Quantifying dynamic facial expressions under naturalistic conditions

  1. Jayson Jeganathan  Is a corresponding author
  2. Megan Campbell
  3. Matthew Hyett
  4. Gordon Parker
  5. Michael Breakspear
  1. University of Newcastle Australia, Australia
  2. University of Western Australia, Australia
  3. University of New South Wales, Australia

Abstract

Facial affect is expressed dynamically - a giggle, grimace, or an agitated frown. However, the characterization of human affect has relied almost exclusively on static images. This approach cannot capture the nuances of human communication or support the naturalistic assessment of affective disorders. Using the latest in machine vision and systems modelling, we studied dynamic facial expressions of people viewing emotionally salient film clips. We found that the apparent complexity of dynamic facial expressions can be captured by a small number of simple spatiotemporal states - composites of distinct facial actions, each expressed with a unique spectral fingerprint. Sequential expression of these states is common across individuals viewing the same film stimuli but varies in those with the melancholic subtype of major depressive disorder. This approach provides a platform for translational research, capturing dynamic facial expressions under naturalistic conditions and enabling new quantitative tools for the study of affective disorders and related mental illnesses.

Data availability

The DISFA dataset is publically available at http://mohammadmahoor.com/disfa/, and can be accessed by application at http://mohammadmahoor.com/disfa-contact-form/. The melancholia dataset is not publically available due to ethical and privacy considerations for patients, and because the original ethics approval does not permit sharing this data.

The following previously published data sets were used

Article and author information

Author details

  1. Jayson Jeganathan

    School of Psychology, University of Newcastle Australia, Newcastle, Australia
    For correspondence
    jayson.jeganathan@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4175-918X
  2. Megan Campbell

    School of Psychology, University of Newcastle Australia, Newcastle, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4051-1529
  3. Matthew Hyett

    School of Psychological Sciences, University of Western Australia, Perth, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Gordon Parker

    School of Psychiatry, University of New South Wales, Kensington, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. Michael Breakspear

    School of Psychology, University of Newcastle Australia, Newcastle, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4943-3969

Funding

Health Education and Training Institute Award in Psychiatry and Mental Health

  • Jayson Jeganathan

Rainbow Foundation

  • Jayson Jeganathan
  • Michael Breakspear

National Health and Medical Research Council (1118153,10371296,1095227)

  • Michael Breakspear

Australian Research Council (CE140100007)

  • Michael Breakspear

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

Reviewing Editor

  1. Alexander Shackman, University of Maryland, United States

Ethics

Human subjects: Participants provided informed consent for the study. Ethics approval was obtained from the University of New South Wales (HREC-08077) and the University of Newcastle (H-2020-0137). Figure 1a shows images of a person's face from the DISFA dataset. Consent to reproduce their image in publications was obtained by the original DISFA authors, and is detailed in the dataset agreement (http://mohammadmahoor.com/disfa-contact-form/) and the original paper (https://ieeexplore.ieee.org/document/6475933).

Version history

  1. Received: April 19, 2022
  2. Preprint posted: May 10, 2022 (view preprint)
  3. Accepted: August 24, 2022
  4. Accepted Manuscript published: August 31, 2022 (version 1)
  5. Version of Record published: September 2, 2022 (version 2)

Copyright

© 2022, Jeganathan 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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  1. Jayson Jeganathan
  2. Megan Campbell
  3. Matthew Hyett
  4. Gordon Parker
  5. Michael Breakspear
(2022)
Quantifying dynamic facial expressions under naturalistic conditions
eLife 11:e79581.
https://doi.org/10.7554/eLife.79581

Share this article

https://doi.org/10.7554/eLife.79581

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