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  Revealing the multidimensional mental representations of natural objects underlying human similarity judgements

Hebart, M. N., Zheng, C. Y., Pereira, F., & Baker, C. I. (2020). Revealing the multidimensional mental representations of natural objects underlying human similarity judgements. Nature Human Behaviour, 4(11), 1173-1185. doi:10.1038/s41562-020-00951-3.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-60A5-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0007-60A6-1
Genre: Journal Article

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 Creators:
Hebart, Martin N.1, 2, Author              
Zheng, Charles Y.3, Author
Pereira, Francisco3, Author
Baker, Chris I.1, Author
Affiliations:
1Laboratory of Brain and Cognition, Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA, ou_persistent22              
2Max Planck Research Group Vision and Computational Cognition, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_3158378              
3Machine Learning Core, National Institutes of Health, Bethesda, MD, USA, ou_persistent22              

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 Abstract: Objects can be characterized according to a vast number of possible criteria (such as animacy, shape, colour and function), but some dimensions are more useful than others for making sense of the objects around us. To identify these core dimensions of object representations, we developed a data-driven computational model of similarity judgements for real-world images of 1,854 objects. The model captured most explainable variance in similarity judgements and produced 49 highly reproducible and meaningful object dimensions that reflect various conceptual and perceptual properties of those objects. These dimensions predicted external categorization behaviour and reflected typicality judgements of those categories. Furthermore, humans can accurately rate objects along these dimensions, highlighting their interpretability and opening up a way to generate similarity estimates from object dimensions alone. Collectively, these results demonstrate that human similarity judgements can be captured by a fairly low-dimensional, interpretable embedding that generalizes to external behaviour.

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Language(s): eng - English
 Dates: 2020-03-182020-08-172020-10-122020-11
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s41562-020-00951-3
Other: epub 2020
PMID: 33046861
 Degree: -

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Project name : -
Grant ID : ZIA-MH-002909 and ZIC-MH002968
Funding program : -
Funding organization : National Institutes of Health
Project name : -
Grant ID : NCT00001360
Funding program : -
Funding organization : National Institute of Mental Health

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Title: Nature Human Behaviour
Source Genre: Journal
 Creator(s):
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Publ. Info: London : Nature Research
Pages: - Volume / Issue: 4 (11) Sequence Number: - Start / End Page: 1173 - 1185 Identifier: ISSN: 2397-3374
CoNE: https://pure.mpg.de/cone/journals/resource/2397-3374