Time-course of cortical networks involved in working memory

Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during pe...

Descripción completa

Detalles Bibliográficos
Autores principales: Luu, Phan, Caggiano, Daniel M., Geyer, Alexandra, Lewis, Jenn, Cohn, Joseph, Tucker, Don M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905217/
https://www.ncbi.nlm.nih.gov/pubmed/24523686
http://dx.doi.org/10.3389/fnhum.2014.00004
_version_ 1782301311067226112
author Luu, Phan
Caggiano, Daniel M.
Geyer, Alexandra
Lewis, Jenn
Cohn, Joseph
Tucker, Don M.
author_facet Luu, Phan
Caggiano, Daniel M.
Geyer, Alexandra
Lewis, Jenn
Cohn, Joseph
Tucker, Don M.
author_sort Luu, Phan
collection PubMed
description Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during performance of a standard WM task, the n-back task, and a blend of principal components analysis and independent components analysis (PCA/ICA) to statistically identify networks of WM and their time courses. Results reveal a visual cortex centric network, that also includes the posterior cingulate cortex, that is active prior to stimulus onset and that appears to reflect anticipatory, attention-related processes. After stimulus onset, the ventromedial prefrontal cortex, lateral prefrontal prefrontal cortex, and temporal poles become associated with the prestimulus network. This second network appears to reflect executive control processes. Following activation of the second network, the cortices of the temporo-parietal junction with the temporal lobe structures seen in the first and second networks re-engage. This third network appears to reflect activity of the ventral attention network involved in control of attentional reorientation. The results point to important temporal features of network dynamics that integrate multiple subsystems of the ventral attention network with the default mode network in the performance of working memory tasks.
format Online
Article
Text
id pubmed-3905217
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-39052172014-02-12 Time-course of cortical networks involved in working memory Luu, Phan Caggiano, Daniel M. Geyer, Alexandra Lewis, Jenn Cohn, Joseph Tucker, Don M. Front Hum Neurosci Neuroscience Working memory (WM) is one of the most studied cognitive constructs. Although many neuroimaging studies have identified brain networks involved in WM, the time course of these networks remains unclear. In this paper we use dense-array electroencephalography (dEEG) to capture neural signals during performance of a standard WM task, the n-back task, and a blend of principal components analysis and independent components analysis (PCA/ICA) to statistically identify networks of WM and their time courses. Results reveal a visual cortex centric network, that also includes the posterior cingulate cortex, that is active prior to stimulus onset and that appears to reflect anticipatory, attention-related processes. After stimulus onset, the ventromedial prefrontal cortex, lateral prefrontal prefrontal cortex, and temporal poles become associated with the prestimulus network. This second network appears to reflect executive control processes. Following activation of the second network, the cortices of the temporo-parietal junction with the temporal lobe structures seen in the first and second networks re-engage. This third network appears to reflect activity of the ventral attention network involved in control of attentional reorientation. The results point to important temporal features of network dynamics that integrate multiple subsystems of the ventral attention network with the default mode network in the performance of working memory tasks. Frontiers Media S.A. 2014-01-29 /pmc/articles/PMC3905217/ /pubmed/24523686 http://dx.doi.org/10.3389/fnhum.2014.00004 Text en Copyright © 2014 Luu, Caggiano, Geyer, Lewis, Cohn and Tucker. http://creativecommons.org/licenses/by/3.0/ 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) or licensor 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
Luu, Phan
Caggiano, Daniel M.
Geyer, Alexandra
Lewis, Jenn
Cohn, Joseph
Tucker, Don M.
Time-course of cortical networks involved in working memory
title Time-course of cortical networks involved in working memory
title_full Time-course of cortical networks involved in working memory
title_fullStr Time-course of cortical networks involved in working memory
title_full_unstemmed Time-course of cortical networks involved in working memory
title_short Time-course of cortical networks involved in working memory
title_sort time-course of cortical networks involved in working memory
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905217/
https://www.ncbi.nlm.nih.gov/pubmed/24523686
http://dx.doi.org/10.3389/fnhum.2014.00004
work_keys_str_mv AT luuphan timecourseofcorticalnetworksinvolvedinworkingmemory
AT caggianodanielm timecourseofcorticalnetworksinvolvedinworkingmemory
AT geyeralexandra timecourseofcorticalnetworksinvolvedinworkingmemory
AT lewisjenn timecourseofcorticalnetworksinvolvedinworkingmemory
AT cohnjoseph timecourseofcorticalnetworksinvolvedinworkingmemory
AT tuckerdonm timecourseofcorticalnetworksinvolvedinworkingmemory