Paper Info
Title
Exploring The Alterations In The Distribution Of Neural Network Weights In Dementia Due To Alzheimer'S Disease
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder which has become an outstanding social problem. The main objective of this study was to evaluate the alterations that dementia due to AD elicits in the distribution of functional network weights. Functional connectivity networks were obtained using the orthogonalized Amplitude Envelope Correlation (AEC), computed from source-reconstructed resting-state eletroencephalographic (EEG) data in a population formed by 45 cognitive healthy elderly controls, 69 mild cognitive impaired (MCI) patients and 81 AD patients. Our results indicated that AD induces a progressive alteration of network weights distribution; specifically, the Shannon entropy (SE) of the weights distribution showed statistically significant between-group differences (p < 0.05, Kruskal-Wallis test, False Discovery Rate corrected). Furthermore, an in-depth analysis of network weights distributions was performed in delta, alpha, and beta-1 frequency bands to discriminate the weight ranges showing statistical differences in SE. Our results showed that lower and higher weights were more affected by the disease, whereas mid-range connections remained unchanged. These findings support the importance of performing detailed analyses of the network weights distribution to further understand the impact of AD progression on functional brain activity.
Year
DOI
Venue
2021
10.3390/e23050500
ENTROPY
Keywords
DocType
Volume
Alzheimer's disease (AD), mild cognitive impairment (MCI), electroencephalogram (EEG), functional neural network, network weights distribution, Shannon entropy (SE)
Journal
23
Issue
ISSN
Citations 
5
1099-4300
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Marcos Revilla-Vallejo100.34
Jesús Poza200.34
Javier Gomez-Pilar300.34
Roberto Hornero400.34
Miguel Ángel Tola-Arribas500.34
Mónica Cano600.34
Carlos Gómez78615.72