Listening to real-world sounds: fMRI data for analyzing connectivity networks.

Auditory Connectivity networks Real-world fMRI

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Oct 2019
Historique:
received: 21 07 2019
revised: 31 07 2019
accepted: 09 08 2019
entrez: 25 10 2019
pubmed: 28 10 2019
medline: 28 10 2019
Statut: epublish

Résumé

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.

Identifiants

pubmed: 31646154
doi: 10.1016/j.dib.2019.104411
pii: S2352-3409(19)30766-8
pii: 104411
pmc: PMC6804394
doi:

Types de publication

Journal Article

Langues

eng

Pagination

104411

Informations de copyright

© 2019 The Authors.

Références

Neuroimage. 2002 Jan;15(1):1-15
pubmed: 11771969
J Neurophysiol. 2009 Jun;101(6):3270-83
pubmed: 19339462
Neuroimage. 2019 Jul 22;202:116042
pubmed: 31344485

Auteurs

Po-Chih Kuo (PC)

Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.

Yi-Li Tseng (YL)

Department of Electrical Engineering, Fu Jen Catholic University, New Taipei City, Taiwan.

Karl Zilles (K)

Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany.

Summit Suen (S)

Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.

Simon B Eickhoff (SB)

Institute of System Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany.

Juin-Der Lee (JD)

Graduate Institute of Business Administration, National Chengchi University, Taipei, Taiwan.

Philip E Cheng (PE)

Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.

Michelle Liou (M)

Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.

Classifications MeSH