Rhesus macaque brain morphometry: a methodological comparison of voxel-wise approaches

Abstract

Voxel-based morphometry studies have become increasingly common in human neuroimaging over the past several years; however, few studies have utilized this method to study morphometry changes in non-human primates. Here we describe the application of voxel-wise morphometry methods to the rhesus macaque (Macaca mulatta) using the 112RM-SL template and priors (McLaren et al. (2009) [42]) and as an illustrative example we describe age-associated changes in grey matter morphometry. Specifically, we evaluated the unified segmentation routine implemented using Statistical Parametric Mapping (SPM) software and the FMRIB's Automated Segmentation Tool (FAST) in the FMRIB Software Library (FSL); the effect of varying the smoothing kernel; and the effect of the normalization routine. We found that when studying non-human primates, brain images need less smoothing than in human studies, 2-4mm FWHM. Using flow field deformations (DARTEL) improved inter-subject alignment leading to results that were more likely due to morphometry differences as opposed to registration differences.