Variations of Resting-State EEG-Based Functional Networks in Brain Maturation From Early Childhood to Adolescence
10.3988/jcn.2022.18.5.581
- Author:
Yoon Gi CHUNG
1
;
Yonghoon JEON
;
Ryeo Gyeong KIM
;
Anna CHO
;
Hunmin KIM
;
Hee HWANG
;
Jieun CHOI
;
Ki Joong KIM
Author Information
1. Department of Pediatrics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
- Publication Type:ORIGINAL ARTICLE
- From:Journal of Clinical Neurology
2022;18(5):581-593
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:and Purpose 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 networkbased brain maturation across the adult lifespan.
Methods: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.
Results: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.
Conclusions: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.
