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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/59100

    Título
    Neurofeedback training based on motor imagery strategies increases EEG complexity in elderly population
    Autor
    Marcos Martínez, DiegoAutoridad UVA
    Martínez Cagigal, VíctorAutoridad UVA Orcid
    SantaMaría Vazquez, EduardoAutoridad UVA
    Pérez Velasco, SergioAutoridad UVA
    Hornero Sánchez, RobertoAutoridad UVA Orcid
    Año del Documento
    2021
    Editorial
    MDPI
    Descripción
    Producción Científica
    Documento Fuente
    Entropy, 2021, Vol. 23, Nº. 12, 1574
    Resumo
    Neurofeedback training (NFT) has shown promising results in recent years as a tool to address the effects of age-related cognitive decline in the elderly. Since previous studies have linked reduced complexity of electroencephalography (EEG) signal to the process of cognitive decline, we propose the use of non-linear methods to characterise changes in EEG complexity induced by NFT. In this study, we analyse the pre- and post-training EEG from 11 elderly subjects who performed an NFT based on motor imagery (MI–NFT). Spectral changes were studied using relative power (RP) from classical frequency bands (delta, theta, alpha, and beta), whilst multiscale entropy (MSE) was applied to assess EEG-induced complexity changes. Furthermore, we analysed the subject’s scores from Luria tests performed before and after MI–NFT. We found that MI–NFT induced a power shift towards rapid frequencies, as well as an increase of EEG complexity in all channels, except for C3. These improvements were most evident in frontal channels. Moreover, results from cognitive tests showed significant enhancement in intellectual and memory functions. Therefore, our findings suggest the usefulness of MI–NFT to improve cognitive functions in the elderly and encourage future studies to use MSE as a metric to characterise EEG changes induced by MI–NFT.
    Materias (normalizadas)
    Biofeedback training
    Entrenamiento de biorretroalimentación
    Entropía
    Brain-computer interfaces
    Older people - Care
    Personas de edad - Salud mental
    Cognición
    Neuropsychology
    Neuropsicología
    Materias Unesco
    3201.07 Geriatría
    3205.07 Neurología
    Palabras Clave
    Neurofeedback training
    Motor imagery
    ISSN
    1099-4300
    Revisión por pares
    SI
    DOI
    10.3390/e23121574
    Patrocinador
    Ministerio de Ciencia e Innovación (Grants PID2020-115468RB-I00 and RTC2019- 007350-1)
    Gobierno de España (Agencia Estatal de Investigación) - (Projects 10.13039/ 501100011033)
    Unión Europea y Fondo Europeo de Desarrollo Regional (FEDER) - (Cooperation Programme Interreg V-A Spain-Portugal POCTEP 2014–2020)
    Version del Editor
    https://www.mdpi.com/1099-4300/23/12/1574
    Propietario de los Derechos
    © 2021 The authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/59100
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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