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    • SCIENTIFIC PRODUCTION
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    • Dpto. Teoría de la Señal y Comunicaciones e Ingeniería Telemática
    • DEP71 - Artículos de revista
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    • DEP71 - Artículos de revista
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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 Peña, CarlosAutoridad UVA Orcid
    Poza Crespo, JesúsAutoridad UVA Orcid
    Gómez Pilar, Javier
    Bachiller Matarranz, Alejandro
    Juan Cruz, Celia
    Tola Arribas, Miguel ÁngelAutoridad UVA Orcid
    Carreres Rodríguez, Alicia
    Cano, Mónica
    Hornero Sánchez, RobertoAutoridad UVA Orcid
    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
    Abstract
    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
    openAccess
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    • DEP71 - Artículos de revista [157]
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    Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcept where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International

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