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Por favor, use este identificador para citar o enlazar este ítem: http://uvadoc.uva.es/handle/10324/21722
Título: Analysis of Spontaneous EEG Activity in Alzheimer’s Disease Using Cross-Sample Entropy and Graph Theory
Autor: Gómez, Carlos
Poza Crespo, Jesús
Gómez Pilar, Javier
Bachiller, Alejandro
Juan Cruz, Celia
Tola Arribas, Miguel A.
Carreres, Alicia
Cano, Mónica
Hornero Sánchez, Roberto
Año del Documento: 2016
Editorial: IEEE Conference Publications
Descripción: Producción Científica
Documento Fuente: 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
Resumen: 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.
Materias (normalizadas): Entropy
ISSN: 1557-170X
Revisión por Pares: SI
Patrocinador: Ministerio de Economía y Competitividad (TEC2014-53196-R)
Junta de Castilla y León (proyecto VA037U16 y BIO/VA08/15)
Version del Editor: http://ieeexplore.ieee.org/servlet/opac?punumber=1000269
Idioma: eng
URI: http://uvadoc.uva.es/handle/10324/21722
Derechos: info:eu-repo/semantics/openAccess
Aparece en las colecciones:DEP71 - Artículos de revista

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