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.

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.

Objectives: This study examined the responses to standard stimuli to investigate the mechanisms underlying mismatch negativity (MMN) impairments in schizophrenia. Methods: We obtained MMN data from 68 patients diagnosed with schizophrenia or schizoaffective disorder and 38 healthy controls and analyzed the electrophysiological activity of the responses to two standard stimuli before deviants using time-frequency methods. Results: As a result of RM ANOVA at evoked alpha power, there were differences not only between-subjects (F 1,104=4.35, p<0.05) but also within-subjects (F 1,104=8.62, p<0.01) without groupby-stimulus interaction (F 1,104=1.70, p=0.20). But at single-trial alpha power, there was a difference not between-subjects (F 1,104=3.81, p=0.054), but only within-subjects (F 1,104=10.14, p<0.01) with significant group-by-stimulus interaction (F 1,104=5.71, p<0.05). Moreover, between-group differences were significant in evoked alpha power (t 104=2.02, p<0.05, d=0.41) and single-trial alpha power (t 104=2.49, p<0.01, d=0.50) to standard stimuli presented not at the first instance but second. According to the order that the two standards presented, there were increases of evoked alpha power (t 37=-2.54, p<0.05, d=0.58) and single-trial alpha power (t 37=-3.41, p<0.01, d=0.78) in only the healthy controls. The positive correlations were shown in clinical features between years of education completed and event-related potential amplitude at 100 ms to both standard stimuli (Each Pearson Corr.: r=0.22, p<0.05). Conclusion These outputs suggest that the P1 alpha oscillation to standards is associated with deficits in the inhibitory control of selective attention relative to cognitive dysfunction in schizophrenia.We could also hypothesize that these deficits are involved in computing prediction errors based on the predictive coding perspective. However, further studies on this hypothesis are necessary.