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A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity
We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792176/ https://www.ncbi.nlm.nih.gov/pubmed/26978040 http://dx.doi.org/10.1038/sdata.2016.16 |
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author | Huang, Lijie Huang, Taicheng Zhen, Zonglei Liu, Jia |
author_facet | Huang, Lijie Huang, Taicheng Zhen, Zonglei Liu, Jia |
author_sort | Huang, Lijie |
collection | PubMed |
description | We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103–189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven’s Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association. |
format | Online Article Text |
id | pubmed-4792176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-47921762016-04-04 A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity Huang, Lijie Huang, Taicheng Zhen, Zonglei Liu, Jia Sci Data Data Descriptor We present a test-retest dataset for evaluation of long-term reliability of measures from structural and resting-state functional magnetic resonance imaging (sMRI and rfMRI) scans. The repeated scan dataset was collected from 61 healthy adults in two sessions using highly similar imaging parameters at an interval of 103–189 days. However, as the imaging parameters were not completely identical, the reliability estimated from this dataset shall reflect the lower bounds of the true reliability of sMRI/rfMRI measures. Furthermore, in conjunction with other test-retest datasets, our dataset may help explore the impact of different imaging parameters on reliability of sMRI/rfMRI measures, which is especially critical for assessing datasets collected from multiple centers. In addition, intelligence quotient (IQ) was measured for each participant using Raven’s Advanced Progressive Matrices. The data can thus be used for purposes other than assessing reliability of sMRI/rfMRI alone. For example, data from each single session could be used to associate structural and functional measures of the brain with the IQ metrics to explore brain-IQ association. Nature Publishing Group 2016-03-15 /pmc/articles/PMC4792176/ /pubmed/26978040 http://dx.doi.org/10.1038/sdata.2016.16 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0 Metadata associated with this Data Descriptor is available at http://www.nature.com/sdata/ and is released under the CC0 waiver to maximize reuse. |
spellingShingle | Data Descriptor Huang, Lijie Huang, Taicheng Zhen, Zonglei Liu, Jia A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title | A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title_full | A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title_fullStr | A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title_full_unstemmed | A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title_short | A test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
title_sort | test-retest dataset for assessing long-term reliability of brain morphology and resting-state brain activity |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4792176/ https://www.ncbi.nlm.nih.gov/pubmed/26978040 http://dx.doi.org/10.1038/sdata.2016.16 |
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