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The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers

Overview of attention for article published in PLoS Computational Biology, January 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

blogs
1 blog
twitter
175 X users
facebook
4 Facebook pages
reddit
1 Redditor

Citations

dimensions_citation
77 Dimensions

Readers on

mendeley
150 Mendeley
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Title
The language of geometry: Fast comprehension of geometrical primitives and rules in human adults and preschoolers
Published in
PLoS Computational Biology, January 2017
DOI 10.1371/journal.pcbi.1005273
Pubmed ID
Authors

Marie Amalric, Liping Wang, Pierre Pica, Santiago Figueira, Mariano Sigman, Stanislas Dehaene

Abstract

During language processing, humans form complex embedded representations from sequential inputs. Here, we ask whether a "geometrical language" with recursive embedding also underlies the human ability to encode sequences of spatial locations. We introduce a novel paradigm in which subjects are exposed to a sequence of spatial locations on an octagon, and are asked to predict future locations. The sequences vary in complexity according to a well-defined language comprising elementary primitives and recursive rules. A detailed analysis of error patterns indicates that primitives of symmetry and rotation are spontaneously detected and used by adults, preschoolers, and adult members of an indigene group in the Amazon, the Munduruku, who have a restricted numerical and geometrical lexicon and limited access to schooling. Furthermore, subjects readily combine these geometrical primitives into hierarchically organized expressions. By evaluating a large set of such combinations, we obtained a first view of the language needed to account for the representation of visuospatial sequences in humans, and conclude that they encode visuospatial sequences by minimizing the complexity of the structured expressions that capture them.

X Demographics

X Demographics

The data shown below were collected from the profiles of 175 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 150 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
France 1 <1%
Korea, Republic of 1 <1%
Italy 1 <1%
Canada 1 <1%
Spain 1 <1%
Unknown 144 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 25%
Researcher 19 13%
Student > Master 17 11%
Professor 10 7%
Student > Bachelor 8 5%
Other 32 21%
Unknown 26 17%
Readers by discipline Count As %
Psychology 36 24%
Neuroscience 23 15%
Computer Science 12 8%
Linguistics 10 7%
Agricultural and Biological Sciences 7 5%
Other 29 19%
Unknown 33 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 119. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 February 2022.
All research outputs
#353,807
of 25,554,853 outputs
Outputs from PLoS Computational Biology
#242
of 9,002 outputs
Outputs of similar age
#7,631
of 423,465 outputs
Outputs of similar age from PLoS Computational Biology
#6
of 165 outputs
Altmetric has tracked 25,554,853 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 423,465 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.