Sleep Med Psychophysiol.  2020 Dec;27(2):67-76. 10.14401/KASMED.2020.27.2.67.

Spectral Analysis of Resting EEG in Brain Compartments

• Lee M

• KMID: 2510600
• DOI: http://doi.org/10.14401/KASMED.2020.27.2.67

Abstract

Objectives
Brain maturation involves brain lateralization and asymmetry to achieve efficient information processing and cognitive controls. This study elucidates normal brain maturation change during the gap between ages 6-9 and age 14-17 using resting EEG.
Methods
An EEG dataset was acquired from open source MIPDB (Multimodal Resource for Studying Information Processing in the Developing Brain). Ages 6-9 (n = 24) and ages 14-17 (n = 26) were selected for analysis, and subjects with psychiatric illness or EEG with severe noise were excluded. Finally, ages 6-9 (n = 14) and ages 14-17 (n = 11) were subjected to EEG analysis using EEGlab. A 120-sec length of resting EEG when eyes were closed was secured for analysis. Brain topography was compartmentalized into nine regions, best fitted with brain anatomical structure.
Results
Absolute power of the delta band and theta band in ages 6-9 was greater than that of ages 14-17 in the whole brain, and, also is relative power of delta band in frontal compartment, which is same line with previous studies. The relative power of the beta band of ages 14-17 was greater than that of ages 6-9 in the whole brain. In asymmetry evaluation, relative power of the theta band in ages 14-17 showed greater power in the left than right frontal compartment; the opposite finding was noted in the parietal compartment. For the alpha band, a strong relative power distribution in the left parietal compartment was observed in ages 14-17. Absolute and relative power of the alpha band is distributed with hemispheric left lateralization in ages 14-17.
Conclusion
During the gap period between ages 6-9 and ages 14-17, brain work becomes more complicated and sophisticated, and alpha band and beta band plays important roles in brain maturation in typically developing children.

Keyword

Adolescents; Children; EEG; Spectral analysis