ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2017
A random-matrix theory of the number sense.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 23 citations in OpenAlex.
- A non-monotonic code for event probability in the human brain.Nature communications · 2025Article
- Role of Lateral Inhibition on Visual Number Sense.Frontiers in computational neuroscience · 2022Article
- Extraordinary claims, extraordinary evidence? A discussion.Learning & behavior · 2021Article
- Visual number sense in untrained deep neural networks.Science advances · 2021Article
- Overexpression of phosphoprotein enriched in astrocytes 15 reverses the damage induced by propofol in hippocampal neurons.Molecular medicine reports · 2019Article
- Introduction: The origins of numerical abilities.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2017Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Number sense, a spontaneous ability to process approximate numbers, has been documented in human adults, infants and newborns, and many other animals. Species as distant as monkeys and crows exhibit very similar neurons tuned to specific numerosities. How number sense can emerge in the absence of learning or fine tuning is currently unknown. We introduce a random-matrix theory of self-organized neural states where numbers are coded by vectors of activation across multiple units, and where the vector codes for successive integers are obtained through multiplication by a fixed but random matrix. This cortical implementation of the 'von Mises' algorithm explains many otherwise disconnected observations ranging from neural tuning curves in monkeys to looking times in neonates and cortical numerotopy in adults. The theory clarifies the origin of Weber-Fechner's Law and yields a novel and empirically validated prediction of multi-peak number neurons. Random matrices constitute a novel mechanism for the emergence of brain states coding for quantity.This article is part of a discussion meeting issue 'The origins of numerical abilities'.
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