2026-05-05T20:55:35Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/217222025-02-20T10:45:14Zcom_10324_1191com_10324_931com_10324_894col_10324_1379

00925njm 22002777a 4500 dc Gómez Peña, Carlos author Poza Crespo, Jesús author Gómez Pilar, Javier author Bachiller Matarranz, Alejandro author Juan Cruz, Celia author Tola Arribas, Miguel Ángel author Carreres Rodríguez, Alicia author Cano, Mónica author Hornero Sánchez, Roberto author 2016 The aim of this pilot study was to analyze spontaneous electroencephalography (EEG) activity in Alzheimer’s disease (AD) by means of Cross-Sample Entropy (Cross-SampEn) and two local measures derived from graph theory: clustering coefficient (CC) and characteristic path length (PL). Five minutes of EEG activity were recorded from 37 patients with dementia due to AD and 29 elderly controls. Our results showed that Cross-SampEn values were lower in the AD group than in the control one for all the interactions among EEG channels. This finding indicates that EEG activity in AD is characterized by a lower statistical dissimilarity among channels. Significant differences were found mainly for fronto-central interactions (p < 0.01, permutation test). Additionally, the application of graph theory measures revealed diverse neural network changes, i.e. lower CC and higher PL values in AD group, leading to a less efficient brain organization. This study suggests the usefulness of our approach to provide further insights into the underlying brain dynamics associated with AD. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2016, p. 2830 - 2833 1557-170X http://uvadoc.uva.es/handle/10324/21722 Entropy Analysis of spontaneous EEG activity in Alzheimer’s disease using cross-sample entropy and graph theory