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Testing the magnocellular-pathway advantage in facial expressions processing for consistency over time

  • Ben-Gurion University of the Negev
  • University of California at Los Angeles

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The ability to identify facial expressions rapidly and accurately is central to human evolution. Previous studies have demonstrated that this ability relies to a large extent on the magnocellular, rather than parvocellular, visual pathway, which is biased toward processing low spatial frequencies. Despite the generally consistent finding, no study to date has investigated the reliability of this effect over time. In the present study, 40 participants completed a facial emotion identification task (fearful, happy, or neutral faces) using facial images presented at three different spatial frequencies (low, high, or broad spatial frequency), at two time points separated by one year. Bayesian statistics revealed an advantage for the magnocellular pathway in processing facial expressions; however, no effect for time was found. Furthermore, participants’ RT patterns of results were highly stable over time. Our replication, together with the consistency of our measurements within subjects, underscores the robustness of this effect. This capacity, therefore, may be considered in a trait-like manner, suggesting that individuals may possess various ability levels for processing facial expressions that can be captured in behavioral measurements.

Original languageEnglish
Article number107352
JournalNeuropsychologia
Volume138
DOIs
StatePublished - 17 Feb 2020

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Ltd

Funding

This work was supported by a grant from the Israel Anti-Drug Authority to Prof. Rassovsky . The funding source had no involvement in the study.

Funders
Israel Anti-Drug Authority

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Bayesian statistics
    • Facial expression
    • Magnocellular
    • Parvocellular
    • Spatial frequency

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