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Spectral parameterization for studying neurodevelopment: How and why
A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for devel...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792072/ https://www.ncbi.nlm.nih.gov/pubmed/35074579 http://dx.doi.org/10.1016/j.dcn.2022.101073 |
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author | Ostlund, Brendan Donoghue, Thomas Anaya, Berenice Gunther, Kelley E. Karalunas, Sarah L. Voytek, Bradley Pérez-Edgar, Koraly E. |
author_facet | Ostlund, Brendan Donoghue, Thomas Anaya, Berenice Gunther, Kelley E. Karalunas, Sarah L. Voytek, Bradley Pérez-Edgar, Koraly E. |
author_sort | Ostlund, Brendan |
collection | PubMed |
description | A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization (“specparam”) algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; M(age) = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox. |
format | Online Article Text |
id | pubmed-8792072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87920722022-02-02 Spectral parameterization for studying neurodevelopment: How and why Ostlund, Brendan Donoghue, Thomas Anaya, Berenice Gunther, Kelley E. Karalunas, Sarah L. Voytek, Bradley Pérez-Edgar, Koraly E. Dev Cogn Neurosci Original Research A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization (“specparam”) algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; M(age) = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox. Elsevier 2022-01-15 /pmc/articles/PMC8792072/ /pubmed/35074579 http://dx.doi.org/10.1016/j.dcn.2022.101073 Text en © 2022 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Ostlund, Brendan Donoghue, Thomas Anaya, Berenice Gunther, Kelley E. Karalunas, Sarah L. Voytek, Bradley Pérez-Edgar, Koraly E. Spectral parameterization for studying neurodevelopment: How and why |
title | Spectral parameterization for studying neurodevelopment: How and why |
title_full | Spectral parameterization for studying neurodevelopment: How and why |
title_fullStr | Spectral parameterization for studying neurodevelopment: How and why |
title_full_unstemmed | Spectral parameterization for studying neurodevelopment: How and why |
title_short | Spectral parameterization for studying neurodevelopment: How and why |
title_sort | spectral parameterization for studying neurodevelopment: how and why |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792072/ https://www.ncbi.nlm.nih.gov/pubmed/35074579 http://dx.doi.org/10.1016/j.dcn.2022.101073 |
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