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Medical & Biological Engineering & Computing
Erschienen in: Medical & Biological Engineering & Computing 11/2016

01.11.2016 | Original Article

Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly

verfasst von: Javier Gomez-Pilar, Rebeca Corralejo, Luis F. Nicolas-Alonso, Daniel Álvarez, Roberto Hornero

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 11/2016

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Abstract

Neurofeedback training (NFT) has shown to be promising and useful to rehabilitate cognitive functions. Recently, brain–computer interfaces (BCIs) were used to restore brain plasticity by inducing brain activity with an NFT. In our study, we hypothesized that an NFT with a motor imagery-based BCI (MI-BCI) could enhance cognitive functions related to aging effects. To assess the effectiveness of our MI-BCI application, 63 subjects (older than 60 years) were recruited. This novel application was used by 31 subjects (NFT group). Their Luria neuropsychological test scores were compared with the remaining 32 subjects, who did not perform NFT (control group). Electroencephalogram changes measured by relative power (RP) endorsed cognitive potential findings under study: visuospatial, oral language, memory, intellectual and attention functions. Three frequency bands were selected to assess cognitive changes: 12, 18, and 21 Hz (bandwidth 3 Hz). Significant increases (p < 0.01) in the RP of these frequency bands were found. Moreover, results from cognitive tests showed significant improvements (p < 0.01) in four cognitive functions after performing five NFT sessions: visuospatial, oral language, memory, and intellectual. This established evidence in the association between NFT performed by a MI-BCI and enhanced cognitive performance. Therefore, it could be a novel approach to help elderly people.
Vorheriger Artikel Nonnegative matrix factorization and sparse representation for the automated detection of periodic limb movements in sleep
Nächster Artikel Calf muscle perfusion as measured with magnetic resonance imaging to assess peripheral arterial disease

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Metadaten
Titel
Neurofeedback training with a motor imagery-based BCI: neurocognitive improvements and EEG changes in the elderly
verfasst von
Javier Gomez-Pilar
Rebeca Corralejo
Luis F. Nicolas-Alonso
Daniel Álvarez
Roberto Hornero
Publikationsdatum
01.11.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 11/2016
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-016-1454-4

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