Altered Effective Connectivity Network in Childhood Absence Epilepsy: A Multi-frequency MEG Study

• Published in: Brain topography 2017-09, Vol.30 (5), p.673-684
• Main Authors: Wu, Caiyun, Xiang, Jing, Jiang, Wenwen, Huang, Shuyang, Gao, Yuan, Tang, Lu, Zhou, Yuchen, Wu, Di, Chen, Qiqi, Hu, Zheng, Wang, Xiaoshan
• Format: Article
• Language: English
• Subjects: Biomedical and Life Sciences; Biomedicine; Brain - diagnostic imaging; Brain - physiopathology; Child; Child, Preschool; Childhood; Children; Correlation analysis; Cortex (cingulate); Cortex (frontal); Cortex (parietal); Epilepsy; Epilepsy, Absence - diagnostic imaging; Epilepsy, Absence - physiopathology; Female; Humans; Magnetic Resonance Imaging; Magnetoencephalography; Male; Neurology; Neurosciences; Original Paper; Psychiatry; Studies
• ISSN: 0896-0267; 1573-6792
• DOI: 10.1007/s10548-017-0555-1

Using multi-frequency magnetoencephalography (MEG) data, we investigated whether the effective connectivity (EC) network of patients with childhood absence epilepsy (CAE) is altered during the inter-ictal period in comparison with healthy controls. MEG data from 13 untreated CAE patients and 10 healthy controls were recorded. Correlation analysis and Granger causality analysis were used to construct an EC network at the source level in eight frequency bands. Alterations in the spatial pattern and topology of the network in CAE were investigated by comparing the patients with the controls. The network pattern was altered mainly in 1–4 Hz, showing strong connections within the frontal cortex and weak connections in the anterior–posterior pathways. The EC involving the precuneus/posterior cingulate cortex (PC/PCC) significantly decreased in low-frequency bands. In addition, the parameters of graph theory were significantly altered in several low- and high-frequency bands. CAE patients display frequency-specific abnormalities in the network pattern even during the inter-ictal period, and the frontal cortex and PC/PCC might play crucial roles in the pathophysiology of CAE. The EC network of CAE patients was over-connective and random during the inter-ictal period. This study is the first to reveal the frequency-specific alteration in the EC network during the inter-ictal period in CAE patients. Multiple-frequency MEG data are useful in investigating the pathophysiology of CAE, which can serve as new biomarkers of this disorder.