Intrinsic mechanical sensitivity of mammalian auditory neurons as a contributor to sound-driven neural activity

  1. Maria Cristina Perez-Flores
  2. Eric Verschooten
  3. Jeong Han Lee
  4. Hyo Jeong Kim
  5. Philip X Joris
  6. Ebenezer N Yamoah  Is a corresponding author
  1. University of Nevada Reno, United States
  2. University of Leuven, Belgium

Abstract

Mechanosensation - by which mechanical stimuli are converted into a neuronal signal - is the basis for the sensory systems of hearing, balance, and touch. Mechanosensation is unmatched in speed and its diverse range of sensitivities, reaching its highest temporal limits with the sense of hearing; however, hair cells (HCs) and the auditory nerve (AN) serve as obligatory bottlenecks for sounds to engage the brain. Like other sensory neurons, auditory neurons use the canonical pathway for neurotransmission and millisecond-duration action potentials (APs). How the auditory system utilizes the relatively slow transmission mechanisms to achieve ultrafast speed, and high audio-frequency hearing remains an enigma. Here, we address this paradox and report that the mouse, and chinchilla, AN are mechanically sensitive, and minute mechanical displacement profoundly affects its response properties. Sound-mimicking sinusoidal mechanical and electrical current stimuli affect phase-locked responses. In a phase-dependent manner, the two stimuli can also evoke suppressive responses. We propose that mechanical sensitivity interacts with synaptic responses to shape responses in the AN, including frequency tuning and temporal phase-locking. Combining neurotransmission and mechanical sensation to control spike patterns gives the mammalian AN a secondary receptor role, an emerging theme in primary neuronal functions.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file; Source Data files have been provided for Figures 1-4

Article and author information

Author details

  1. Maria Cristina Perez-Flores

    University of Nevada Reno, Reno, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Eric Verschooten

    Laboratory of Auditory Neurophysiology, University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  3. Jeong Han Lee

    University of Nevada Reno, Reno, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Hyo Jeong Kim

    University of Nevada Reno, Reno, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Philip X Joris

    Laboratory of Auditory Neurophysiology, University of Leuven, Leuven, Belgium
    Competing interests
    The authors declare that no competing interests exist.
  6. Ebenezer N Yamoah

    University of Nevada Reno, Reno, United States
    For correspondence
    enyamoah@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9797-085X

Funding

National Institute of Health (DC016099,DC015252,DC015135,AG060504,AG051443)

  • Ebenezer N Yamoah

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

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols (#08-133) of the University of Arizona. The protocol was approved by the Committee on the Ethics of Animal Experiments of the University of Minnesota (Permit Number: 27-2956). All surgery was performed under sodium pentobarbital anesthesia, and every effort was made to minimize suffering (Yamoah, UNR protocol).

Reviewing Editor

  1. Tobias Reichenbach, Friedrich-Alexander-University (FAU) Erlangen-Nürnberg, Germany

Version history

  1. Preprint posted: May 18, 2021 (view preprint)
  2. Received: October 22, 2021
  3. Accepted: March 9, 2022
  4. Accepted Manuscript published: March 10, 2022 (version 1)
  5. Version of Record published: March 23, 2022 (version 2)

Copyright

© 2022, Perez-Flores et al.

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.

Metrics

  • 1,154
    Page views
  • 210
    Downloads
  • 2
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Maria Cristina Perez-Flores
  2. Eric Verschooten
  3. Jeong Han Lee
  4. Hyo Jeong Kim
  5. Philip X Joris
  6. Ebenezer N Yamoah
(2022)
Intrinsic mechanical sensitivity of mammalian auditory neurons as a contributor to sound-driven neural activity
eLife 11:e74948.
https://doi.org/10.7554/eLife.74948

Share this article

https://doi.org/10.7554/eLife.74948

Further reading

    1. Computational and Systems Biology
    2. Neuroscience
    Tony Zhang, Matthew Rosenberg ... Markus Meister
    Research Article

    An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Here we propose a neural algorithm that can solve all these problems and operates reliably in diverse and complex environments. At its core, the mechanism makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source. We show how the brain can learn to generate internal “virtual odors” that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis.

    1. Neuroscience
    Frances Skinner
    Insight

    Automatic leveraging of information in a hippocampal neuron database to generate mathematical models should help foster interactions between experimental and computational neuroscientists.