Literature DB >> 28286918

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

Caiyun Wu1, Jing Xiang2, Wenwen Jiang1, Shuyang Huang1, Yuan Gao1, Lu Tang1, Yuchen Zhou1, Di Wu1, Qiqi Chen3, Zheng Hu4, Xiaoshan Wang5.   

Abstract

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.

Entities:  

Keywords:  Childhood absence epilepsy; Effective connectivity; Graph theory; Low- and high-frequency bands; Magnetoencephalography

Mesh:

Year:  2017        PMID: 28286918     DOI: 10.1007/s10548-017-0555-1

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  8 in total

Review 1.  The epileptic network and cognition: What functional connectivity is teaching us about the childhood epilepsies.

Authors:  Joshua J Bear; Kevin E Chapman; Jason R Tregellas
Journal:  Epilepsia       Date:  2019-06-27       Impact factor: 5.864

2.  Multifrequency Dynamics of Cortical Neuromagnetic Activity Underlying Seizure Termination in Absence Epilepsy.

Authors:  Jintao Sun; Yuan Gao; Ailiang Miao; Chuanyong Yu; Lu Tang; Shuyang Huang; Caiyun Wu; Qi Shi; Tingting Zhang; Yihan Li; Yulei Sun; Xiaoshan Wang
Journal:  Front Hum Neurosci       Date:  2020-06-26       Impact factor: 3.169

Review 3.  Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies?

Authors:  Thandar Aung; Jeffrey R Tenney; Anto I Bagić
Journal:  Front Neurol       Date:  2022-04-27       Impact factor: 4.086

Review 4.  Recent Advances in Neuroimaging of Epilepsy.

Authors:  Adam M Goodman; Jerzy P Szaflarski
Journal:  Neurotherapeutics       Date:  2021-05-03       Impact factor: 7.620

5.  Differences Between Interictal and Ictal Generalized Spike-Wave Discharges in Childhood Absence Epilepsy: A MEG Study.

Authors:  Qi Shi; Tingting Zhang; Ailiang Miao; Jintao Sun; Yulei Sun; Qiqi Chen; Zheng Hu; Jing Xiang; Xiaoshan Wang
Journal:  Front Neurol       Date:  2020-01-24       Impact factor: 4.003

6.  A computational biomarker of juvenile myoclonic epilepsy from resting-state MEG.

Authors:  Marinho A Lopes; Dominik Krzemiński; Khalid Hamandi; Krish D Singh; Naoki Masuda; John R Terry; Jiaxiang Zhang
Journal:  Clin Neurophysiol       Date:  2021-02-04       Impact factor: 3.708

7.  Altered effective connectivity in migraine patients during emotional stimuli: a multi-frequency magnetoencephalography study.

Authors:  Jing Ren; Qun Yao; Minjie Tian; Feng Li; Yueqiu Chen; Qiqi Chen; Jing Xiang; Jingping Shi
Journal:  J Headache Pain       Date:  2022-01-15       Impact factor: 7.277

8.  Predicting seizure outcome of vagus nerve stimulation using MEG-based network topology.

Authors:  Abbas Babajani-Feremi; Negar Noorizadeh; Basanagoud Mudigoudar; James W Wheless
Journal:  Neuroimage Clin       Date:  2018-06-18       Impact factor: 4.881

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.