Reliably measuring learning-dependent distractor suppression with eye tracking

In the field of psychological science, behavioral performance in computer-based cognitive tasks often exhibits poor reliability. The absence of reliable measures of cognitive processes contributes to non-reproducibility in the field and impedes the investigation of individual differences. Specifically in visual search paradigms, response time-based measures have shown poor test-retest reliability and internal consistency across attention capture and distractor suppression, but one study has demonstrated the potential for oculomotor measures to exhibit superior reliability. Therefore, in this study, we investigated three datasets to compare the reliability of learning-dependent distractor suppression measured via distractor fixations (oculomotor capture) and latency to fixate the target (fixation times). Our findings reveal superior split-half reliability of oculomotor capture compared to that of fixation times regardless of the critical distractor comparison, with the reliability of oculomotor capture in most cases falling within the range that is acceptable for the investigation of individual differences. We additionally find that older adults have superior oculomotor reliability compared with young adults, potentially addressing a significant limitation in the aging literature of high variability in response time measures due to slower responses. Our findings highlight the utility of measuring eye movements in the pursuit of reliable indicators of distractor processing and the need to further test and develop additional measures in other sensory domains to maximize statistical power, reliability, and reproducibility.

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Publication Details

Journal
Behavior Research Methods
Published
2024-12-18
DOI
https://doi.org/10.3758/s13428-024-02552-8
Citations
7
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
2.40

Funders

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article

Reliably measuring learning-dependent distractor suppression with eye tracking

Andy Jeesu Kim, Laurent Grégoire, Brian A. Anderson
7 citations
Behavior Research Methods
Neural and Behavioral Psychology Studies
2.40
article

Reliably measuring learning-dependent distractor suppression with eye tracking

Andy Jeesu Kim, Laurent Grégoire, Brian A. Anderson
article en
7 citations

Abstract

In the field of psychological science, behavioral performance in computer-based cognitive tasks often exhibits poor reliability. The absence of reliable measures of cognitive processes contributes to non-reproducibility in the field and impedes the investigation of individual differences. Specifically in visual search paradigms, response time-based measures have shown poor test-retest reliability and internal consistency across attention capture and distractor suppression, but one study has demonstrated the potential for oculomotor measures to exhibit superior reliability. Therefore, in this study, we investigated three datasets to compare the reliability of learning-dependent distractor suppression measured via distractor fixations (oculomotor capture) and latency to fixate the target (fixation times). Our findings reveal superior split-half reliability of oculomotor capture compared to that of fixation times regardless of the critical distractor comparison, with the reliability of oculomotor capture in most cases falling within the range that is acceptable for the investigation of individual differences. We additionally find that older adults have superior oculomotor reliability compared with young adults, potentially addressing a significant limitation in the aging literature of high variability in response time measures due to slower responses. Our findings highlight the utility of measuring eye movements in the pursuit of reliable indicators of distractor processing and the need to further test and develop additional measures in other sensory domains to maximize statistical power, reliability, and reproducibility.

Behavior Research MethodsVol. 57(1)
University of Southern California (US), Texas A&M University (US)
University of Southern California
No poverty
Openalex Percentile: Top 11%
Neural and Behavioral Psychology Studies
2.40
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