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Listening to real-world sounds: fMRI data for analyzing connectivity networks
There is a growing interest in functional magnetic resonance imaging (fMRI) studies on connectivity networks in the brain when subjects are under exposure to natural sensory stimulation. Because of a complicated coupling between spontaneous and evoked brain activity under real-world stimulation, the...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804394/ https://www.ncbi.nlm.nih.gov/pubmed/31646154 http://dx.doi.org/10.1016/j.dib.2019.104411 |
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author | Kuo, Po-Chih Tseng, Yi-Li Zilles, Karl Suen, Summit Eickhoff, Simon B. Lee, Juin-Der Cheng, Philip E. Liou, Michelle |
author_facet | Kuo, Po-Chih Tseng, Yi-Li Zilles, Karl Suen, Summit Eickhoff, Simon B. Lee, Juin-Der Cheng, Philip E. Liou, Michelle |
author_sort | Kuo, Po-Chih |
collection | PubMed |
description | There is a growing interest in functional magnetic resonance imaging (fMRI) studies on connectivity networks in the brain when subjects are under exposure to natural sensory stimulation. Because of a complicated coupling between spontaneous and evoked brain activity under real-world stimulation, there is no critical mapping between the experimental inputs and corresponding brain responses. The dataset contains auditory fMRI scans and T1-weighted anatomical scans acquired under eyes-closed and eyes-open conditions. Within each scanning condition, the subject was presented 12 different sound clips, including human voices followed by animal vocalizations. The dataset is meant to be used to assess brain dynamics and connectivity networks under natural sound stimulation; it also allows for empirical investigation of changes in fMRI responses between eyes-closed and eyes-open conditions, between animal vocalizations and human voices, as well as between the 12 different sound clips during auditory stimulation. The dataset is a supplement to the research findings in the paper “Brain dynamics and connectivity networks under natural auditory stimulation” published in NeuroImage. |
format | Online Article Text |
id | pubmed-6804394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-68043942019-10-23 Listening to real-world sounds: fMRI data for analyzing connectivity networks Kuo, Po-Chih Tseng, Yi-Li Zilles, Karl Suen, Summit Eickhoff, Simon B. Lee, Juin-Der Cheng, Philip E. Liou, Michelle Data Brief Neuroscience There is a growing interest in functional magnetic resonance imaging (fMRI) studies on connectivity networks in the brain when subjects are under exposure to natural sensory stimulation. Because of a complicated coupling between spontaneous and evoked brain activity under real-world stimulation, there is no critical mapping between the experimental inputs and corresponding brain responses. The dataset contains auditory fMRI scans and T1-weighted anatomical scans acquired under eyes-closed and eyes-open conditions. Within each scanning condition, the subject was presented 12 different sound clips, including human voices followed by animal vocalizations. The dataset is meant to be used to assess brain dynamics and connectivity networks under natural sound stimulation; it also allows for empirical investigation of changes in fMRI responses between eyes-closed and eyes-open conditions, between animal vocalizations and human voices, as well as between the 12 different sound clips during auditory stimulation. The dataset is a supplement to the research findings in the paper “Brain dynamics and connectivity networks under natural auditory stimulation” published in NeuroImage. Elsevier 2019-08-17 /pmc/articles/PMC6804394/ /pubmed/31646154 http://dx.doi.org/10.1016/j.dib.2019.104411 Text en © 2019 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 Kuo, Po-Chih Tseng, Yi-Li Zilles, Karl Suen, Summit Eickhoff, Simon B. Lee, Juin-Der Cheng, Philip E. Liou, Michelle Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title | Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title_full | Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title_fullStr | Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title_full_unstemmed | Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title_short | Listening to real-world sounds: fMRI data for analyzing connectivity networks |
title_sort | listening to real-world sounds: fmri data for analyzing connectivity networks |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6804394/ https://www.ncbi.nlm.nih.gov/pubmed/31646154 http://dx.doi.org/10.1016/j.dib.2019.104411 |
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