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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
Research Article
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Cite this article as: eLife 2017;6:e24910 doi: 10.7554/eLife.24910

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.

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.

Reviewing Editor

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

Publication 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.

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