癫痫是一种伴随短暂认知损伤的大脑疾病，由于病理机制的异质性，导致其缺乏临床诊断和治疗评价的客观度量。多通道脑电记录是检测大脑状态的重要手段。本文采用复杂网络可视化的方法对癫痫患者大脑功能状态进行研究，利用相位锁定值方法从癫痫患者的静息态皮层脑电图（EEG）信号中提取出加权频率依赖的复杂网络，使用Pajek软件和最小生成树算法对癫痫患者大脑的复杂网络进行描述，可为量化大脑特征提供系统化、全局化的可视化思路，未来可以为进一步辅助诊断提供技术支持。%Epilepsy is a kind of brain disease accompanied by transient cognitive impairment. The objective metrics for clinical diagnosis and treatment evaluation of the disease is deficient because of the heterogeneity of the pathological mechanism. Multi-channel EEG (Electroencephalogram) recording is an important technique for monitoring of brain functions. In this paper, complex network visualization is adopted to investigate the overall state of brain functions in patients with epilepsy. Transient phase locking values are brought in to extract weighted frequency-dependent complex networks from resting state cortical EEG signals of epilepsy patients, then Pajek software and minimum spanning tree algorithm are introduced for depiction of these complex brain networks, which provides a systematic and global visualization framework for quantitation of brain characteristics of epilepsy patients, and lays a solid technical foundation for development of intuitive as well as effective auxiliary diagnostic tools for the future.
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