkable anatomic variation of different brains. As a consequence, the resulted misalignment among multiple brains could substantially degrade the accuracy and specificity of group-wise fMRI activation detection. To address these challenges, this paper presents a novel methodology to detect group-wise fMRI activation based on a publicly released dense map of DTI-derived structural cortical landmarks, which possess intrinsic correspondences across individuals and populations. The basic idea here is that a first-level general linear model (GLM) analysis is performed on fMRI signals of each corresponding cortical landmark in each individual brain's own space, and then the single-subject effect size of the same landmark from a group of subjects are statistically integrated and assessed at the group level using the mixed-effects model. As a result, the consistently activated cortical landmarks are determined and declared group-wisely in response to external block-based stimuli. Our experimental results demonstrated that the proposed approach can map meaningful group-wise activation patterns on the atlas of cortical landmarks without image registration between subjects and spatial smoothing.