Abstract

In almost every natural environment, sounds are reflected by nearby objects, producing many delayed and distorted copies of the original sound, known as reverberation. Our brains usually cope well with reverberation, allowing us to recognize sound sources regardless of their environments. In contrast, reverberation can cause severe difficulties for speech recognition algorithms and hearing-impaired people. The present study examines how the auditory system copes with reverberation. We trained a linear model to recover a rich set of natural, anechoic sounds from their simulated reverberant counterparts. The model neurons achieved this by extending the inhibitory component of their receptive filters for more reverberant spaces, and did so in a frequency-dependent manner. These predicted effects were observed in the responses of auditory cortical neurons of ferrets in the same simulated reverberant environments. Together, these results suggest that auditory cortical neurons adapt to reverberation by adjusting their filtering properties in a manner consistent with dereverberation.

Data availability

We have provided our Matlab scripts for generating our model and figures on Github: https://github.com/PhantomSpike/DeReverb.

The following data sets were generated

Article and author information

Author details

  1. Aleksandar Z Ivanov

    Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
    For correspondence
    aleksandar.ivanov@dpag.ox.ac.uk
    Competing interests
    No competing interests declared.
  2. Andrew J King

    Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
    Competing interests
    Andrew J King, Senior editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5180-7179
  3. Ben DB Willmore

    Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
    For correspondence
    benjamin.willmore@dpag.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2969-7572
  4. Kerry MM Walker

    Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
    For correspondence
    kerry.walker@dpag.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1043-5302
  5. Nicol S Harper

    Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
    For correspondence
    nicol.harper@dpag.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7851-4840

Funding

Wellcome Trust (WT108369/Z/2015/Z)

  • Andrew J King

Biotechnology and Biological Sciences Research Council (BB/M010929/1)

  • Kerry MM Walker

Oxford University Press (Christopher Welch Scholarship)

  • Aleksandar Z Ivanov

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

Ethics

Animal experimentation: Animal experimentation: The animal procedures were approved by the University of Oxford Committee on Animal Care and Ethical Review and were carried out under license from the UK Home Office, in accordance with the Animals (Scientific Procedures) Act 1986 and in line with the 3Rs. Project licence PPL 30/3181 and PIL l23DD2122. All surgery was performed under general anesthesia (ketamine/medetomidine) and every effort was made to minimize suffering.

Copyright

© 2022, Ivanov 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

  • 1,227
    views
  • 234
    downloads
  • 11
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Aleksandar Z Ivanov
  2. Andrew J King
  3. Ben DB Willmore
  4. Kerry MM Walker
  5. Nicol S Harper
(2022)
Cortical adaptation to sound reverberation
eLife 11:e75090.
https://doi.org/10.7554/eLife.75090

Share this article

https://doi.org/10.7554/eLife.75090

Further reading

    1. Neuroscience
    Li Shen, Shuo Li ... Yi Jiang
    Research Article

    When observing others’ behaviors, we continuously integrate their movements with the corresponding sounds to enhance perception and develop adaptive responses. However, how the human brain integrates these complex audiovisual cues based on their natural temporal correspondence remains unclear. Using electroencephalogram (EEG), we demonstrated that rhythmic cortical activity tracked the hierarchical rhythmic structures in audiovisually congruent human walking movements and footstep sounds. Remarkably, the cortical tracking effects exhibit distinct multisensory integration modes at two temporal scales: an additive mode in a lower-order, narrower temporal integration window (step cycle) and a super-additive enhancement in a higher-order, broader temporal window (gait cycle). Furthermore, while neural responses at the lower-order timescale reflect a domain-general audiovisual integration process, cortical tracking at the higher-order timescale is exclusively engaged in the integration of biological motion cues. In addition, only this higher-order, domain-specific cortical tracking effect correlates with individuals’ autistic traits, highlighting its potential as a neural marker for autism spectrum disorder. These findings unveil the multifaceted mechanism whereby rhythmic cortical activity supports the multisensory integration of human motion, shedding light on how neural coding of hierarchical temporal structures orchestrates the processing of complex, natural stimuli across multiple timescales.

    1. Evolutionary Biology
    2. Neuroscience
    Gregor Belušič
    Insight

    The first complete 3D reconstruction of the compound eye of a minute wasp species sheds light on the nuts and bolts of size reduction.