Cortical similarity networks are sensitive to age effects in functional domains of the macaque brain

Brisbane Convention & Exhibition Centre 

Biological aging, in both health and disease, is linked to changes in brain architecture. Neuroimaging has been used extensively to study the impact of aging on brain structure, revealing reductions in cortical volume, surface area, thickness, and gyrification. New evidence suggests that these structural changes reflect dysconnectivity within brain networks that are particularly vulnerable to aging [1].

Structural connectivity is often studied using tractography derived from diffusion-weighted MRI data [2]. Yet, this approach is sensitive to false-positive connections and does not leverage information sensitive to cytoarchitectural changes (i.e. T1w, T2w, T2*). Morphometric Inverse Divergence (MIND) has been proposed as an alternative strategy, providing a measure of within-subject architectonic similarity between cortical areas based on multivariate distributions of vertex-wise MRI data for macro and microstructural features between region pair [3].

In this study, we will evaluate the sensitivity of MIND in detecting lifespan changes in global brain architecture in a cohort of N=63 macaque monkeys.