October 2020
Volume 20, Issue 11
Open Access
Vision Sciences Society Annual Meeting Abstract  |   October 2020
Eye tracking reveals two components of monitoring in prospective memory
Author Affiliations & Notes
  • Seth, R. Koslov
    University of Texas at Austin
  • Landry, S. Bulls
    University of Texas at Austin
  • Jarrod, A. Lewis-Peacock
    University of Texas at Austin
  • Footnotes
    Acknowledgements  R01 EY028746, UT Austin Provost Graduate Fellowship
Journal of Vision October 2020, Vol.20, 935. doi:https://doi.org/10.1167/jov.20.11.935
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      Seth, R. Koslov, Landry, S. Bulls, Jarrod, A. Lewis-Peacock; Eye tracking reveals two components of monitoring in prospective memory. Journal of Vision 2020;20(11):935. https://doi.org/10.1167/jov.20.11.935.

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      © ARVO (1962-2015); The Authors (2016-present)

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Prospective memory (PM) describes the ability to remember to perform goal-relevant actions at an appropriate time in the future despite other concurrent demands. Previous research posits a critical role for strategic, effortful monitoring of the environment for PM-related cues in successful PM task performance. The common method for inferring strategic monitoring in PM tasks is to compare response time slowing on an ongoing task performed with versus without a concurrent PM task, referred to as PM costs. However, the use of this indirect measure as a proxy for strategic monitoring has led to a debate as to how costs and subsequent PM performance are related to strategic monitoring. In the current experiment, participants performed an ongoing visual search task that varied in difficulty level while concurrently performing a PM-task that involved identifying the occurrences of face or scene targets presented elsewhere on the screen. We collected eye-tracking data in order to quantify monitoring for PM-targets, which we then related to both PM costs and PM performance. We found that PM costs were comprised of two distinct components: an overt monitoring component related to strategic evaluation of PM-target lures, and a covert monitoring component involving changes in gaze on the ongoing task. While both components were related to PM costs, the relative contribution of overt and covert monitoring was modulated by ongoing task demands (t=9.11, p <.001). Additionally, we found that accounting for both monitoring components explained the most variance in PM performance, as opposed to relying on overt monitoring alone (Wilcoxon pseudo-median = 0.289, p<.001). These results further specify multiple components of PM costs, and indicate that the relationship between costs and performance depends on the relative contribution of overt and covert monitoring processes. Future experiments would benefit from eye-tracking to more specifically explain the role of monitoring in PM.


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