InterTVA. A multimodal MRI dataset for the study of inter-individual differences in voice perception and identification.
Resource type
Authors/contributors
- AGLIERI, Virginia (Author)
- CAGNA, Bastien (Author)
- BELIN, Pascal (Author)
- TAKERKART, Sylvain (Author)
Title
InterTVA. A multimodal MRI dataset for the study of inter-individual differences in voice perception and identification.
Abstract
The InterTVA dataset has been acquired with two main objectives. First, from a neuroscientific perspective, it aims at studying the inter-individual differences observed in people's ability at performing voice perception and voice identification tasks. Secondly, from a methodological perspective, it should allow benchmarking multi-view machine learning methods. Indeed, it includes several MRI modalities: anatomical MRI, diffusion MRI and several sessions of functional MRI -- one resting state run, one event-related voice localizer run (passive listening of vocal and non-vocal sounds), and four runs during which the subject performed a voice identification task.
Date
2019
Repository
Openneuro
Citation Key
aglieri.etal_2019
Accessed
16/05/2025, 16:28
Library Catalog
DOI.org (Datacite)
Citation
AGLIERI, V., CAGNA, B., BELIN, P., & TAKERKART, S. (2019). InterTVA. A multimodal MRI dataset for the study of inter-individual differences in voice perception and identification. [Dataset]. Openneuro. https://doi.org/10.18112/OPENNEURO.DS001771.V1.0.2
Speech Perception Data
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