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Emergence of a 'visual number sense' in hierarchical generative models

Nature Neuroscience volume 15, pages 194–196 (2012)Cite this article

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Abstract

Numerosity estimation is phylogenetically ancient and foundational to human mathematical learning, but its computational bases remain controversial. Here we show that visual numerosity emerges as a statistical property of images in 'deep networks' that learn a hierarchical generative model of the sensory input. Emergent numerosity detectors had response profiles resembling those of monkey parietal neurons and supported numerosity estimation with the same behavioral signature shown by humans and animals.

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Figure 1: Deep network model and number-sensitive neurons.
Figure 2: Numerosity comparison task.

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Acknowledgements

This study was supported by the European Research Council (grant no. 210922 to M.Z.)

Author information

Authors and Affiliations

  1. Dipartimento di Psicologia Generale, Università di Padova, Italy

    Ivilin Stoianov & Marco Zorzi

  2. Center for Cognitive Science, Università di Padova, Italy

    Marco Zorzi

Authors
  1. Ivilin Stoianov
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  2. Marco Zorzi
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Contributions

M.Z. and I.S. conceived the experiments, discussed the results and wrote the paper. I.S. wrote the code, ran the model and analyzed data.

Corresponding author

Correspondence to Marco Zorzi.

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The authors declare no competing financial interests.

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Supplementary Figures 1–4, Supplementary Methods (PDF 242 kb)

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Stoianov, I., Zorzi, M. Emergence of a 'visual number sense' in hierarchical generative models. Nat Neurosci 15, 194–196 (2012). https://doi.org/10.1038/nn.2996

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  • DOI: https://doi.org/10.1038/nn.2996

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