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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...

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Autores principales: Kuo, Po-Chih, Tseng, Yi-Li, Zilles, Karl, Suen, Summit, Eickhoff, Simon B., Lee, Juin-Der, Cheng, Philip E., Liou, Michelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
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.
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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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