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A primarily serial, foveal accumulator underlies approximate numerical estimation

The work

AuthorsSamuel Cheyette; Steven T. Piantadosi
Editors
Typearticle
Year2019
Citekeycheyette2019primarily

Where it appeared

Published inProceedings of the National Academy of Sciences
PublisherNational Academy of Sciences
Volume116
Issue36
Pages17729--17734

Identifiers

DOI10.1073/pnas.1819956116
OpenAlexW2969602418

From OpenAlex, which stores abstracts as an index of words and their positions: what is shown is rebuilt from that, and reads fluently whether or not it is what the author wrote.

Abstract

The approximate number system (ANS) has attracted broad interest due to its potential importance in early mathematical development and the fact that it is conserved across species. Models of the ANS and behavioral measures of ANS acuity both assume that quantity estimation is computed rapidly and in parallel across an entire view of the visual scene. We present evidence instead that ANS estimates are largely the product of a serial accumulation mechanism operating across visual fixations. We used an eye-tracker to collect data on participants' visual fixations while they performed quantity-estimation and -discrimination tasks. We were able to predict participants' numerical estimates using their visual fixation data: As the number of dots fixated increased, mean estimates also increased, and estimation error decreased. A detailed model-based analysis shows that fixated dots contribute twice as much as peripheral dots to estimated quantities; people do not "double count" multiply fixated dots; and they do not adjust for the proportion of area in the scene that they have fixated. The accumulation mechanism we propose explains reported effects of display time on estimation and earlier findings of a bias to underestimate quantities.

How it got here

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Added2026-10-29 08:15 UTC
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Filed under

pnas

Cite it as

@article{cheyette2019primarily,
  title        = {A primarily serial, foveal accumulator underlies approximate numerical estimation},
  author       = {Samuel Cheyette and Steven T. Piantadosi},
  year         = {2019},
  journal      = {Proceedings of the National Academy of Sciences},
  publisher    = {National Academy of Sciences},
  volume       = {116},
  number       = {36},
  pages        = {17729--17734},
  doi          = {10.1073/pnas.1819956116},
}

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