Literature DB >> 34677785

Interictal epileptiform discharges changed epilepsy-related brain network architecture in BECTS.

Xi-Jian Dai1,2, Yang Yang3, Yongjun Wang4.   

Abstract

To investigate directed information flow of epileptiform activity in benign epilepsy with centrotemporal spikes (BECTS) during ictal epileptiform discharges (IEDs) and non-IEDs periods. In this multi-center study, a total of 188 subjects, including 50 BECTS and 138 normal children's controls (NCs) from three different centers (Center 1: females/males, 38/55; mean age, 9.33 ± 2.6 years; Center 2: females/males,7/10; mean age, 8.59 ± 2.32 years; Center 3: females/males, 14/14; mean age, 13 ± 3.42 years) were recruited. The BECTS were classified into IEDs (females/males, 12/15; mean age, 8.15 ± 1.68 years) and non-IEDs (females/males, 10/13; mean age, 9.09 ± 1.98 years) subgroups depending on presence of central-temporal spikes from an EEG-fMRI examination. Three new methods, structural equation parametric modeling, dynamic causal modeling and granger causality density (GCD) were used to determine optimal network architectures for BECTS. Three multicentric NCs determined a reliable and consistent network architecture by structural equation parametric modeling method. Further analyses were used for IEDs and non-IEDs to determine the brain network architecture by structural equation parametric modeling, dynamic causal modeling and GCD, respectively. The brain network architecture of IEDs substate, non-IEDs substate and NCs are different. IEDs promoted the driving effect of the Rolandic areas with more output information flows, and increased the targeted effect of the top of pre-/post-central gyrus with more input information flows. The information flow arises from the Rolandic areas, and subsequently propagates to the top of pre-/post-central gyrus and thalamus. From non-IEDs status to IEDs status, the thalamus load may play an important role in the modulation and regulation of epileptiform activity. These findings shed new light on pathophysiological mechanism of directed localization of epileptiform activity in BECTS.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Benign epilepsy with centrotemporal spikes; Dynamic causal modeling; Effective connectivity; Granger causality density; Structural equation parametric modeling

Mesh:

Year:  2021        PMID: 34677785     DOI: 10.1007/s11682-021-00566-w

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.224


  44 in total

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Journal:  Epilepsia       Date:  2012-05       Impact factor: 5.864

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Authors:  Edward H Bertram; DeXing Zhang; John M Williamson
Journal:  Epilepsia       Date:  2007-11-19       Impact factor: 5.864

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Authors:  V Bouilleret; F Semah; F Chassoux; M Mantzaridez; A Biraben; R Trebossen; M-J Ribeiro
Journal:  Neurology       Date:  2008-01-15       Impact factor: 9.910

Review 9.  Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions.

Authors:  Maria Centeno; David W Carmichael
Journal:  Front Neurol       Date:  2014-07-04       Impact factor: 4.003

10.  BECTS Substate Classification by Granger Causality Density Based Support Vector Machine Model.

Authors:  Xi-Jian Dai; Qiang Xu; Jianping Hu; QiRui Zhang; Yin Xu; Zhiqiang Zhang; Guangming Lu
Journal:  Front Neurol       Date:  2019-11-14       Impact factor: 4.003

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