Regional Strength of Large-Scale Functional Brain Networks is Associated with Regional Volumes in Older Adults and in Alzheimer's Disease.

Abstract

Background: The association between regional volumes and resting-state functional networks was tested within the default-mode network (DMN), influenced by Alzheimer pathology, salience network (SalN), not under similar pathological influence, and sensorimotor network (SMN), usually spared by pathology. Methods: A total of 148 participants, with Alzheimer's disease (AD) dementia, mild cognitive impairment (MCI), and healthy controls underwent multimodal brain magnetic resonance imaging (MRI). Functional network identification was achieved with group-level independent-component analysis of functional MRI (fMRI) scans. T1 weighted images were also analyzed. Ten regions of interest (ROI) were defined in core hubs of the three networks. Gray-matter volume/functional network strength association was tested within-ROI and cross-ROI in each group by using partial-correlation models and ROI-to-ROI, ROI-to-voxel, and voxel-to-voxel correlations. Results: In controls, a negative association was found between right inferior-parietal volumes and SMN expression in the left precentral gyrus, as revealed by ROI-to-ROI models. In AD, DMN expression was positively associated with the volume of the left insula and the right inferior parietal lobule, and SalN expression was positively associated with volume of the left inferior parietal lobule. ROI-to-voxel models revealed significant associations between the volume of the posterior cingulate cortex and SMN expression in sensorimotor and premotor regions. No significant findings emerged in the MCI nor from voxel-to-voxel analyses. Discussion: Regional volumes of main network hubs are significantly associated with hemodynamic network expression, although patterns are intricate and dependent on diagnostic status. Since distinct networks are differentially influenced by Alzheimer pathology, it appears that pathology plays a significant role in influencing the association between regional volumes and regional functional network strength.