Cargando…

Efficient evaluation of the Open QC task fMRI dataset

This article is an evaluation of the task dataset as part of the Demonstrating Quality Control (QC) Procedures in fMRI (FMRI Open QC Project) methodological research topic. The quality of both the task and fMRI aspects of the dataset are summarized in concise reports created with R, AFNI, and knitr....

Descripción completa

Detalles Bibliográficos
Autor principal: Etzel, Joset A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406291/
https://www.ncbi.nlm.nih.gov/pubmed/37554632
http://dx.doi.org/10.3389/fnimg.2023.1070274
_version_ 1785085720303501312
author Etzel, Joset A.
author_facet Etzel, Joset A.
author_sort Etzel, Joset A.
collection PubMed
description This article is an evaluation of the task dataset as part of the Demonstrating Quality Control (QC) Procedures in fMRI (FMRI Open QC Project) methodological research topic. The quality of both the task and fMRI aspects of the dataset are summarized in concise reports created with R, AFNI, and knitr. The reports and underlying tests are designed to highlight potential issues, are pdf files for easy archiving, and require relatively little experience to use and adapt. This article is accompanied by both the compiled reports and the source code and explanation necessary to use them.
format Online
Article
Text
id pubmed-10406291
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-104062912023-08-08 Efficient evaluation of the Open QC task fMRI dataset Etzel, Joset A. Front Neuroimaging Neuroimaging This article is an evaluation of the task dataset as part of the Demonstrating Quality Control (QC) Procedures in fMRI (FMRI Open QC Project) methodological research topic. The quality of both the task and fMRI aspects of the dataset are summarized in concise reports created with R, AFNI, and knitr. The reports and underlying tests are designed to highlight potential issues, are pdf files for easy archiving, and require relatively little experience to use and adapt. This article is accompanied by both the compiled reports and the source code and explanation necessary to use them. Frontiers Media S.A. 2023-02-17 /pmc/articles/PMC10406291/ /pubmed/37554632 http://dx.doi.org/10.3389/fnimg.2023.1070274 Text en Copyright © 2023 Etzel. https://creativecommons.org/licenses/by/4.0/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) and the copyright owner(s) 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 Neuroimaging
Etzel, Joset A.
Efficient evaluation of the Open QC task fMRI dataset
title Efficient evaluation of the Open QC task fMRI dataset
title_full Efficient evaluation of the Open QC task fMRI dataset
title_fullStr Efficient evaluation of the Open QC task fMRI dataset
title_full_unstemmed Efficient evaluation of the Open QC task fMRI dataset
title_short Efficient evaluation of the Open QC task fMRI dataset
title_sort efficient evaluation of the open qc task fmri dataset
topic Neuroimaging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406291/
https://www.ncbi.nlm.nih.gov/pubmed/37554632
http://dx.doi.org/10.3389/fnimg.2023.1070274
work_keys_str_mv AT etzeljoseta efficientevaluationoftheopenqctaskfmridataset