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

• Main Authors: Po-Chih Kuo, Yi-Li Tseng, Karl Zilles, Summit Suen, Simon B. Eickhoff, Juin-Der Lee, Philip E. Cheng, Michelle Liou
• Format: Article
• Language: English
• Published: Elsevier 2019-10-01
• Series: Data in Brief
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352340919307668

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. Keywords: fMRI, Connectivity networks, Real-world, Auditory