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Neurocognitive subprocesses of working memory performance
Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively in...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8563426/ https://www.ncbi.nlm.nih.gov/pubmed/34155599 http://dx.doi.org/10.3758/s13415-021-00924-7 |
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author | Lenartowicz, Agatha Truong, Holly Enriquez, Kristen D. Webster, Julia Pochon, Jean-Baptiste Rissman, Jesse Bearden, Carrie E. Loo, Sandra K. Bilder, Robert M. |
author_facet | Lenartowicz, Agatha Truong, Holly Enriquez, Kristen D. Webster, Julia Pochon, Jean-Baptiste Rissman, Jesse Bearden, Carrie E. Loo, Sandra K. Bilder, Robert M. |
author_sort | Lenartowicz, Agatha |
collection | PubMed |
description | Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13415-021-00924-7. |
format | Online Article Text |
id | pubmed-8563426 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-85634262021-11-15 Neurocognitive subprocesses of working memory performance Lenartowicz, Agatha Truong, Holly Enriquez, Kristen D. Webster, Julia Pochon, Jean-Baptiste Rissman, Jesse Bearden, Carrie E. Loo, Sandra K. Bilder, Robert M. Cogn Affect Behav Neurosci Research Article Working memory (WM) has been defined as the active maintenance and flexible updating of goal-relevant information in a form that has limited capacity and resists interference. Complex measures of WM recruit multiple subprocesses, making it difficult to isolate specific contributions of putatively independent subsystems. The present study was designed to determine whether neurophysiological indicators of proposed subprocesses of WM predict WM performance. We recruited 200 individuals defined by care-seeking status and measured neural responses using electroencephalography (EEG), while participants performed four WM tasks. We extracted spectral and time-domain EEG features from each task to quantify each of the hypothesized WM subprocesses: maintenance (storage of content), goal maintenance, and updating. We then used EEG measures of each subprocess as predictors of task performance to evaluate their contribution to WM. Significant predictors of WM capacity included contralateral delay activity and frontal theta, features typically associated with maintenance (storage of content) processes. In contrast, significant predictors of reaction time and its variability included contingent negative variation and the P3b, features typically associated with goal maintenance and updating. Broadly, these results suggest two principal dimensions that contribute to WM performance, tonic processes during maintenance contributing to capacity, and phasic processes during stimulus processing that contribute to response speed and variability. The analyses additionally highlight that reliability of features across tasks was greater (and comparable to that of WM performance) for features associated with stimulus processing (P3b and alpha), than with maintenance (gamma, theta and cross-frequency coupling). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.3758/s13415-021-00924-7. Springer US 2021-06-21 2021 /pmc/articles/PMC8563426/ /pubmed/34155599 http://dx.doi.org/10.3758/s13415-021-00924-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Lenartowicz, Agatha Truong, Holly Enriquez, Kristen D. Webster, Julia Pochon, Jean-Baptiste Rissman, Jesse Bearden, Carrie E. Loo, Sandra K. Bilder, Robert M. Neurocognitive subprocesses of working memory performance |
title | Neurocognitive subprocesses of working memory performance |
title_full | Neurocognitive subprocesses of working memory performance |
title_fullStr | Neurocognitive subprocesses of working memory performance |
title_full_unstemmed | Neurocognitive subprocesses of working memory performance |
title_short | Neurocognitive subprocesses of working memory performance |
title_sort | neurocognitive subprocesses of working memory performance |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8563426/ https://www.ncbi.nlm.nih.gov/pubmed/34155599 http://dx.doi.org/10.3758/s13415-021-00924-7 |
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