{"title":"儿童静息状态脑电图分形维数随年龄增大而增大。","authors":"Si Long Jenny Tou, Tom Chau","doi":"10.1093/cercor/bhaf138","DOIUrl":null,"url":null,"abstract":"<p><p>Resting-state electroencephalography (rs-EEG) represents spontaneous neural activity and is increasingly analyzed using nonlinear measures to assess brain complexity. The Higuchi Fractal Dimension (HFD) is a widely used metric for quantifying the fractal properties of EEG signals, yet its developmental trajectory remains largely unexplored. In this study, we examined age-related changes in HFD across childhood, adolescence, and early adulthood. We analyzed eyes-closed rs-EEG from 128 channels in 83 neurotypical participants (8 to 30 yr) from the MIPDB database. To assess developmental patterns, we applied a Gaussian Linear Mixed Model with age, electrode location, and their interaction as predictors, alongside non-parametric cluster-based permutation analysis to evaluate topographical differences. We observed a significant increase in HFD with age (P = 0.001), most pronounced between childhood and adolescence, followed by stabilization in early adulthood. HFD also varied across electrode locations, with higher values in frontal, central, and temporal regions and lower values in parietal and occipital areas. These findings provide new insights into the maturation of neural complexity in rs-EEG, aligning with known structural and functional changes in brain development. This study contributes to the growing body of research on nonlinear EEG dynamics and their relevance to neurodevelopment.</p>","PeriodicalId":9715,"journal":{"name":"Cerebral cortex","volume":"35 6","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12159291/pdf/","citationCount":"0","resultStr":"{\"title\":\"The fractal dimension of resting state EEG increases over age in children.\",\"authors\":\"Si Long Jenny Tou, Tom Chau\",\"doi\":\"10.1093/cercor/bhaf138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Resting-state electroencephalography (rs-EEG) represents spontaneous neural activity and is increasingly analyzed using nonlinear measures to assess brain complexity. The Higuchi Fractal Dimension (HFD) is a widely used metric for quantifying the fractal properties of EEG signals, yet its developmental trajectory remains largely unexplored. In this study, we examined age-related changes in HFD across childhood, adolescence, and early adulthood. We analyzed eyes-closed rs-EEG from 128 channels in 83 neurotypical participants (8 to 30 yr) from the MIPDB database. To assess developmental patterns, we applied a Gaussian Linear Mixed Model with age, electrode location, and their interaction as predictors, alongside non-parametric cluster-based permutation analysis to evaluate topographical differences. We observed a significant increase in HFD with age (P = 0.001), most pronounced between childhood and adolescence, followed by stabilization in early adulthood. HFD also varied across electrode locations, with higher values in frontal, central, and temporal regions and lower values in parietal and occipital areas. These findings provide new insights into the maturation of neural complexity in rs-EEG, aligning with known structural and functional changes in brain development. This study contributes to the growing body of research on nonlinear EEG dynamics and their relevance to neurodevelopment.</p>\",\"PeriodicalId\":9715,\"journal\":{\"name\":\"Cerebral cortex\",\"volume\":\"35 6\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12159291/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cerebral cortex\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1093/cercor/bhaf138\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cerebral cortex","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/cercor/bhaf138","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
The fractal dimension of resting state EEG increases over age in children.
Resting-state electroencephalography (rs-EEG) represents spontaneous neural activity and is increasingly analyzed using nonlinear measures to assess brain complexity. The Higuchi Fractal Dimension (HFD) is a widely used metric for quantifying the fractal properties of EEG signals, yet its developmental trajectory remains largely unexplored. In this study, we examined age-related changes in HFD across childhood, adolescence, and early adulthood. We analyzed eyes-closed rs-EEG from 128 channels in 83 neurotypical participants (8 to 30 yr) from the MIPDB database. To assess developmental patterns, we applied a Gaussian Linear Mixed Model with age, electrode location, and their interaction as predictors, alongside non-parametric cluster-based permutation analysis to evaluate topographical differences. We observed a significant increase in HFD with age (P = 0.001), most pronounced between childhood and adolescence, followed by stabilization in early adulthood. HFD also varied across electrode locations, with higher values in frontal, central, and temporal regions and lower values in parietal and occipital areas. These findings provide new insights into the maturation of neural complexity in rs-EEG, aligning with known structural and functional changes in brain development. This study contributes to the growing body of research on nonlinear EEG dynamics and their relevance to neurodevelopment.
期刊介绍:
Cerebral Cortex publishes papers on the development, organization, plasticity, and function of the cerebral cortex, including the hippocampus. Studies with clear relevance to the cerebral cortex, such as the thalamocortical relationship or cortico-subcortical interactions, are also included.
The journal is multidisciplinary and covers the large variety of modern neurobiological and neuropsychological techniques, including anatomy, biochemistry, molecular neurobiology, electrophysiology, behavior, artificial intelligence, and theoretical modeling. In addition to research articles, special features such as brief reviews, book reviews, and commentaries are included.