Frequency-dependent amplitude alterations of resting-state spontaneous fluctuations in idiopathic generalized epilepsy

Objective: Idiopathic generalized epilepsy (IGE) involves aberrant organization and functioning of large-scale brain networks. This study aims to investigate whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with IGE.Methods: Three groups of participants were chosen for this study (namely IGE-Seizure, IGE-Seizure Free, and Healthy Controls). EEG microstate analysis on the resting-state EEG datasets was conducted for all participants. The average duration (“Duration”), the average number of microstates per second (“Frequency”), as well as the percentage of total analysis time occupied in that state (“Coverage”) of the EEG microstate were compared among the three groups.Results: For microstate classes B and D, the differences in Duration, Frequency, and Coverage among the three groups were not statistically significant. Both Frequency and Coverage of microstate class A were statistically significantly larger in the IGE-Seizure group than in the other two groups. The Duration and Coverage of microstate class C were statistically significantly smaller in the IGE-Seizure group than those in the other two groups.Conclusions: The Microstate class A was regarded as a sensorimotor network and Microstate class C was mainly related to the salience network, this study indicated an altered sensorimotor and salience network in patients with IGE, especially in those who had experienced seizures in the past 2 years, while the visual and attention networks seemed to be intact.Significance: The temporal dynamics of resting-state networks were studied through EEG microstate analysis in patients with IGE, which is expected to generate indices that could be utilized in clinical researches of epilepsy.

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A computational biomarker of idiopathic generalized epilepsy from resting state EEG

Epilepsia ◽

10.1111/epi.13481 ◽

2016 ◽

Vol 57 (10) ◽

pp. e200-e204 ◽

Cited By ~ 18

Author(s):

Helmut Schmidt ◽

Wessel Woldman ◽

Marc Goodfellow ◽

Fahmida A. Chowdhury ◽

Michalis Koutroumanidis ◽

...

Keyword(s):

Resting State ◽

Idiopathic Generalized Epilepsy ◽

Generalized Epilepsy

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Resting state basal ganglia network in idiopathic generalized epilepsy

Human Brain Mapping ◽

10.1002/hbm.21286 ◽

2011 ◽

Vol 33 (6) ◽

pp. 1279-1294 ◽

Cited By ~ 75

Author(s):

Cheng Luo ◽

Qifu Li ◽

Yang Xia ◽

Xu Lei ◽

Kaiqing Xue ◽

...

Keyword(s):

Basal Ganglia ◽

Resting State ◽

Idiopathic Generalized Epilepsy ◽

Generalized Epilepsy

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Functional network topology in drug resistant and well-controlled idiopathic generalized epilepsy: a resting state functional MRI study

Brain Communications ◽

10.1093/braincomms/fcab196 ◽

2021 ◽

Vol 3 (3) ◽

Author(s):

Emily J Pegg ◽

Andrea McKavanagh ◽

R Martyn Bracewell ◽

Yachin Chen ◽

Kumar Das ◽

...

Keyword(s):

Network Topology ◽

Resting State ◽

Betweenness Centrality ◽

Path Length ◽

Seizure Control ◽

Drug Resistant ◽

Idiopathic Generalized Epilepsy ◽

Characteristic Path Length ◽

Graph Theoretic ◽

Generalized Epilepsy

Abstract Despite an increasing number of drug treatment options for people with idiopathic generalized epilepsy (IGE), drug resistance remains a significant issue and the mechanisms underlying it remain poorly understood. Previous studies have largely focused on potential cellular or genetic explanations for drug resistance. However, epilepsy is understood to be a network disorder and there is a growing body of literature suggesting altered topology of large-scale resting networks in people with epilepsy compared with controls. We hypothesize that network alterations may also play a role in seizure control. The aim of this study was to compare resting state functional network structure between well-controlled IGE (WC-IGE), drug resistant IGE (DR-IGE) and healthy controls. Thirty-three participants with IGE (10 with WC-IGE and 23 with DR-IGE) and 34 controls were included. Resting state functional MRI networks were constructed using the Functional Connectivity Toolbox (CONN). Global graph theoretic network measures of average node strength (an equivalent measure to mean degree in a network that is fully connected), node strength distribution variance, characteristic path length, average clustering coefficient, small-world index and average betweenness centrality were computed. Graphs were constructed separately for positively weighted connections and for absolute values. Individual nodal values of strength and betweenness centrality were also measured and ‘hub nodes’ were compared between groups. Outcome measures were assessed across the three groups and between both groups with IGE and controls. The IGE group as a whole had a higher average node strength, characteristic path length and average betweenness centrality. There were no clear differences between groups according to seizure control. Outcome metrics were sensitive to whether negatively correlated connections were included in network construction. There were no clear differences in the location of ‘hub nodes’ between groups. The results suggest that, irrespective of seizure control, IGE interictal network topology is more regular and has a higher global connectivity compared to controls, with no alteration in hub node locations. These alterations may produce a resting state network that is more vulnerable to transitioning to the seizure state. It is possible that the lack of apparent influence of seizure control on network topology is limited by challenges in classifying drug response. It is also demonstrated that network topological features are influenced by the sign of connectivity weights and therefore future methodological work is warranted to account for anticorrelations in graph theoretic studies.

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