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 (nor-mal 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 rest-ing-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 addi-tion, 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 Alz-heimer’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.

Key words: neural regeneration, neurodegeneration, human connectome, functional MRI, graph theory, resting state, small world property, early mild cognitive impairment, late mild cognitive impairment, Alzheimer’s disease, aging, diffuse brain disease, grants-supported paper, neuroregeneration