1. Neuroscience
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Mechanisms underlying sharpening of visual response dynamics with familiarity

  1. Sukbin Lim  Is a corresponding author
  1. New York University, Shanghai, China
Research Article
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Cite this article as: eLife 2019;8:e44098 doi: 10.7554/eLife.44098

Abstract

Experience-dependent modifications of synaptic connections are thought to change patterns of network activities and stimulus tuning with learning. However, only a few studies explored how synaptic plasticity shapes the response dynamics of cortical circuits. Here, we investigated the mechanism underlying sharpening of both stimulus selectivity and response dynamics with familiarity observed in monkey inferotemporal cortex. Broadening the distribution of activities and stronger oscillations in the response dynamics after learning provide evidence for synaptic plasticity in recurrent connections modifying the strength of positive feedback. Its interplay with slow negative feedback via firing rate adaptation is critical in sharpening response dynamics. Analysis of changes in temporal patterns also enables us to disentangle recurrent and feedforward synaptic plasticity and provides a measure for the strengths of recurrent synaptic plasticity. Overall, this work highlights the importance of analyzing changes in dynamics as well as network patterns to further reveal the mechanisms of visual learning.

Article and author information

Author details

  1. Sukbin Lim

    New York University, Shanghai, Shanghai, China
    For correspondence
    sukbin.lim@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9936-5293

Funding

National Natural Science Foundation of China (Fund for International Young Scientists, 31650110468)

  • Sukbin Lim

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

Reviewing Editor

  1. Nicole Rust, University of Pennsylvania, United States

Publication history

  1. Received: December 3, 2018
  2. Accepted: August 7, 2019
  3. Accepted Manuscript published: August 8, 2019 (version 1)

Copyright

© 2019, Lim

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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