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Characterization of High-Gamma Activity in Electrocorticographic Signals

INTRODUCTION: Electrocorticographic (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 characte...

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Autores principales: Gruenwald, Johannes, Sieghartsleitner, Sebastian, Kapeller, Christoph, Scharinger, Josef, Kamada, Kyousuke, Brunner, Peter, Guger, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440607/
https://www.ncbi.nlm.nih.gov/pubmed/37609450
http://dx.doi.org/10.3389/fnins.2023.1206120
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author Gruenwald, Johannes
Sieghartsleitner, Sebastian
Kapeller, Christoph
Scharinger, Josef
Kamada, Kyousuke
Brunner, Peter
Guger, Christoph
author_facet Gruenwald, Johannes
Sieghartsleitner, Sebastian
Kapeller, Christoph
Scharinger, Josef
Kamada, Kyousuke
Brunner, Peter
Guger, Christoph
author_sort Gruenwald, Johannes
collection PubMed
description INTRODUCTION: Electrocorticographic (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. METHODS: To 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. RESULTS: The 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. DISCUSSION: This 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.
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spelling pubmed-104406072023-08-22 Characterization of High-Gamma Activity in Electrocorticographic Signals Gruenwald, Johannes Sieghartsleitner, Sebastian Kapeller, Christoph Scharinger, Josef Kamada, Kyousuke Brunner, Peter Guger, Christoph Front Neurosci Neuroscience INTRODUCTION: Electrocorticographic (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. METHODS: To 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. RESULTS: The 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. DISCUSSION: This 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. Frontiers Media S.A. 2023-08-07 /pmc/articles/PMC10440607/ /pubmed/37609450 http://dx.doi.org/10.3389/fnins.2023.1206120 Text en Copyright © 2023 Gruenwald, Sieghartsleitner, Kapeller, Scharinger, Kamada, Brunner and Guger. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Gruenwald, Johannes
Sieghartsleitner, Sebastian
Kapeller, Christoph
Scharinger, Josef
Kamada, Kyousuke
Brunner, Peter
Guger, Christoph
Characterization of High-Gamma Activity in Electrocorticographic Signals
title Characterization of High-Gamma Activity in Electrocorticographic Signals
title_full Characterization of High-Gamma Activity in Electrocorticographic Signals
title_fullStr Characterization of High-Gamma Activity in Electrocorticographic Signals
title_full_unstemmed Characterization of High-Gamma Activity in Electrocorticographic Signals
title_short Characterization of High-Gamma Activity in Electrocorticographic Signals
title_sort characterization of high-gamma activity in electrocorticographic signals
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440607/
https://www.ncbi.nlm.nih.gov/pubmed/37609450
http://dx.doi.org/10.3389/fnins.2023.1206120
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