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A naturalistic neuroimaging database for understanding the brain using ecological stimuli

Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of ‘resting-state’ data for which the f...

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Autores principales: Aliko, Sarah, Huang, Jiawen, Gheorghiu, Florin, Meliss, Stefanie, Skipper, Jeremy I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555491/
https://www.ncbi.nlm.nih.gov/pubmed/33051448
http://dx.doi.org/10.1038/s41597-020-00680-2
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author Aliko, Sarah
Huang, Jiawen
Gheorghiu, Florin
Meliss, Stefanie
Skipper, Jeremy I.
author_facet Aliko, Sarah
Huang, Jiawen
Gheorghiu, Florin
Meliss, Stefanie
Skipper, Jeremy I.
author_sort Aliko, Sarah
collection PubMed
description Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of ‘resting-state’ data for which the functions of networks cannot be verifiably labelled. We make a ‘Naturalistic Neuroimaging Database’ (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world.
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spelling pubmed-75554912020-10-19 A naturalistic neuroimaging database for understanding the brain using ecological stimuli Aliko, Sarah Huang, Jiawen Gheorghiu, Florin Meliss, Stefanie Skipper, Jeremy I. Sci Data Data Descriptor Neuroimaging has advanced our understanding of human psychology using reductionist stimuli that often do not resemble information the brain naturally encounters. It has improved our understanding of the network organization of the brain mostly through analyses of ‘resting-state’ data for which the functions of networks cannot be verifiably labelled. We make a ‘Naturalistic Neuroimaging Database’ (NNDb v1.0) publically available to allow for a more complete understanding of the brain under more ecological conditions during which networks can be labelled. Eighty-six participants underwent behavioural testing and watched one of 10 full-length movies while functional magnetic resonance imaging was acquired. Resulting timeseries data are shown to be of high quality, with good signal-to-noise ratio, few outliers and low movement. Data-driven functional analyses provide further evidence of data quality. They also demonstrate accurate timeseries/movie alignment and how movie annotations might be used to label networks. The NNDb can be used to answer questions previously unaddressed with standard neuroimaging approaches, progressing our knowledge of how the brain works in the real world. Nature Publishing Group UK 2020-10-13 /pmc/articles/PMC7555491/ /pubmed/33051448 http://dx.doi.org/10.1038/s41597-020-00680-2 Text en © The Author(s) 2020 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Aliko, Sarah
Huang, Jiawen
Gheorghiu, Florin
Meliss, Stefanie
Skipper, Jeremy I.
A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title_full A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title_fullStr A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title_full_unstemmed A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title_short A naturalistic neuroimaging database for understanding the brain using ecological stimuli
title_sort naturalistic neuroimaging database for understanding the brain using ecological stimuli
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555491/
https://www.ncbi.nlm.nih.gov/pubmed/33051448
http://dx.doi.org/10.1038/s41597-020-00680-2
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