{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["18(5)"],"submitter":["Chung YG"],"pubmed_abstract":["<h4>Background and purpose</h4>Alterations in human brain functional networks with maturation have been explored extensively in numerous electroencephalography (EEG) and functional magnetic resonance imaging studies. It is known that the age-related changes in the functional networks occurring prior to adulthood deviate from ordinary trajectories of network-based brain maturation across the adult lifespan.<h4>Methods</h4>This study investigated the longitudinal evolution of resting-state EEG-based functional networks from early childhood to adolescence among 212 pediatric patients (age 12.2±3.5 years, range 4.4-17.9) in 6 frequency bands using 8 types of functional connectivity measures in the amplitude, frequency, and phase domains.<h4>Results</h4>Electrophysiological aspects of network-based pediatric brain maturation were characterized by increases in both functional segregation and integration up to middle adolescence. EEG oscillations in the upper alpha band reflected the age-related increases in mean node strengths and mean clustering coefficients and a decrease in the characteristic path lengths better than did those in the other frequency bands, especially for the phase-domain functional connectivity. The frequency-band-specific age-related changes in the global network metrics were influenced more by volume-conduction effects than by the domain specificity of the functional connectivity measures.<h4>Conclusions</h4>We believe that this is the first study to reveal EEG-based functional network properties during preadult brain maturation based on various functional connectivity measures. The findings potentially have clinical applications in the diagnosis and treatment of age-related brain disorders."],"journal":["Journal of clinical neurology (Seoul, Korea)"],"pagination":["581-593"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9444558"],"repository":["biostudies-literature"],"pubmed_title":["Variations of Resting-State EEG-Based Functional Networks in Brain Maturation From Early Childhood to Adolescence."],"pmcid":["PMC9444558"],"pubmed_authors":["Kim RG","Kim H","Kim KJ","Hwang H","Jeon Y","Cho A","Choi J","Chung YG"],"additional_accession":[]},"is_claimable":false,"name":"Variations of Resting-State EEG-Based Functional Networks in Brain Maturation From Early Childhood to Adolescence.","description":"<h4>Background and purpose</h4>Alterations in human brain functional networks with maturation have been explored extensively in numerous electroencephalography (EEG) and functional magnetic resonance imaging studies. It is known that the age-related changes in the functional networks occurring prior to adulthood deviate from ordinary trajectories of network-based brain maturation across the adult lifespan.<h4>Methods</h4>This study investigated the longitudinal evolution of resting-state EEG-based functional networks from early childhood to adolescence among 212 pediatric patients (age 12.2±3.5 years, range 4.4-17.9) in 6 frequency bands using 8 types of functional connectivity measures in the amplitude, frequency, and phase domains.<h4>Results</h4>Electrophysiological aspects of network-based pediatric brain maturation were characterized by increases in both functional segregation and integration up to middle adolescence. EEG oscillations in the upper alpha band reflected the age-related increases in mean node strengths and mean clustering coefficients and a decrease in the characteristic path lengths better than did those in the other frequency bands, especially for the phase-domain functional connectivity. The frequency-band-specific age-related changes in the global network metrics were influenced more by volume-conduction effects than by the domain specificity of the functional connectivity measures.<h4>Conclusions</h4>We believe that this is the first study to reveal EEG-based functional network properties during preadult brain maturation based on various functional connectivity measures. The findings potentially have clinical applications in the diagnosis and treatment of age-related brain disorders.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Sep","modification":"2025-04-04T11:05:59.262Z","creation":"2025-02-19T00:42:35.129Z"},"accession":"S-EPMC9444558","cross_references":{"pubmed":["36062776"],"doi":["10.3988/jcn.2022.18.5.581"]}}