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Support for a synaptic chain model of neuronal sequence generation

Author

Listed:
  • Michael A. Long

    (McGovern Institute for Brain Research, Massachusetts Institute of Technology
    Present address: Departments of Otolaryngology and Physiology and Neuroscience, NYU School of Medicine, 522 First Avenue, New York, New York 10016, USA.)

  • Dezhe Z. Jin

    (The Pennsylvania State University)

  • Michale S. Fee

    (McGovern Institute for Brain Research, Massachusetts Institute of Technology)

Abstract

In songbirds, the remarkable temporal precision of song is generated by a sparse sequence of bursts in the premotor nucleus HVC. To distinguish between two possible classes of models of neural sequence generation, we carried out intracellular recordings of HVC neurons in singing zebra finches (Taeniopygia guttata). We found that the subthreshold membrane potential is characterized by a large, rapid depolarization 5–10 ms before burst onset, consistent with a synaptically connected chain of neurons in HVC. We found no evidence for the slow membrane potential modulation predicted by models in which burst timing is controlled by subthreshold dynamics. Furthermore, bursts ride on an underlying depolarization of ∼10-ms duration, probably the result of a regenerative calcium spike within HVC neurons that could facilitate the propagation of activity through a chain network with high temporal precision. Our results provide insight into the fundamental mechanisms by which neural circuits can generate complex sequential behaviours.

Suggested Citation

  • Michael A. Long & Dezhe Z. Jin & Michale S. Fee, 2010. "Support for a synaptic chain model of neuronal sequence generation," Nature, Nature, vol. 468(7322), pages 394-399, November.
    • Handle: RePEc:nat:nature:v:468:y:2010:i:7322:d:10.1038_nature09514
    DOI: 10.1038/nature09514
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    Cited by:

    1. Alex P. Vaz & John H. Wittig & Sara K. Inati & Kareem A. Zaghloul, 2023. "Backbone spiking sequence as a basis for preplay, replay, and default states in human cortex," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Matthew A Slayton & Juan L Romero-Sosa & Katrina Shore & Dean V Buonomano & Indre V Viskontas, 2020. "Musical expertise generalizes to superior temporal scaling in a Morse code tapping task," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-9, January.
    3. Satohiro Tajima & Toru Yanagawa & Naotaka Fujii & Taro Toyoizumi, 2015. "Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding," PLOS Computational Biology, Public Library of Science, vol. 11(11), pages 1-28, November.
    4. A. Barri & M. T. Wiechert & M. Jazayeri & D. A. DiGregorio, 2022. "Synaptic basis of a sub-second representation of time in a neural circuit model," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    5. Sravani Kondapavulur & Stefan M. Lemke & David Darevsky & Ling Guo & Preeya Khanna & Karunesh Ganguly, 2022. "Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    6. Joshua M Mueller & Primoz Ravbar & Julie H Simpson & Jean M Carlson, 2019. "Drosophila melanogaster grooming possesses syntax with distinct rules at different temporal scales," PLOS Computational Biology, Public Library of Science, vol. 15(6), pages 1-25, June.

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