Does resting state functional connectivity differ between mild cognitive impairment and early Alzheimer's dementia?

Purpose: This study aimed to investigate differences in functional connectivity (FC) among different resting state networks (RSN) in clinically non-progressive mild cognitive impairment (MCI) and Alzheimer's disease (AD).

Methods: Using 3T MRI acquired resting-state functional MRI (rs-fMRI), we attempted identification of different RSN using independent component analysis (ICA) in amnestic-MCI, convertors to early AD and age-matched cognitively normal healthy controls. Regions of interest (ROI) that showed significant differences in connectivity on group ICA were selected as seeds for seed-voxel analysis. Group differences in FC for each network-connectivity map were entered into a general linear model with age, gender and total intra-cranial volume (TIV) as covariates.

Results: In this cross-sectional design 31 HC, 30 MCI and 30 MCI-convertors to early AD were evaluated. Seed-based analysis between AD and controls revealed reduced posterior connectivity within the default mode (DMN), dorsal attention (DAN) and antero-posterior connectivity with sensori-motor (SMN) networks. Reduced cerebellar connectivity of DMN and posterior connectivity within the frontal parietal network (FPN) separated AD from MCI. MCI-control comparisons revealed differences only on ICA. Positive correlation was observed between FC in DMN network clusters with verbal list-learning (r = 0.50) and recall scores (r = 0.51) in AD, the latter additionally demonstrating correlation with SMN clusters (r = 0.50).

Conclusions: Widespread network hypo-connectivity is apparent in AD as opposed to MCI non-convertors in comparison to controls, along with positive correlation with memory scores. Reduced connectivity involving DMN and FPN helps to differentiate between AD and MCI-nonconvertors to dementia. Longitudinal studies are required into utility of these measures.