Mean field modelling of human EEG: Application to Epilepsy Seizure Prediction

癫痫是困扰人类的最常见的神经系统疾病之一。几乎每个公众都直接或间接地知道某人患有某种类型的癫痫。这项拟议研究的目的是利用数学建模和分析来开发一种算法，该算法能够通过分析从患者大脑记录的电信号来预测癫痫活动的开始。该项目将包括开发一个能够再现临床数据中观察到的动力学类型的数学模型，并使用这些模型，项目组将了解健康状态是如何变成癫痫状态的，并利用这些知识开发算法，可以从伦敦丹麦希尔国王学院医院癫痫中心记录的临床数据集中提取这些信息。该项目是数学家和临床医生之间令人兴奋的合作，它将导致更好地理解和可能治疗这种令人衰弱的疾病。

Epilepsy is one of the most common neurological disorders to afflict human beings. Almost every member of the public knows, either directly or indirectly, someone who has epilepsy of some description. The aim of the proposed research is to use mathematical modelling and analysis to develop an algorithm which is capable of predicting the onset of epileptic activity via analysis of electrical signals recorded from the brain of the patient. The project will consist of developing a mathematical model that is capable of reproducing the types of dynamics observed in clinical data and using these models, the project team will develop an understanding of how healthy states become seizure states and use this knowledge to develop algorithms that can extract this information from clinical data sets recorded at the Centre for Epilepsy at King's College Hospital in Denmark Hill, London. The project is an exciting collaboration between mathematicians and clinicians which will lead to a better understanding and possible treatment of a debilitating medical condition.