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MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable
High frequency brain oscillations are associated with numerous cognitive and behavioral processes. Non-invasive measurements using electro-/magnetoencephalography (EEG/MEG) have revealed that high frequency neural signals are heritable and manifest changes with age as well as in neuropsychiatric ill...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405052/ https://www.ncbi.nlm.nih.gov/pubmed/27153980 http://dx.doi.org/10.1016/j.neuroimage.2016.05.006 |
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author | Tan, H.-R.M. Gross, J. Uhlhaas, P.J. |
author_facet | Tan, H.-R.M. Gross, J. Uhlhaas, P.J. |
author_sort | Tan, H.-R.M. |
collection | PubMed |
description | High frequency brain oscillations are associated with numerous cognitive and behavioral processes. Non-invasive measurements using electro-/magnetoencephalography (EEG/MEG) have revealed that high frequency neural signals are heritable and manifest changes with age as well as in neuropsychiatric illnesses. Despite the extensive use of EEG/MEG-measured neural oscillations in basic and clinical research, studies demonstrating test–retest reliability of power and frequency measures of neural signals remain scarce. Here, we evaluated the test–retest reliability of visually induced gamma (30–100 Hz) oscillations derived from sensor and source signals acquired over two MEG sessions. The study required participants (N = 13) to detect the randomly occurring stimulus acceleration while viewing a moving concentric grating. Sensor and source MEG measures of gamma-band activity yielded comparably strong reliability (average intraclass correlation, ICC = 0.861). Peak stimulus-induced gamma frequency (53–72 Hz) yielded the highest measures of stability (ICC(sensor) = 0.940; ICC(source) = 0.966) followed by spectral signal change (ICC(sensor) = 0.890; ICC(source) = 0.893) and peak frequency bandwidth (ICC(sensor) = 0.856; ICC(source) = 0.622). Furthermore, source-reconstruction significantly improved signal-to-noise for spectral amplitude of gamma activity compared to sensor estimates. Our assessments highlight that both sensor and source derived estimates of visually induced gamma-band oscillations from MEG signals are characterized by high test–retest reliability, with source derived oscillatory measures conferring an improvement in the stability of peak-frequency estimates. Importantly, our finding of high test–retest reliability supports the feasibility of pharma-MEG studies and longitudinal aging or clinical studies. |
format | Online Article Text |
id | pubmed-5405052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Academic Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54050522017-05-05 MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable Tan, H.-R.M. Gross, J. Uhlhaas, P.J. Neuroimage Article High frequency brain oscillations are associated with numerous cognitive and behavioral processes. Non-invasive measurements using electro-/magnetoencephalography (EEG/MEG) have revealed that high frequency neural signals are heritable and manifest changes with age as well as in neuropsychiatric illnesses. Despite the extensive use of EEG/MEG-measured neural oscillations in basic and clinical research, studies demonstrating test–retest reliability of power and frequency measures of neural signals remain scarce. Here, we evaluated the test–retest reliability of visually induced gamma (30–100 Hz) oscillations derived from sensor and source signals acquired over two MEG sessions. The study required participants (N = 13) to detect the randomly occurring stimulus acceleration while viewing a moving concentric grating. Sensor and source MEG measures of gamma-band activity yielded comparably strong reliability (average intraclass correlation, ICC = 0.861). Peak stimulus-induced gamma frequency (53–72 Hz) yielded the highest measures of stability (ICC(sensor) = 0.940; ICC(source) = 0.966) followed by spectral signal change (ICC(sensor) = 0.890; ICC(source) = 0.893) and peak frequency bandwidth (ICC(sensor) = 0.856; ICC(source) = 0.622). Furthermore, source-reconstruction significantly improved signal-to-noise for spectral amplitude of gamma activity compared to sensor estimates. Our assessments highlight that both sensor and source derived estimates of visually induced gamma-band oscillations from MEG signals are characterized by high test–retest reliability, with source derived oscillatory measures conferring an improvement in the stability of peak-frequency estimates. Importantly, our finding of high test–retest reliability supports the feasibility of pharma-MEG studies and longitudinal aging or clinical studies. Academic Press 2016-08-15 /pmc/articles/PMC5405052/ /pubmed/27153980 http://dx.doi.org/10.1016/j.neuroimage.2016.05.006 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tan, H.-R.M. Gross, J. Uhlhaas, P.J. MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title | MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title_full | MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title_fullStr | MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title_full_unstemmed | MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title_short | MEG sensor and source measures of visually induced gamma-band oscillations are highly reliable |
title_sort | meg sensor and source measures of visually induced gamma-band oscillations are highly reliable |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5405052/ https://www.ncbi.nlm.nih.gov/pubmed/27153980 http://dx.doi.org/10.1016/j.neuroimage.2016.05.006 |
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