scholarly journals Interictal electroencephalographic functional network topology in drug‐resistant and well‐controlled idiopathic generalized epilepsy

Epilepsia ◽  
2021 ◽  
Vol 62 (2) ◽  
pp. 492-503
Author(s):  
Emily J. Pegg ◽  
Jason R. Taylor ◽  
Petroula Laiou ◽  
Mark Richardson ◽  
Rajiv Mohanraj
Keyword(s):  
Network Topology ◽  
Functional Network ◽  
Drug Resistant ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy

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

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.

Depressive disorder in a boy with drug resistant idiopathic generalized epilepsy

2012 ◽  
Vol 24 (2) ◽  
pp. 191-192
Author(s):  
I. Leo⁎ ◽  
D. Cordelli ◽  
V. Gentile ◽  
A. Barbieri ◽  
V. Marchiani ◽  
...  
Keyword(s):  
Depressive Disorder ◽  
Drug Resistant ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy

scholarly journals Efficacy of Vagal Nerve Stimulation for Drug-Resistant Epilepsy: Is it the Stimulation or Medication?

2017 ◽  
Vol 44 (5) ◽  
pp. 532-537 ◽  
Author(s):  
Jaylynn Arcand ◽  
Karen Waterhouse ◽  
Lizbeth Hernandez-Ronquillo ◽  
Aleksander Vitali ◽  
Jose F. Tellez-Zenteno
Keyword(s):  
Nerve Stimulation ◽  
Vagus Nerve Stimulation ◽  
Drug Resistant ◽  
Idiopathic Generalized Epilepsy ◽  
Drug Resistant Epilepsy ◽  
Generalized Epilepsy ◽  
Patients With Epilepsy ◽  
Seizure Classification

AbstractBackground: Vagus nerve stimulation (VNS) therapy has been widely recognized as an alternative for the treatment of drug-resistant epilepsy, although modification of antiepileptic drugs (AEDs) during VNS treatment could explain the improvement in patients. Methods: We retrospectively assessed the efficacy of VNS in 30 adult patients with epilepsy treated with >6 months of follow-up. The criteria for implantation were the following: (1) not a candidate for resective epilepsy surgery, (2) drug-resistant epilepsy, (3) impairment of quality of life, (4) no other option of treatment, and (5) patients with idiopathic generalized epilepsy who fail to be controlled with appropriate AEDs. We assessed sociodemographics, seizure etiology, seizure classification, and AEDs used during treatment with VNS. We assessed adverse effects and efficacy. Responder rate was defined as >50% seizure improvement from baseline. Results: Thirty patients (females, 18; males, 12; age, 35.1±13.3 years) were included. After 6, 12, 24, and 36 months of follow-up, the response rates were: 13/30 (43%), 13/27 (48%), 9/22 (41%), and 8/16 (50%), respectively; none was seizure free. Fifty-seven percent, 33%, 59%, and 81% of patients had changes of medication type or dose at 6, 12, 24, and 36 months respectively. In the majority of patients, the change of medication consisted of an increase in the dose of AEDs. Conclusions: Our study shows that VNS is an effective therapy, although significant changes in medications were done along with the therapy; therefore, the real effect of VNS could be controversial.

scholarly journals Multimodal connectome biomarkers of cognitive and affective dysfunction in the common epilepsies

2021 ◽  
Author(s):  
raul rodriguez-cruces ◽  
Jessica Royer ◽  
Sara Lariviere ◽  
Danielle S Bassett ◽  
Lorenzo Caciagli ◽  
...  
Keyword(s):  
Future Research ◽  
Drug Resistant ◽  
Cortical Circuits ◽  
Idiopathic Generalized Epilepsy ◽  
Behavioral Challenges ◽  
Cognitive Domains ◽  
The Common ◽  
Neurological Conditions ◽  
Drug Resistant Epilepsy ◽  
Generalized Epilepsy

Epilepsy is one of the most common chronic neurological conditions, traditionally defined as a disorder of recurrent seizures. Cognitive and affective dysfunctions are increasingly recognized as core disease dimensions and can affect patient wellbeing sometimes more than the seizures themselves. Connectome- based approaches hold immense promise for revealing mechanisms that contribute to dysfunction, and to identify biomarkers. Our review discusses emerging multimodal neuroimaging and connectomics studies that highlight network substrates of cognitive/affective dysfunction in the common epilepsies. We first overview work in drug-resistant epilepsy syndromes i.e., temporal lobe epilepsy related to mesiotemporal sclerosis (TLE) and extratemporal epilepsy (ETE) related to malformations of cortical development. While these are traditionally conceptualized as ‘focal’ epilepsies, many patients present with broad structural and functional anomalies. Moreover, the extent of distributed changes contributes to difficulties in multiple cognitive domains as well as affective-behavioral challenges. We will also review work in idiopathic generalized epilepsy (IGE), a class of generalized epilepsy syndromes that involve subcortico-cortical circuits. Overall, neuroimaging and network neuroscience studies point to both shared and syndrome specific connectome signatures of dysfunction across TLE, ETE, and IGE. Lastly, we point to current gaps in the literature and formulate recommendations for future research.

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy

2020 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Erin C. Conrad ◽  
Nanak Chugh ◽  
Taneeta M. Ganguly ◽  
James J. Gugger ◽  
Etsegenet F. Tizazu ◽  
...  
Keyword(s):  
Drug Resistant ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy
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