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A critical window for cooperation and competition among developing retinotectal synapses

Author

Listed:
  • Li I. Zhang
  • Huizhong W. Tao
  • Christine E. Holt

    (University of Cambridge)

  • William A. Harris

    (University of Cambridge)

  • Mu-ming Poo

    (University of California at San Diego)

Abstract

In the developing frog visual system, topographic refinement of the retinotectal projection depends on electrical activity. In vivo whole-cell recording from developing Xenopus tectal neurons shows that convergent retinotectal synapses undergo activity-dependent cooperation and competition following correlated pre- and postsynaptic spiking within a narrow time window. Synaptic inputs activated repetitively within 20 ms before spiking of the tectal neuron become potentiated, whereas subthreshold inputs activated within 20 ms after spiking become depressed. Thus both the initial synaptic strength and the temporal order of activation are critical for heterosynaptic interactions among convergent synaptic inputs during activity-dependent refinement of developing neural networks.

Suggested Citation

  • Li I. Zhang & Huizhong W. Tao & Christine E. Holt & William A. Harris & Mu-ming Poo, 1998. "A critical window for cooperation and competition among developing retinotectal synapses," Nature, Nature, vol. 395(6697), pages 37-44, September.
    • Handle: RePEc:nat:nature:v:395:y:1998:i:6697:d:10.1038_25665
    DOI: 10.1038/25665
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    Cited by:

    1. John Palmer & Adam Keane & Pulin Gong, 2017. "Learning and executing goal-directed choices by internally generated sequences in spiking neural circuits," PLOS Computational Biology, Public Library of Science, vol. 13(7), pages 1-23, July.
    2. Yu, Haitao & Guo, Xinmeng & Wang, Jiang & Deng, Bin & Wei, Xile, 2015. "Spike coherence and synchronization on Newman–Watts small-world neuronal networks modulated by spike-timing-dependent plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 307-317.
    3. Li, Tianyu & Wu, Yong & Yang, Lijian & Zhan, Xuan & Jia, Ya, 2022. "Spike-timing-dependent plasticity enhances chaotic resonance in small-world network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    4. Henning Sprekeler & Christian Michaelis & Laurenz Wiskott, 2007. "Slowness: An Objective for Spike-Timing–Dependent Plasticity?," PLOS Computational Biology, Public Library of Science, vol. 3(6), pages 1-13, June.
    5. Li Shen & Guang-Wei Zhang & Can Tao & Michelle B. Seo & Nicole K. Zhang & Junxiang J. Huang & Li I. Zhang & Huizhong W. Tao, 2022. "A bottom-up reward pathway mediated by somatostatin neurons in the medial septum complex underlying appetitive learning," Nature Communications, Nature, vol. 13(1), pages 1-15, December.

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