Department of Neurology, Department of Biomedical Engineering, University of Michigan, United States.
Department of Mathematics and Statistics, Center of Systems Neuroscience, Boston University, United States.
Epilepsy Res. 2020 Jan;159:106255. doi: 10.1016/j.eplepsyres.2019.106255. Epub 2019 Dec 9.
In recent years there has been increasing interest in applying network science tools to EEG data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly session of the Engineering and Neurostimulation Special Interest Group focused on emerging, translational technologies to analyze seizure networks. Each speaker demonstrated practical examples of how network tools can be utilized in clinical care and provide additional data to help care for patients with intractable epilepsy. The groups presented advances using tools from functional connectivity, control theory, and graph theory to analyze human EEG data. These tools have great potential to augment clinical interpretation of EEG signals.
近年来，人们越来越感兴趣地将网络科学工具应用于 EEG 数据。在 2018 年新奥尔良举行的美国癫痫学会会议上，神经工程和神经刺激特别兴趣小组的年度会议重点关注新兴的转化技术，以分析癫痫发作网络。每位演讲者都展示了网络工具如何在临床护理中得到实际应用的实例，并提供了额外的数据来帮助治疗难治性癫痫患者。这些小组介绍了使用功能连接、控制理论和图论工具来分析人类 EEG 数据的进展。这些工具具有极大的潜力，可以增强对 EEG 信号的临床解释。
