Evidence map›Paper›PMID 29593641›Full record

ArticleFrontiers in neurology2018

Localization of Epileptogenic Zone With the Correction of Pathological Networks.

Chuanzuo Yang, Guoming Luan, Qian Wang, Zhao Liu, Feng Zhai, Qingyun Wang

Abstract read
In one paragraph

Article in Frontiers in neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

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0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Bifurcations and bursting in the Epileptor.PLoS computational biology · 2024
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Chuanzuo YangDepartment of Dynamics and Control, Beihang University, Beijing, China.
Guoming LuanBeijing Key Laboratory of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
Qian WangBeijing Key Laboratory of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
Zhao LiuBeijing Key Laboratory of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
Feng ZhaiBeijing Key Laboratory of Epilepsy, Sanbo Brain Hospital, Capital Medical University, Beijing, China.
Qingyun WangDepartment of Dynamics and Control, Beihang University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with focal drug-resistant epilepsy are potential candidates for surgery. Stereo-electroencephalograph (SEEG) is often considered as the "gold standard" to identify the epileptogenic zone (EZ) that accounts for the onset and propagation of epileptiform discharges. However, visual analysis of SEEG still prevails in clinical practice. In addition, epilepsy is increasingly understood to be the result of network disorder, but the specific organization of the epileptic network is still unclear. Therefore, it is necessary to quantitatively localize the EZ and investigate the nature of epileptogenic networks. In this study, intracranial recordings from 10 patients were analyzed through adaptive directed transfer function, and the out-degree of effective network was selected as the principal indicator to localize the epileptogenic area. Furthermore, a coupled neuronal population model was used to qualitatively simulate electrical activity in the brain. By removing individual populations, virtual surgery adjusting the network organization could be performed. Results suggested that the accuracy and detection rate of the EZ localization were 82.86 and 85.29%, respectively. In addition, the same stage shared a relatively stable connectivity pattern, while the patterns changed with transition to different processes. Meanwhile, eight cases of simulations indicated that networks in the ictal stage were more likely to generate rhythmic spikes. This indicated the existence of epileptogenic networks, which could enhance local excitability and facilitate synchronization. The removal of the EZ could correct these pathological networks and reduce the amount of spikes by at least 75%. This might be one reason why accurate resection could reduce or even suppress seizures. This study provides novel insights into epilepsy and surgical treatments from the network perspective.

Indexed as

coupled neuronal population modelepileptogenic networksepileptogenic zone localizationrefractory focal epilepsystereo-electroencephalograph

Identifiers

PMID29593641
PMCPMC5861205

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