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A Functional Model for Studying Common Trends Across Trial Time in Eye Tracking Experiments

Author

Listed:
  • Mingfei Dong

    (University of California, Los Angeles)

  • Donatello Telesca

    (University of California, Los Angeles)

  • Catherine Sugar

    (University of California, Los Angeles
    University of California, Los Angeles)

  • Frederick Shic

    (Seattle Children’s Research Institute
    University of Washington)

  • Adam Naples

    (Yale University)

  • Scott P. Johnson

    (University of California)

  • Beibin Li

    (Seattle Children’s Research Institute
    University of Washington)

  • Adham Atyabi

    (Seattle Children’s Research Institute
    University of Colorado)

  • Minhang Xie

    (Seattle Children’s Research Institute)

  • Sara J. Webb

    (Seattle Children’s Research Institute
    University of Washington)

  • Shafali Jeste

    (University of South California)

  • Susan Faja

    (Harvard Medical School)

  • April R. Levin

    (Boston Children’s Hospital and Harvard Medical School)

  • Geraldine Dawson

    (Duke University)

  • James C. McPartland

    (Yale University)

  • Damla Şentürk

    (University of California, Los Angeles)

Abstract

Eye tracking (ET) experiments commonly record the continuous trajectory of a subject’s gaze on a two-dimensional screen throughout repeated presentations of stimuli (referred to as trials). Even though the continuous path of gaze is recorded during each trial, commonly derived outcomes for analysis collapse the data into simple summaries, such as looking times in regions of interest, latency to looking at stimuli, number of stimuli viewed, number of fixations, or fixation length. In order to retain information in trial time, we utilize functional data analysis (FDA) for the first time in literature in the analysis of ET data. More specifically, novel functional outcomes for ET data, referred to as viewing profiles, are introduced that capture the common gazing trends across trial time which are lost in traditional data summaries. Mean and variation of the proposed functional outcomes across subjects are then modeled using functional principal component analysis. Applications to data from a visual exploration paradigm conducted by the Autism Biomarkers Consortium for Clinical Trials showcase the novel insights gained from the proposed FDA approach, including significant group differences between children diagnosed with autism and their typically developing peers in their consistency of looking at faces early on in trial time.

Suggested Citation

  • Mingfei Dong & Donatello Telesca & Catherine Sugar & Frederick Shic & Adam Naples & Scott P. Johnson & Beibin Li & Adham Atyabi & Minhang Xie & Sara J. Webb & Shafali Jeste & Susan Faja & April R. Lev, 2023. "A Functional Model for Studying Common Trends Across Trial Time in Eye Tracking Experiments," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 261-287, April.
    • Handle: RePEc:spr:stabio:v:15:y:2023:i:1:d:10.1007_s12561-022-09354-6
    DOI: 10.1007/s12561-022-09354-6
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    References listed on IDEAS

    as
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