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Human V4 size predicts crowding distance

Author

Listed:
  • Jan W. Kurzawski

    (New York University
    Maastricht University)

  • Brenda S. Qiu

    (University of Washington)

  • Najib J. Majaj

    (New York University)

  • Noah C. Benson

    (University of Washington)

  • Denis G. Pelli

    (New York University
    New York University)

  • Jonathan Winawer

    (New York University
    New York University)

Abstract

Visual recognition is limited by both object size (acuity) and spacing. The spacing limit, called “crowding”, is the failure to recognize an object in the presence of other objects. Here, we take advantage of individual differences in crowding to investigate its biological basis. Crowding distance, the minimum object spacing needed for recognition, varies 2-fold among healthy adults. We test the conjecture that this variation in psychophysical crowding distance is due to variation in cortical map size. To test this, we make paired measurements of brain and behavior in 49 observers. We use psychophysics to measure crowding distance and calculate λ, the number of letters that fit into each observer’s visual field without crowding. In the same observers, we use functional magnetic resonance imaging (fMRI) to measure the surface area A of retinotopic maps V1, V2, V3, and V4. Across observers, λ is proportional to the surface area of V4 but is uncorrelated with the surface area of V1 to V3. The proportional relationship of λ to area of V4 indicates conservation of cortical crowding distance across individuals: letters can be recognized if they are spaced by at least 1.4 mm on the V4 map, irrespective of map size and psychophysical crowding distance. We conclude that the size of V4 predicts the spacing limit of visual perception.

Suggested Citation

  • Jan W. Kurzawski & Brenda S. Qiu & Najib J. Majaj & Noah C. Benson & Denis G. Pelli & Jonathan Winawer, 2025. "Human V4 size predicts crowding distance," Nature Communications, Nature, vol. 16(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59101-w
    DOI: 10.1038/s41467-025-59101-w
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    References listed on IDEAS

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    2. Garikoitz Lerma-Usabiaga & Noah Benson & Jonathan Winawer & Brian A Wandell, 2020. "A validation framework for neuroimaging software: The case of population receptive fields," PLOS Computational Biology, Public Library of Science, vol. 16(6), pages 1-18, June.
    3. Russell Epstein & Nancy Kanwisher, 1998. "A cortical representation of the local visual environment," Nature, Nature, vol. 392(6676), pages 598-601, April.
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