The importance of modeling epileptic seizure dynamics as spatio-temporal patterns

被引:66
|
作者
Baier, Gerold [1 ]
Goodfellow, Marc [1 ,2 ]
Taylor, Peter N. [1 ]
Wang, Yujiang [1 ]
Garry, Daniel J. [1 ]
机构
[1] Univ Manchester, Manchester Interdisciplinary Bioctr, DTC Integrat Syst Biol, Manchester M1 7DN, Lancs, England
[2] Univ Manchester, Sch Math, Ctr Interdisciplinary Computat & Dynam Anal, Manchester M1 7DN, Lancs, England
来源
FRONTIERS IN PHYSIOLOGY | 2012年 / 3卷
基金
英国生物技术与生命科学研究理事会; 英国工程与自然科学研究理事会;
关键词
computational modeling; electroencephalogram (EEG); epilepsy; heterogeneity; spatio-temporal patterns; NEURAL MASS MODEL; ABSENCE SEIZURES; EEG; INTEGRATION; TRANSITION; SPIKE; ILAE;
D O I
10.3389/fphys.2012.00281
中图分类号
Q4 [生理学];
学科分类号
071003 ;
摘要
The occurrence of seizures is the common feature across the spectrum of epileptic disorders. We describe how the use of mechanistic neural population models leads to novel insight into the dynamic mechanisms underlying two important types of epileptic seizures. We specifically stress the need for a spatio-temporal description of the rhythms to deal with the complexity of the pathophenotype. Adapted to functional and structural patient data, the macroscopic models may allow a patient-specific description of seizures and prediction of treatment outcome.
引用
收藏
页数:7
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