Development of EEG connectivity from preschool to school-age children
IntroductionMany studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, r...
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Frontiers Media S.A.
2024-01-01
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Series: | Frontiers in Neuroscience |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2023.1277786/full |
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author | Jiannan Kang Wenqin Mao Juanmei Wu Xinping Huang Manuel F. Casanova Estate M. Sokhadze Estate M. Sokhadze Xiaoli Li Xinling Geng |
author_facet | Jiannan Kang Wenqin Mao Juanmei Wu Xinping Huang Manuel F. Casanova Estate M. Sokhadze Estate M. Sokhadze Xiaoli Li Xinling Geng |
author_sort | Jiannan Kang |
collection | DOAJ |
description | IntroductionMany studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, rather, on the interaction between different brain regions. In this regard studying the connectivity between brain regions is of great importance towards understanding higher cognitive functions and its underlying mechanisms.MethodsIn this study, EEG data of children (N = 253; 3-10 years old; 113 females, 140 males) from pre-school to schoolage was collected, and the weighted phase delay index and directed transfer function method was used to find the electrophysiological indicators of both functional connectivity and effective connectivity. A general linear model was built between the indicators and age, and the change trend of electrophysiological indicators analyzed for age.ResultsThe results showed an age trend for the functional and effective connectivity of the brain of children.DiscussionThe results are of importance in understanding normative brain development and in defining those conditions that deviate from typical growth trajectories. |
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format | Article |
id | doaj.art-65d44a3fcca74b69b5e4313d7c0e9191 |
institution | Directory Open Access Journal |
issn | 1662-453X |
language | English |
last_indexed | 2024-03-08T14:48:57Z |
publishDate | 2024-01-01 |
publisher | Frontiers Media S.A. |
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series | Frontiers in Neuroscience |
spelling | doaj.art-65d44a3fcca74b69b5e4313d7c0e91912024-01-11T04:48:46ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2024-01-011710.3389/fnins.2023.12777861277786Development of EEG connectivity from preschool to school-age childrenJiannan Kang0Wenqin Mao1Juanmei Wu2Xinping Huang3Manuel F. Casanova4Estate M. Sokhadze5Estate M. Sokhadze6Xiaoli Li7Xinling Geng8Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, ChinaChild Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, ChinaChild Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, ChinaChild Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo, ChinaDepartment of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Prisma Health System, Greenville, SC, United StatesDepartment of Biomedical Sciences, University of South Carolina School of Medicine Greenville Campus, Prisma Health System, Greenville, SC, United StatesDuke University, Durham, NC, United StatesState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, ChinaSchool of Biomedical Engineering, Capital Medical University, Beijing, ChinaIntroductionMany studies have collected normative developmental EEG data to better understand brain function in early life and associated changes during both aging and pathology. Higher cognitive functions of the brain do not normally stem from the workings of a single brain region that works but, rather, on the interaction between different brain regions. In this regard studying the connectivity between brain regions is of great importance towards understanding higher cognitive functions and its underlying mechanisms.MethodsIn this study, EEG data of children (N = 253; 3-10 years old; 113 females, 140 males) from pre-school to schoolage was collected, and the weighted phase delay index and directed transfer function method was used to find the electrophysiological indicators of both functional connectivity and effective connectivity. A general linear model was built between the indicators and age, and the change trend of electrophysiological indicators analyzed for age.ResultsThe results showed an age trend for the functional and effective connectivity of the brain of children.DiscussionThe results are of importance in understanding normative brain development and in defining those conditions that deviate from typical growth trajectories.https://www.frontiersin.org/articles/10.3389/fnins.2023.1277786/fullEEGfunctional connectivityeffective connectivitychildrenbrain development |
spellingShingle | Jiannan Kang Wenqin Mao Juanmei Wu Xinping Huang Manuel F. Casanova Estate M. Sokhadze Estate M. Sokhadze Xiaoli Li Xinling Geng Development of EEG connectivity from preschool to school-age children Frontiers in Neuroscience EEG functional connectivity effective connectivity children brain development |
title | Development of EEG connectivity from preschool to school-age children |
title_full | Development of EEG connectivity from preschool to school-age children |
title_fullStr | Development of EEG connectivity from preschool to school-age children |
title_full_unstemmed | Development of EEG connectivity from preschool to school-age children |
title_short | Development of EEG connectivity from preschool to school-age children |
title_sort | development of eeg connectivity from preschool to school age children |
topic | EEG functional connectivity effective connectivity children brain development |
url | https://www.frontiersin.org/articles/10.3389/fnins.2023.1277786/full |
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