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Kinetics of exocytosis and endocytosis at the cochlear inner hair cell afferent synapse of the mouse

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Moser, Tobias, Beutner, Dirk·2000·Proceedings of the National Academy of Sciences

Abstract

Hearing in mammals relies on the highly synchronous synaptic transfer between cochlear inner hair cells (IHCs) and the auditory nerve. We studied the presynaptic function of single mouse IHCs by monitoring membrane capacitance changes and voltage-gated Ca 2+ currents. Exocytosis initially occurred at a high rate but then slowed down within a few milliseconds, despite nearly constant Ca 2+ influx. We interpret the observed secretory depression as depletion of a readily releasable pool (RRP) of about 280 vesicles. These vesicles are probably docked close to Ca 2+ channels at the ribbon-type active zones of the IHCs. Continued depolarization evoked slower exocytosis occurring at a nearly constant rate for at least 1 s and depending on “long-distance” Ca 2+ signaling. Refilling of the RRP after depletion followed a biphasic time course and was faster than endocytosis. RRP depletion is discussed as a mechanism for fast auditory adaptation.

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Metadata

Authors
Moser, T., & Beutner, D.
Venue
Proceedings of the National Academy of Sciences
Published
2000-01-18
Volume
97
Issue
2
Pages
883-888
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2155756146
Cited by
461
References
0
FWCI
6.89
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Kinetics of exocytosis and endocytosis at the cochlear inner hair cell afferent synapse of the mouse. https://app.cochat.ai/papers/10.1073/pnas.97.2.883
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Moser, T., & Beutner, D. (2000). Kinetics of exocytosis and endocytosis at the cochlear inner hair cell afferent synapse of the mouse. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.97.2.883

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.