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Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consisten...

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Autores principales: Kumar, Wupadrasta Santosh, Manikandan, Keerthana, Murty, Dinavahi V P S, Ramesh, Ranjini Garani, Purokayastha, Simran, Javali, Mahendra, Rao, Naren Prahalada, Ray, Supratim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790174/
https://www.ncbi.nlm.nih.gov/pubmed/35088052
http://dx.doi.org/10.1093/texcom/tgab066
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author Kumar, Wupadrasta Santosh
Manikandan, Keerthana
Murty, Dinavahi V P S
Ramesh, Ranjini Garani
Purokayastha, Simran
Javali, Mahendra
Rao, Naren Prahalada
Ray, Supratim
author_facet Kumar, Wupadrasta Santosh
Manikandan, Keerthana
Murty, Dinavahi V P S
Ramesh, Ranjini Garani
Purokayastha, Simran
Javali, Mahendra
Rao, Naren Prahalada
Ray, Supratim
author_sort Kumar, Wupadrasta Santosh
collection PubMed
description Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20–35 Hz) and fast gamma (36–66 Hz) oscillations in subjects (n = 40) (age: 50–88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8–12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification.
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spelling pubmed-87901742022-01-26 Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG Kumar, Wupadrasta Santosh Manikandan, Keerthana Murty, Dinavahi V P S Ramesh, Ranjini Garani Purokayastha, Simran Javali, Mahendra Rao, Naren Prahalada Ray, Supratim Cereb Cortex Commun Original Article Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer’s Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20–35 Hz) and fast gamma (36–66 Hz) oscillations in subjects (n = 40) (age: 50–88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8–12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification. Oxford University Press 2022-01-07 /pmc/articles/PMC8790174/ /pubmed/35088052 http://dx.doi.org/10.1093/texcom/tgab066 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kumar, Wupadrasta Santosh
Manikandan, Keerthana
Murty, Dinavahi V P S
Ramesh, Ranjini Garani
Purokayastha, Simran
Javali, Mahendra
Rao, Naren Prahalada
Ray, Supratim
Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title_full Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title_fullStr Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title_full_unstemmed Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title_short Stimulus-Induced Narrowband Gamma Oscillations are Test–Retest Reliable in Human EEG
title_sort stimulus-induced narrowband gamma oscillations are test–retest reliable in human eeg
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790174/
https://www.ncbi.nlm.nih.gov/pubmed/35088052
http://dx.doi.org/10.1093/texcom/tgab066
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