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A functional model for studying common trends across trial time in eye tracking experiments.

Publication ,  Journal Article
Dong, M; Telesca, D; Sugar, C; Shic, F; Naples, A; Johnson, SP; Li, B; Atyabi, A; Xie, M; Webb, SJ; Jeste, S; Faja, S; Levin, AR; Dawson, G ...
Published in: Stat Biosci
April 2023

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 components 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.

Duke Scholars

Published In

Stat Biosci

DOI

ISSN

1867-1764

Publication Date

April 2023

Volume

15

Issue

1

Start / End Page

261 / 287

Location

United States

Related Subject Headings

  • 4905 Statistics
  • 3102 Bioinformatics and computational biology
 

Citation

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Dong, M., Telesca, D., Sugar, C., Shic, F., Naples, A., Johnson, S. P., … Autism Biomarkers Consortium for Clinical Trials. (2023). A functional model for studying common trends across trial time in eye tracking experiments. Stat Biosci, 15(1), 261–287. https://doi.org/10.1007/s12561-022-09354-6
Dong, Mingfei, Donatello Telesca, Catherine Sugar, Frederick Shic, Adam Naples, Scott P. Johnson, Beibin Li, et al. “A functional model for studying common trends across trial time in eye tracking experiments.Stat Biosci 15, no. 1 (April 2023): 261–87. https://doi.org/10.1007/s12561-022-09354-6.
Dong M, Telesca D, Sugar C, Shic F, Naples A, Johnson SP, et al. A functional model for studying common trends across trial time in eye tracking experiments. Stat Biosci. 2023 Apr;15(1):261–87.
Dong, Mingfei, et al. “A functional model for studying common trends across trial time in eye tracking experiments.Stat Biosci, vol. 15, no. 1, Apr. 2023, pp. 261–87. Pubmed, doi:10.1007/s12561-022-09354-6.
Dong M, Telesca D, Sugar C, Shic F, Naples A, Johnson SP, Li B, Atyabi A, Xie M, Webb SJ, Jeste S, Faja S, Levin AR, Dawson G, McPartland JC, Şentürk D, Autism Biomarkers Consortium for Clinical Trials. A functional model for studying common trends across trial time in eye tracking experiments. Stat Biosci. 2023 Apr;15(1):261–287.
Journal cover image

Published In

Stat Biosci

DOI

ISSN

1867-1764

Publication Date

April 2023

Volume

15

Issue

1

Start / End Page

261 / 287

Location

United States

Related Subject Headings

  • 4905 Statistics
  • 3102 Bioinformatics and computational biology