title: An abnormal resting-state functional brain network indicates progression towards Alzheimer's disease.
abstract: Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer's disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations (normal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer's disease) using the Alzheimer's Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer's disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the resting-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addition, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and Alzheimer's disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.
authors.affiliation: College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China ; International WIC Institute, Beijing University of Technology, Beijing 100022, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Xiang
authors.affiliation: College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China.
authors.forename: Hao
authors.initials: H
authors.lastname: Guo
authors.affiliation: College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China.
authors.forename: Rui
authors.initials: R
authors.lastname: Cao
authors.affiliation: College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China.
authors.forename: Hong
authors.initials: H
authors.lastname: Liang
authors.affiliation: College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi Province, China.
authors.forename: Junjie
authors.initials: J
authors.lastname: Chen
keywords: Alzheimer's disease; aging; diffuse brain disease; early mild cognitive impairment; functional MRI; grants-supported paper; graph theory; human connectome; late mild cognitive impairment; neural regeneration; neurodegeneration; neuroregeneration; resting state; small world property