Detecting changes in dynamic and complex acoustic environments

  1. Yves Boubenec  Is a corresponding author
  2. Jennifer Lawlor
  3. Urszula Górska
  4. Shihab Shamma
  5. Bernhard Englitz
  1. Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, France
  2. Radboud Universiteit, Netherlands

Abstract

Natural sounds such as wind or rain, are characterized by the statistical occurrence of their constituents. Despite their complexity, listeners readily detect changes in these contexts. We here address the neural basis of statistical decision-making using a combination of psychophysics, EEG and modelling. In a texture-based, change-detection paradigm, human performance and reaction times improved with longer pre-change exposure, consistent with improved estimation of baseline statistics. Change-locked and decision-related EEG responses were found in a centro-parietal scalp location, whose slope depended on change size, consistent with sensory evidence accumulation. The potential's amplitude scaled with the duration of pre-change exposure, suggesting a time-dependent decision threshold. Auditory cortex-related potentials showed no response to the change. A dual timescale, statistical estimation model accounted for subjects' performance. Furthermore, a decision-augmented auditory cortex model accounted for performance and reaction times, suggesting that the primary cortical representation requires little post-processing to enable change-detection in complex acoustic environments.

Article and author information

Author details

  1. Yves Boubenec

    Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, Paris, France
    For correspondence
    boubenec@ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0106-6947
  2. Jennifer Lawlor

    Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6116-3001
  3. Urszula Górska

    Department of Neurophysiology, Radboud Universiteit, Nijmegen, Netherlands
    Competing interests
    The authors declare that no competing interests exist.
  4. Shihab Shamma

    Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Bernhard Englitz

    Laboratoire des Systèmes Perceptifs, CNRS UMR 8248, Paris, France
    Competing interests
    The authors declare that no competing interests exist.

Funding

Agence Nationale de la Recherche (ANR-10-LABX-0087 IEC)

  • Yves Boubenec
  • Jennifer Lawlor
  • Shihab Shamma
  • Bernhard Englitz

Agence Nationale de la Recherche (ANR-10-IDEX-0001-02 PSL*)

  • Yves Boubenec
  • Jennifer Lawlor
  • Shihab Shamma
  • Bernhard Englitz

Advanced European Research Council (ERC 295603)

  • Yves Boubenec
  • Jennifer Lawlor
  • Shihab Shamma
  • Bernhard Englitz

European Commission's Marie Curie grant (660328)

  • Bernhard Englitz

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

Reviewing Editor

  1. Timothy EJ Behrens, University College London, United Kingdom

Ethics

Human subjects: All experiments were performed in accordance with the guidelines of the Helsinki Declaration. The Ethics Committees for Health Sciences at Université Paris Descartes approved the experimental procedures.

Version history

  1. Received: January 5, 2017
  2. Accepted: March 4, 2017
  3. Accepted Manuscript published: March 6, 2017 (version 1)
  4. Accepted Manuscript updated: March 8, 2017 (version 2)
  5. Version of Record published: March 27, 2017 (version 3)
  6. Version of Record updated: March 29, 2017 (version 4)
  7. Version of Record updated: August 23, 2017 (version 5)

Copyright

© 2017, Boubenec 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

  • 2,457
    views
  • 465
    downloads
  • 20
    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. Yves Boubenec
  2. Jennifer Lawlor
  3. Urszula Górska
  4. Shihab Shamma
  5. Bernhard Englitz
(2017)
Detecting changes in dynamic and complex acoustic environments
eLife 6:e24910.
https://doi.org/10.7554/eLife.24910

Share this article

https://doi.org/10.7554/eLife.24910

Further reading

    1. Neuroscience
    Ivan Tomić, Paul M Bays
    Research Article

    Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or ‘iconic’ memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these time scales. Here, we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.

    1. Neuroscience
    Emilio Salinas, Bashirul I Sheikh
    Insight

    Our ability to recall details from a remembered image depends on a single mechanism that is engaged from the very moment the image disappears from view.