癫痫是一种常见的神经疾病,目前常见的药物治疗和手术治疗方法都存在一定的现实问题，使众多癫痫患者仍无法得到有效治疗。本项目针对癫痫的临床治疗需求，从两方面研究了癫痫大脑活动的探测方法。一方面从空间域上对癫痫活动进行准确地探测，即癫痫病灶的源定位，本项目提出了一种新的基于小波包变换的脑电源定位算法，并通过仿真研究和临床实验来验证该癫痫病灶源定位方法在临床实际使用中的有效性。另一方面从时间域上对癫痫活动进行准确的早期探测，即癫痫发作的预测，本项目拟结合大脑神经信号同步分析和大脑神经信息流分析，在量化不同脑区间关系以刻画其相互作用的基础上，进行癫痫发作预测的研究，并依靠临床实验研究来证明其能够提高癫痫预测的有效性及可靠性。预计该课题的研究成果能够为癫痫患者的有效治疗和治愈提供新的思路和理论基础。项目申请人已具有利用癫痫发作间期棘波进行脑电源定位的研究经历，并已获得新的源定位算法的初步仿真研究结果。

Epilepsy is one of the most common and devastating neurological disorders, afflicting more than 50 million individuals worldwide. For epilepsy patients who do not achieve complete seizure control, the seizures often lead to threaten life, especially if they occur while the person is driving, swimming, climbing heights, or alone.Apart from the risk of serious injury, there is often an intense feeling of helpness that has a strong impact on the everyday life of a patient. Thereby, a method capable of removing or controlling the occurrence of seizures could significantly improve the quality of life for epilepsy patients. Nowadays, majority of epilepsy patients could achieve sufficient seizure control from anticonvulsive medication and resective surgery, but there are still some limitations with antiepileptic drugs treatment and surgical therapy. Thus, sufficient treatment is not currently available for a lot of patients with medically intractable epilepsy. This project will try to study the method of expolring brain electrical activity around seizure onset in two aspects, aiming at clinical epilepsy therapy. On the one hand, brain electrical activity around seizure onset will be explored in the spatial domain, i.e. EEG (electroencephalogram) source localization of epileptogenic zone. A new algorithm of EEG source localization based on wavelet packet transform will be proposed. Then the epileptic source will be stimulated by using dipole model and the validity of this EEG source localization algorithm will be evaluated in this simulation study. In the clinical experiments, the epielptogenic zone will be identified from the pre-operative and post-operative MR images in a cohort of epilepsy patients and the ability of source localization of this algorithm will be examined from EEG recording. On the other hand, the brain electrical activity of preictal state preceding a seizure onset will be accurately detected in the time domain, i.e. seizure prediction. In this research, seizure prediction will be analyzed in terms of the mechanisms of ictogenesis that take into consideration the complex spatiotemporal interactions between different brain regions in epilepsy. The methods will include neural signal synchronization anlaysis and neural information flow pattern analysis which reflect the nature of brain electrical activity in epilepsy. These methods can quantify relations between recording sites to characterize interaction among different brain regions. Furthermore, validity and reliability of these methods will be verified in clinical experiments.It is expected that the research results of this project can provide new ideas and theoretical foundations for both effective treatment and cure of epilepsy. In the end, the principle investigator has already had some experiences about EEG source localization using interictal spike in patients with partial epilepsy and obtained preliminary simulation results by using the new EEG source localization algorithm.