Clustered functional domains for curves and corners in cortical area V4

  1. Rundong Jiang
  2. Ian Max Andolina
  3. Ming Li
  4. Shiming Tang  Is a corresponding author
  1. Peking University, China
  2. Chinese Academy of Sciences, China
  3. Bejing Normal University, China

Abstract

The ventral visual pathway is crucially involved in integrating low-level visual features into complex representations for objects and scenes. At an intermediate stage of the ventral visual pathway, V4 plays a crucial role in supporting this transformation. Many V4 neurons are selective for shape segments like curves and corners, however it remains unclear whether these neurons are organized into clustered functional domains, a structural motif common across other visual cortices. Using two-photon calcium imaging in awake macaques, we confirmed and localized cortical domains selective for curves or corners in V4. Single-cell resolution imaging confirmed that curve or corner selective neurons were spatially clustered into such domains. When tested with hexagonal-segment stimuli, we find that stimulus smoothness is the cardinal difference between curve and corner selectivity in V4. Combining cortical population responses with single neuron analysis, our results reveal that curves and corners are encoded by neurons clustered into functional domains in V4. This functionally-specific population architecture bridges the gap between the early and late cortices of the ventral pathway and may serve to facilitate complex object recognition.

Data availability

The data and MATLAB codes used in this study can be found in GitHub (https://github.com/RJiang1994/macaque-v4-2P).

The following data sets were generated
    1. Rundong Jiang
    2. Shiming Tang
    (2020) macaque-v4-2P
    GitHub, github.com/RJiang1994/macaque-v4-2P.

Article and author information

Author details

  1. Rundong Jiang

    School of Lifesciences, Peking University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9217-0749
  2. Ian Max Andolina

    Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9985-3414
  3. Ming Li

    State key laboratory of Congnitive Neuroscience and learning, Bejing Normal University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5173-1602
  4. Shiming Tang

    School of Life Sciences, Peking University, Beijing, China
    For correspondence
    tangshm@pku.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0294-3259

Funding

National Natural Science Foundation of China (31730109)

  • Shiming Tang

National Basic Research Program of China (2017YFA0105201)

  • Shiming Tang

National Natural Science Foundation of China (China Outstanding Young Researcher Award 30525016)

  • Shiming Tang

Peking University (Project 985 grant Z151100000915070)

  • Shiming Tang

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

Ethics

Animal experimentation: All procedures involving animals were in accordance with the Guide of Institutional Animal Care and Use Committee (IACUC) of Peking University Laboratory Animal Center, and approved by the Peking University Animal Care and Use Committee (LSC-TangSM-5).

Copyright

© 2021, Jiang et al.

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.

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  1. Rundong Jiang
  2. Ian Max Andolina
  3. Ming Li
  4. Shiming Tang
(2021)
Clustered functional domains for curves and corners in cortical area V4
eLife 10:e63798.
https://doi.org/10.7554/eLife.63798

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https://doi.org/10.7554/eLife.63798