THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior
Posted on 2023-01-17 - 19:30 authored by Martin Hebart
Here we provide all datasets which are part of the THINGS-data collection comprising functional MRI, magnetoencephalographic recordings, and 4.70 million similarity judgments in response to thousands of photographic images for up to 1,854 object concepts. THINGS-data is unique in its breadth of richly-annotated objects, allowing for testing countless hypotheses at scale while assessing the reproducibility of previous findings. Beyond the unique insights promised by each individual dataset, the multimodality of THINGS-data allows combining datasets for a much broader view into object processing than previously possible.
CITE THIS COLLECTION
Hebart, Martin; Contier, Oliver; Teichmann, Lina; Rockter, Adam; Zheng, Charles; Kidder, Alexis; et al. (2023). THINGS-data: A multimodal collection of large-scale datasets for investigating object representations in brain and behavior. Figshare+. Collection. https://doi.org/10.25452/figshare.plus.c.6161151.v1
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FUNDING
Intramural Research Program of the National Institutes of Health (ZIA-MH-002909, ZIC-MH002968)
ERC Starting Grant project COREDIM (101039712)
Research group grant by the Max Planck Society awarded to MNH
Object, face, body and scene representations in the human brain
National Institute of Mental Health
Research Institution(s)
National Institute of Mental Health, Max Planck Institute for Human Cognitive and Brain SciencesContact email
hebart@cbs.mpg.deAssociated Preprint DOI
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AUTHORS (9)
LT
Lina Teichmann
AR
Adam Rockter
CZ
Charles Zheng
AK
Alexis Kidder
AC
Anna Corriveau
MV
Maryam Vaziri-Pashkam
CB
Chris Baker