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Joint coding of shape and blur in area V4

Author

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  • Timothy D. Oleskiw

    (University of Washington
    University of Washington)

  • Amy Nowack

    (University of Washington)

  • Anitha Pasupathy

    (University of Washington)

Abstract

Edge blur, a prevalent feature of natural images, is believed to facilitate multiple visual processes including segmentation and depth perception. Furthermore, image descriptions that explicitly combine blur and shape information provide complete representations of naturalistic scenes. Here we report the first demonstration of blur encoding in primate visual cortex: neurons in macaque V4 exhibit tuning for both object shape and boundary blur, with observed blur tuning not explained by potential confounds including stimulus size, intensity, or curvature. A descriptive model wherein blur selectivity is cast as a distinct neural process that modulates the gain of shape-selective V4 neurons explains observed data, supporting the hypothesis that shape and blur are fundamental features of a sufficient neural code for natural image representation in V4.

Suggested Citation

  • Timothy D. Oleskiw & Amy Nowack & Anitha Pasupathy, 2018. "Joint coding of shape and blur in area V4," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02438-8
    DOI: 10.1038/s41467-017-02438-8
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    Cited by:

    1. Hojin Jang & Frank Tong, 2024. "Improved modeling of human vision by incorporating robustness to blur in convolutional neural networks," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Ian J C MacCormick & Bryan M Williams & Yalin Zheng & Kun Li & Baidaa Al-Bander & Silvester Czanner & Rob Cheeseman & Colin E Willoughby & Emery N Brown & George L Spaeth & Gabriela Czanner, 2019. "Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-20, January.

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