Characterization of High-Gamma Activity in Electrocorticographic Signals

Frontiers in Neuroscience

Neuroscience

Kyousuke Kamada¹  Josef Scharinger²  Peter Brunner³  Christoph Guger⁴  Christoph Kapeller⁴  Johannes Gruenwald⁵  Sebastian Sieghartsleitner⁵ 

[1] Department for Neurosurgery, Asahikawa Medical University, Asahikawa, Japan;Hokashin Group Megumino Hospital, Sapporo, Japan;Institute of Computational Perception, Johannes Kepler University, Linz, Austria;National Center for Adaptive Neurotechnologies, Albany, NY, United States;Department of Neurosurgery, Washington University School of Medicine, St. Louis, MO, United States;g.tec medical engineering GmbH, Schiedlberg, Austria;g.tec medical engineering GmbH, Schiedlberg, Austria;Institute of Computational Perception, Johannes Kepler University, Linz, Austria;

关键词: high-gamma activity;    electrocorticography;    brain-computer interface;    high-gamma frequency band;    biosignal processing;   

DOI  :  10.3389/fnins.2023.1206120

 received in 2023-04-14, accepted in 2023-07-10,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionElectrocorticographic (ECoG) high-gamma activity (HGA) is a widely recognized and robust neural correlate of cognition and behavior. However, fundamental signal properties of HGA, such as the high-gamma frequency band or temporal dynamics of HGA, have never been systematically characterized. As a result, HGA estimators are often poorly adjusted, such that they miss valuable physiological information.MethodsTo address these issues, we conducted a thorough qualitative and quantitative characterization of HGA in ECoG signals. Our study is based on ECoG signals recorded from 18 epilepsy patients while performing motor control, listening, and visual perception tasks. In this study, we first categorize HGA into HGA types based on the cognitive/behavioral task. For each HGA type, we then systematically quantify three fundamental signal properties of HGA: the high-gamma frequency band, the HGA bandwidth, and the temporal dynamics of HGA.ResultsThe high-gamma frequency band strongly varies across subjects and across cognitive/behavioral tasks. In addition, HGA time courses have lowpass character, with transients limited to 10 Hz. The task-related rise time and duration of these HGA time courses depend on the individual subject and cognitive/behavioral task. Task-related HGA amplitudes are comparable across the investigated tasks.DiscussionThis study is of high practical relevance because it provides a systematic basis for optimizing experiment design, ECoG acquisition and processing, and HGA estimation. Our results reveal previously unknown characteristics of HGA, the physiological principles of which need to be investigated in further studies.

【 授权许可】

Unknown   
Copyright © 2023 Gruenwald, Sieghartsleitner, Kapeller, Scharinger, Kamada, Brunner and Guger.