The evolution of quantitative sensitivity

Margaret A.H. Bryer, Sarah E. Koopman, Jessica F. Cantlon, Steven T. Piantadosi, Evan L. MacLean, Joseph M. Baker, Michael J. Beran, Sarah M. Jones, Kerry E. Jordan, Salif Mahamane, Andreas Nieder, Bonnie M. Perdue, Friederike Range, Jeffrey R. Stevens, Masaki Tomonaga, Dorottya J. Ujfalussy, Jennifer Vonk

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The ability to represent approximate quantities appears to be phylogenetically widespread, but the selective pressures and proximate mechanisms favouring this ability remain unknown. We analysed quantity discrimination data from 672 subjects across 33 bird and mammal species, using a novel Bayesian model that combined phylogenetic regression with a model of number psychophysics and random effect components. This allowed us to combine data from 49 studies and calculate the Weber fraction (a measure of quantity representation precision) for each species. We then examined which cognitive, socioecological and biological factors were related to variance in Weber fraction. We found contributions of phylogeny to quantity discrimination performance across taxa. Of the neural, socioecological and general cognitive factors we tested, cortical neuron density and domain-general cognition were the strongest predictors of Weber fraction, controlling for phylogeny. Our study is a new demonstration of evolutionary constraints on cognition, as well as of a relation between species-specific neuron density and a particular cognitive ability. This article is part of the theme issue 'Systems neuroscience through the lens of evolutionary theory'.

Original languageEnglish (US)
Pages (from-to)20200529
Number of pages1
JournalPhilosophical transactions of the Royal Society of London. Series B, Biological sciences
Volume377
Issue number1844
DOIs
StatePublished - Feb 14 2022
Externally publishedYes

Keywords

  • Weber fraction
  • brain evolution
  • quantity discrimination

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

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