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Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study
The infant brain shows rapid neural network development that considerably influences cognitive and behavioral abilities in later life. Reportedly, this neural development process can be indexed by estimating neural signal complexity. However, the precise developmental trajectory of brain signal comp...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102372/ https://www.ncbi.nlm.nih.gov/pubmed/30154695 http://dx.doi.org/10.3389/fnins.2018.00566 |
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author | Hasegawa, Chiaki Takahashi, Tetsuya Yoshimura, Yuko Nobukawa, Sou Ikeda, Takashi Saito, Daisuke N. Kumazaki, Hirokazu Minabe, Yoshio Kikuchi, Mitsuru |
author_facet | Hasegawa, Chiaki Takahashi, Tetsuya Yoshimura, Yuko Nobukawa, Sou Ikeda, Takashi Saito, Daisuke N. Kumazaki, Hirokazu Minabe, Yoshio Kikuchi, Mitsuru |
author_sort | Hasegawa, Chiaki |
collection | PubMed |
description | The infant brain shows rapid neural network development that considerably influences cognitive and behavioral abilities in later life. Reportedly, this neural development process can be indexed by estimating neural signal complexity. However, the precise developmental trajectory of brain signal complexity during infancy remains elusive. This study was conducted to ascertain the trajectory of magnetoencephalography (MEG) signal complexity from 2 months to 3 years of age in five infants using multiscale entropy (MSE), which captures signal complexity at multiple temporal scales. Analyses revealed scale-dependent developmental trajectories. Specifically, signal complexity predominantly increased from 5 to 15 months of age at higher temporal scales, whereas the complexity at lower temporal scales was constant across age, except in one infant who showed decreased complexity. Despite a small sample size limiting this study’s power, this is the first report of a longitudinal investigation of changes in brain signal complexity during early infancy and is unique in its application of MSE analysis of longitudinal MEG data during infancy. The results of this pilot study may serve to further our understanding of the longitudinal changes in the neural dynamics of the developing infant brain. |
format | Online Article Text |
id | pubmed-6102372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61023722018-08-28 Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study Hasegawa, Chiaki Takahashi, Tetsuya Yoshimura, Yuko Nobukawa, Sou Ikeda, Takashi Saito, Daisuke N. Kumazaki, Hirokazu Minabe, Yoshio Kikuchi, Mitsuru Front Neurosci Neuroscience The infant brain shows rapid neural network development that considerably influences cognitive and behavioral abilities in later life. Reportedly, this neural development process can be indexed by estimating neural signal complexity. However, the precise developmental trajectory of brain signal complexity during infancy remains elusive. This study was conducted to ascertain the trajectory of magnetoencephalography (MEG) signal complexity from 2 months to 3 years of age in five infants using multiscale entropy (MSE), which captures signal complexity at multiple temporal scales. Analyses revealed scale-dependent developmental trajectories. Specifically, signal complexity predominantly increased from 5 to 15 months of age at higher temporal scales, whereas the complexity at lower temporal scales was constant across age, except in one infant who showed decreased complexity. Despite a small sample size limiting this study’s power, this is the first report of a longitudinal investigation of changes in brain signal complexity during early infancy and is unique in its application of MSE analysis of longitudinal MEG data during infancy. The results of this pilot study may serve to further our understanding of the longitudinal changes in the neural dynamics of the developing infant brain. Frontiers Media S.A. 2018-08-14 /pmc/articles/PMC6102372/ /pubmed/30154695 http://dx.doi.org/10.3389/fnins.2018.00566 Text en Copyright © 2018 Hasegawa, Takahashi, Yoshimura, Nobukawa, Ikeda, Saito, Kumazaki, Minabe and Kikuchi. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Hasegawa, Chiaki Takahashi, Tetsuya Yoshimura, Yuko Nobukawa, Sou Ikeda, Takashi Saito, Daisuke N. Kumazaki, Hirokazu Minabe, Yoshio Kikuchi, Mitsuru Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title | Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title_full | Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title_fullStr | Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title_full_unstemmed | Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title_short | Developmental Trajectory of Infant Brain Signal Variability: A Longitudinal Pilot Study |
title_sort | developmental trajectory of infant brain signal variability: a longitudinal pilot study |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102372/ https://www.ncbi.nlm.nih.gov/pubmed/30154695 http://dx.doi.org/10.3389/fnins.2018.00566 |
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