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Activity-dependent homeostatic specification of transmitter expression in embryonic neurons

Author

Listed:
  • Laura N. Borodinsky

    (UCSD)

  • Cory M. Root

    (UCSD)

  • Julia A. Cronin

    (UCSD)

  • Sharon B. Sann

    (UCSD)

  • Xiaonan Gu

    (UCSD)

  • Nicholas C. Spitzer

    (UCSD)

Abstract

Neurotransmitters are essential for interneuronal signalling, and the specification of appropriate transmitters in differentiating neurons has been related to intrinsic neuronal identity and to extrinsic signalling proteins. Here we show that altering the distinct patterns of Ca2+ spike activity spontaneously generated by different classes of embryonic spinal neurons in vivo changes the transmitter that neurons express without affecting the expression of markers of cell identity. Regulation seems to be homeostatic: suppression of activity leads to an increased number of neurons expressing excitatory transmitters and a decreased number of neurons expressing inhibitory transmitters; the reverse occurs when activity is enhanced. The imposition of specific spike frequencies in vitro does not affect labels of cell identity but again specifies the expression of transmitters that are inappropriate for the markers they express, during an early critical period. The results identify a new role of patterned activity in development of the central nervous system.

Suggested Citation

  • Laura N. Borodinsky & Cory M. Root & Julia A. Cronin & Sharon B. Sann & Xiaonan Gu & Nicholas C. Spitzer, 2004. "Activity-dependent homeostatic specification of transmitter expression in embryonic neurons," Nature, Nature, vol. 429(6991), pages 523-530, June.
    • Handle: RePEc:nat:nature:v:429:y:2004:i:6991:d:10.1038_nature02518
    DOI: 10.1038/nature02518
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    Cited by:

    1. Juan Prada & Manju Sasi & Corinna Martin & Sibylle Jablonka & Thomas Dandekar & Robert Blum, 2018. "An open source tool for automatic spatiotemporal assessment of calcium transients and local ‘signal-close-to-noise’ activity in calcium imaging data," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-34, March.

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