Cargando…

Age-Related Changes in Electroencephalographic Signal Complexity

The study of active and healthy aging is a primary focus for social and neuroscientific communities. Here, we move a step forward in assessing electrophysiological neuronal activity changes in the brain with healthy aging. To this end, electroencephalographic (EEG) resting state activity was acquire...

Descripción completa

Detalles Bibliográficos
Autores principales: Zappasodi, Filippo, Marzetti, Laura, Olejarczyk, Elzbieta, Tecchio, Franca, Pizzella, Vittorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4633126/
https://www.ncbi.nlm.nih.gov/pubmed/26536036
http://dx.doi.org/10.1371/journal.pone.0141995
_version_ 1782399154517966848
author Zappasodi, Filippo
Marzetti, Laura
Olejarczyk, Elzbieta
Tecchio, Franca
Pizzella, Vittorio
author_facet Zappasodi, Filippo
Marzetti, Laura
Olejarczyk, Elzbieta
Tecchio, Franca
Pizzella, Vittorio
author_sort Zappasodi, Filippo
collection PubMed
description The study of active and healthy aging is a primary focus for social and neuroscientific communities. Here, we move a step forward in assessing electrophysiological neuronal activity changes in the brain with healthy aging. To this end, electroencephalographic (EEG) resting state activity was acquired in 40 healthy subjects (age 16–85). We evaluated Fractal Dimension (FD) according to the Higuchi algorithm, a measure which quantifies the presence of statistical similarity at different scales in temporal fluctuations of EEG signals. Our results showed that FD increases from age twenty to age fifty and then decreases. The curve that best fits the changes in FD values across age over the whole sample is a parabola, with the vertex located around age fifty. Moreover, FD changes are site specific, with interhemispheric FD asymmetry being pronounced in elderly individuals in the frontal and central regions. The present results indicate that fractal dimension well describes the modulations of brain activity with age. Since fractal dimension has been proposed to be related to the complexity of the signal dynamics, our data demonstrate that the complexity of neuronal electric activity changes across the life span of an individual, with a steady increase during young adulthood and a decrease in the elderly population.
format Online
Article
Text
id pubmed-4633126
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-46331262015-11-13 Age-Related Changes in Electroencephalographic Signal Complexity Zappasodi, Filippo Marzetti, Laura Olejarczyk, Elzbieta Tecchio, Franca Pizzella, Vittorio PLoS One Research Article The study of active and healthy aging is a primary focus for social and neuroscientific communities. Here, we move a step forward in assessing electrophysiological neuronal activity changes in the brain with healthy aging. To this end, electroencephalographic (EEG) resting state activity was acquired in 40 healthy subjects (age 16–85). We evaluated Fractal Dimension (FD) according to the Higuchi algorithm, a measure which quantifies the presence of statistical similarity at different scales in temporal fluctuations of EEG signals. Our results showed that FD increases from age twenty to age fifty and then decreases. The curve that best fits the changes in FD values across age over the whole sample is a parabola, with the vertex located around age fifty. Moreover, FD changes are site specific, with interhemispheric FD asymmetry being pronounced in elderly individuals in the frontal and central regions. The present results indicate that fractal dimension well describes the modulations of brain activity with age. Since fractal dimension has been proposed to be related to the complexity of the signal dynamics, our data demonstrate that the complexity of neuronal electric activity changes across the life span of an individual, with a steady increase during young adulthood and a decrease in the elderly population. Public Library of Science 2015-11-04 /pmc/articles/PMC4633126/ /pubmed/26536036 http://dx.doi.org/10.1371/journal.pone.0141995 Text en © 2015 Zappasodi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zappasodi, Filippo
Marzetti, Laura
Olejarczyk, Elzbieta
Tecchio, Franca
Pizzella, Vittorio
Age-Related Changes in Electroencephalographic Signal Complexity
title Age-Related Changes in Electroencephalographic Signal Complexity
title_full Age-Related Changes in Electroencephalographic Signal Complexity
title_fullStr Age-Related Changes in Electroencephalographic Signal Complexity
title_full_unstemmed Age-Related Changes in Electroencephalographic Signal Complexity
title_short Age-Related Changes in Electroencephalographic Signal Complexity
title_sort age-related changes in electroencephalographic signal complexity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4633126/
https://www.ncbi.nlm.nih.gov/pubmed/26536036
http://dx.doi.org/10.1371/journal.pone.0141995
work_keys_str_mv AT zappasodifilippo agerelatedchangesinelectroencephalographicsignalcomplexity
AT marzettilaura agerelatedchangesinelectroencephalographicsignalcomplexity
AT olejarczykelzbieta agerelatedchangesinelectroencephalographicsignalcomplexity
AT tecchiofranca agerelatedchangesinelectroencephalographicsignalcomplexity
AT pizzellavittorio agerelatedchangesinelectroencephalographicsignalcomplexity