Literature DB >> 33197505

Alterations of Brain Networks in Alzheimer's Disease and Mild Cognitive Impairment: A Resting State fMRI Study Based on a Population-specific Brain Template.

Yuan Luo1, Tongtong Sun1, Chunchao Ma2, Xianchang Zhang3, Yong Ji4, Xiuwei Fu5, Hongyan Ni6.   

Abstract

This study aimed to investigate the alterations in brain networks in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on a population-specific brain template. Previous studies on AD brain networks using graph theory rarely adopted brain templates specific for certain ethnicities. In this study, patients were divided into 3 groups: AD (n = 24), MCI (n = 27), and healthy controls (HCs, n = 33), and all of the subjects are Chinese. Functional brain networks were constructed for each group based on a Chinese brain template using resting-state functional magnetic resonance imaging (rs-fMRI) data; several graph metrics were calculated. Graph metrics with significant differences after false discovery rate (FDR) correction were analyzed with respect to correlations with four neuropsychological test scores: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), and Clinical Dementia Rating (CDR), which assessed the subjects' cognitive functions and ability to engage in ADL. Graph metrics including assortativity coefficient, nodal degree centrality, nodal clustering coefficient, nodal efficiency, and nodal local efficiency of the frontal gyrus and cerebellum were significantly altered in AD and MCI compared with HC. Several graph metrics were significantly correlated with cognitive function and the ability to engage in daily activities. The findings suggest that altered graph metrics in the frontal gyrus may reflect brain plasticity, and that patients with MCI may have unique graph metric alterations in the cerebellum. Future graph analysis studies on functional brain networks in AD and MCI based on population-specific brain atlases for particular ethnicities may prove valuable.
Copyright © 2020. Published by Elsevier Ltd.

Entities:  

Keywords:  brain plasticity; cerebellum; functional brain network; graph analysis

Mesh:

Year:  2020        PMID: 33197505     DOI: 10.1016/j.neuroscience.2020.10.023

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  4 in total

1.  Temporal and Spatial Analysis of Alzheimer's Disease Based on an Improved Convolutional Neural Network and a Resting-State FMRI Brain Functional Network.

Authors:  Haijing Sun; Anna Wang; Shanshan He
Journal:  Int J Environ Res Public Health       Date:  2022-04-08       Impact factor: 4.614

2.  Diagnosis of Alzheimer's Disease Severity with fMRI Images Using Robust Multitask Feature Extraction Method and Convolutional Neural Network (CNN).

Authors:  Morteza Amini; MirMohsen Pedram; AliReza Moradi; Mahshad Ouchani
Journal:  Comput Math Methods Med       Date:  2021-04-27       Impact factor: 2.238

3.  Functional Brain Connectivity in Mild Cognitive Impairment With Sleep Disorders: A Study Based on Resting-State Functional Magnetic Resonance Imaging.

Authors:  Yuxi Luo; Mengyuan Qiao; Yuqing Liang; Chongli Chen; Lichuan Zeng; Lin Wang; Wenbin Wu
Journal:  Front Aging Neurosci       Date:  2022-03-10       Impact factor: 5.750

4.  Subcortical and Cerebellar Neural Correlates of Prodromal Alzheimer's Disease with Prolonged Sleep Latency.

Authors:  Yoo Hyun Um; Sheng-Min Wang; Dong Woo Kang; Nak-Young Kim; Hyun Kook Lim
Journal:  J Alzheimers Dis       Date:  2022       Impact factor: 4.472

  4 in total

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