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Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women
Functional neuroimaging data was collected while postpartum women and age-matched control women performed the Remember/Know judgment task in the functional magnetic resonance imaging scanner. This data provides information about functional connectivity patterns across the subjective recollection net...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6139472/ https://www.ncbi.nlm.nih.gov/pubmed/30225283 http://dx.doi.org/10.1016/j.dib.2018.05.070 |
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author | Nah, Yoonjin Shin, Na-Young Yi, Sehjung Lee, Seung-Koo Han, Sanghoon |
author_facet | Nah, Yoonjin Shin, Na-Young Yi, Sehjung Lee, Seung-Koo Han, Sanghoon |
author_sort | Nah, Yoonjin |
collection | PubMed |
description | Functional neuroimaging data was collected while postpartum women and age-matched control women performed the Remember/Know judgment task in the functional magnetic resonance imaging scanner. This data provides information about functional connectivity patterns across the subjective recollection networks that were informative in differentiating the postpartum women from control women. Classification performances based on machine learning algorithms and descriptions of functional connectivity patterns that derived the peak classification accuracy are reported in this article. All other results from our study have been reported in Nah et al. (2018) [1]. |
format | Online Article Text |
id | pubmed-6139472 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-61394722018-09-17 Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women Nah, Yoonjin Shin, Na-Young Yi, Sehjung Lee, Seung-Koo Han, Sanghoon Data Brief Neuroscience Functional neuroimaging data was collected while postpartum women and age-matched control women performed the Remember/Know judgment task in the functional magnetic resonance imaging scanner. This data provides information about functional connectivity patterns across the subjective recollection networks that were informative in differentiating the postpartum women from control women. Classification performances based on machine learning algorithms and descriptions of functional connectivity patterns that derived the peak classification accuracy are reported in this article. All other results from our study have been reported in Nah et al. (2018) [1]. Elsevier 2018-05-18 /pmc/articles/PMC6139472/ /pubmed/30225283 http://dx.doi.org/10.1016/j.dib.2018.05.070 Text en © 2018 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 | Neuroscience Nah, Yoonjin Shin, Na-Young Yi, Sehjung Lee, Seung-Koo Han, Sanghoon Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title | Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title_full | Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title_fullStr | Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title_full_unstemmed | Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title_short | Data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
title_sort | data on subjective recollection effects reflected in large-scale functional connectivity patterns in postpartum women |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6139472/ https://www.ncbi.nlm.nih.gov/pubmed/30225283 http://dx.doi.org/10.1016/j.dib.2018.05.070 |
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