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...
Autores principales: | , , , , |
---|---|
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 |