Open AccessInvestigation of the Changes in the Power Distribution in Resting-State Brain Networks Associated with Pure Conduct Disorder
Author(s) -
Jiang Zhang,
Jiansong Zhou,
Fengmei Lu,
Liangyin Chen,
Yunzhi Huang,
Huafu Chen,
YuTao Xiang,
Gang Yang,
Zhen Yuan
Publication year - 2017
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/s41598-017-05863-3
Subject(s) - resting state fmri , functional magnetic resonance imaging , spectral density , distribution (mathematics) , power (physics) , statistical power , neuroscience , psychology , brain activity and meditation , medicine , audiology , electroencephalography , statistics , mathematics , physics , mathematical analysis , quantum mechanics
Conduct disorder (CD) is a psychiatric disorder in children and adolescence. To investigate changes in the power distribution in brain networks between CD and typically developing (TD) groups, resting-state functional magnetic resonance imaging (rsfMRI) data of thirty-six subjects were first recorded, and then the data were preprocessed using DPARSF and SPM8. Meanwhile, the power of the blood oxygenation level-dependent (BOLD) signals of ninety brain regions was acquired using the integral of the Welch power spectral density (PSD). Additionally, the powers of the brain regions that reached significance ( p < 0.05) were extracted using the bootstrap statistics, in which the standardized z-scores of the powers were used as a reference. The results of the analysis of the changes in power exhibited that there were significant power differences in some pairs of brain regions between the CD and TD groups, indicating a change in the power distribution. In addition, the results also suggest that the total power consumption of brain networks in CD patients is less than that observed in the TD group. Consequently, the study provided a paradigm for establishing quantifiable indicators via the power spectrum approach for the comparison and analysis of the BOLD signal power between CD patients and healthy controls.