RT info:eu-repo/semantics/article
T1 Exploring the alterations in the distribution of neural network weights in dementia due to alzheimer’s disease
A1 Revilla Vallejo, Marcos
A1 Poza Crespo, Jesús
A1 Gómez Pilar, Javier
A1 Hornero Sánchez, Roberto
A1 Tola Arribas, Miguel Ángel
A1 Cano, Mónica
A1 Gómez Peña, Carlos
K1 Alzheimer's disease
K1 Alzheimer, Enfermedad de
K1 Cognition disorders
K1 Mental health
K1 Electroencephalography
K1 Entropy
K1 Demencia
K1 Enfermedades mentales
K1 Cerebro - Enfermedades
K1 Neural network
K1 Red neuronal
K1 3201.07 Geriatría
K1 6310.03 Enfermedad
AB 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.
PB MDPI
SN 1099-4300
YR 2021
FD 2021
LK https://uvadoc.uva.es/handle/10324/59686
UL https://uvadoc.uva.es/handle/10324/59686
LA eng
NO Entropy, 2021, Vol. 23, Nº. 5, 500
NO Producción Científica
DS UVaDOC
RD 18-nov-2024