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

Shania M Soman; Sheelakumari Raghavan; P G Rajesh; Nandini Mohanan; Bejoy Thomas; Chandrsekharan Kesavadas; Ramshekhar N Menon

doi:10.1016/j.jns.2020.117093

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

J Neurol Sci. 2020 Nov 15:418:117093. doi: 10.1016/j.jns.2020.117093. Epub 2020 Aug 13.

Authors

Shania M Soman¹, Sheelakumari Raghavan², P G Rajesh¹, Nandini Mohanan¹, Bejoy Thomas³, Chandrsekharan Kesavadas³, Ramshekhar N Menon⁴

Affiliations

¹ Cognition and Behavioural Neurology Section, Department of Neurology, SreeChitraTirunal Institute for Medical Sciences and Technology, Trivandrum 695011, India.
² Cognition and Behavioural Neurology Section, Department of Neurology, SreeChitraTirunal Institute for Medical Sciences and Technology, Trivandrum 695011, India; Department of Imaging Sciences and Interventional Radiology, SreeChitraTirunal Institute for Medical Sciences and Technology, Trivandrum 695011, India.
³ Department of Imaging Sciences and Interventional Radiology, SreeChitraTirunal Institute for Medical Sciences and Technology, Trivandrum 695011, India.
⁴ Cognition and Behavioural Neurology Section, Department of Neurology, SreeChitraTirunal Institute for Medical Sciences and Technology, Trivandrum 695011, India. Electronic address: rsnmenon@sctimst.ac.in.

PMID: 32827882
DOI: 10.1016/j.jns.2020.117093

Abstract

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.

Keywords: Alzheimer's disease; Functional connectivity; Independent component analysis; Mild cognitive impairment; Seed-based connectivity.

MeSH terms

Alzheimer Disease* / diagnostic imaging
Brain / diagnostic imaging
Cognitive Dysfunction* / diagnostic imaging
Cross-Sectional Studies
Humans
Magnetic Resonance Imaging
Nerve Net
Neuropsychological Tests