癫痫
神经刺激
脑电图
计算机科学
会话(web分析)
数据科学
神经科学
网络分析
心理学
人工智能
万维网
工程类
刺激
电气工程
作者
William C. Stacey,Mark Kramer,Kristin M. Gunnarsdottir,Jorge González-Martínez,Kareem A. Zaghloul,Sara K. Inati,Sridevi V. Sarma,Jennifer Stiso,Ankit N. Khambhati,Danielle S. Bassett,Rachel J. Smith,Virginia B. Liu,Beth A. Lopour,Richard J. Staba
标识
DOI:10.1016/j.eplepsyres.2019.106255
摘要
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.
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