A visual sense of number emerges from divisive normalization in a simple center-surround convolutional network

  1. Joonkoo Park  Is a corresponding author
  2. David E Huber
  1. University of Massachusetts Amherst, United States

Abstract

Many species of animals exhibit an intuitive sense of number, suggesting a fundamental neural mechanism for representing numerosity in a visual scene. Recent empirical studies demonstrate that early feedforward visual responses are sensitive to numerosity of a dot array but substantially less so to continuous dimensions orthogonal to numerosity, such as size and spacing of the dots. However, the mechanisms that extract numerosity are unknown. Here we identified the core neurocomputational principles underlying these effects: (1) center-surround contrast filters; (2) at different spatial scales; with (3) divisive normalization across network units. In an untrained computational model, these principles eliminated sensitivity to size and spacing, making numerosity the main determinant of the neuronal response magnitude. Moreover, a model implementation of these principles explained both well-known and relatively novel illusions of numerosity perception across space and time. This supports the conclusion that the neural structures and feedforward processes that encode numerosity naturally produce visual illusions of numerosity. Together, these results identify a set of neurocomputational properties that gives rise to the ubiquity of the number sense in the animal kingdom.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript. Modelling code is uploaded in the following public repository: https://osf.io/4rwjs/.

Article and author information

Author details

  1. Joonkoo Park

    Department of Psychological and Brain Sciences, University of Massachusetts Amherst, Amherst, United States
    For correspondence
    joonkoo@umass.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6703-3961
  2. David E Huber

    Department of Psychological and Brain Sciences, University of Massachusetts Amherst, Amherst, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Science Foundation (BCS 1654089)

  • Joonkoo Park

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2022, Park & Huber

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,176
    views
  • 289
    downloads
  • 7
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Joonkoo Park
  2. David E Huber
(2022)
A visual sense of number emerges from divisive normalization in a simple center-surround convolutional network
eLife 11:e80990.
https://doi.org/10.7554/eLife.80990

Share this article

https://doi.org/10.7554/eLife.80990

Further reading

    1. Neuroscience
    Magdalena Solyga, Georg B Keller
    Research Article

    Our movements result in predictable sensory feedback that is often multimodal. Based on deviations between predictions and actual sensory input, primary sensory areas of cortex have been shown to compute sensorimotor prediction errors. How prediction errors in one sensory modality influence the computation of prediction errors in another modality is still unclear. To investigate multimodal prediction errors in mouse auditory cortex, we used a virtual environment to experimentally couple running to both self-generated auditory and visual feedback. Using two-photon microscopy, we first characterized responses of layer 2/3 (L2/3) neurons to sounds, visual stimuli, and running onsets and found responses to all three stimuli. Probing responses evoked by audiomotor (AM) mismatches, we found that they closely resemble visuomotor (VM) mismatch responses in visual cortex (V1). Finally, testing for cross modal influence on AM mismatch responses by coupling both sound amplitude and visual flow speed to the speed of running, we found that AM mismatch responses were amplified when paired with concurrent VM mismatches. Our results demonstrate that multimodal and non-hierarchical interactions shape prediction error responses in cortical L2/3.

    1. Neuroscience
    Gyeong Hee Pyeon, Hyewon Cho ... Yong Sang Jo
    Research Article Updated

    Recent studies suggest that calcitonin gene-related peptide (CGRP) neurons in the parabrachial nucleus (PBN) represent aversive information and signal a general alarm to the forebrain. If CGRP neurons serve as a true general alarm, their activation would modulate both passive nad active defensive behaviors depending on the magnitude and context of the threat. However, most prior research has focused on the role of CGRP neurons in passive freezing responses, with limited exploration of their involvement in active defensive behaviors. To address this, we examined the role of CGRP neurons in active defensive behavior using a predator-like robot programmed to chase mice. Our electrophysiological results revealed that CGRP neurons encode the intensity of aversive stimuli through variations in firing durations and amplitudes. Optogenetic activation of CGRP neurons during robot chasing elevated flight responses in both conditioning and retention tests, presumably by amplifying the perception of the threat as more imminent and dangerous. In contrast, animals with inactivated CGRP neurons exhibited reduced flight responses, even when the robot was programmed to appear highly threatening during conditioning. These findings expand the understanding of CGRP neurons in the PBN as a critical alarm system, capable of dynamically regulating active defensive behaviors by amplifying threat perception, and ensuring adaptive responses to varying levels of danger.