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    Prospective Memory in the Red Zone: Cognitive Control and Capacity Sharing in a Complex, Multi-Stimulus Task

    76928.pdf (1.050Mb)
    Access Status
    Open access
    Authors
    Strickland, Luke
    Elliott, D.
    Wilson, Micah
    Loft, S.
    Neal, A.
    Heathcote, A.
    Date
    2019
    Type
    Journal Article
    
    Metadata
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    Citation
    Strickland, L. and Elliott, D. and Wilson, M.K. and Loft, S. and Neal, A. and Heathcote, A. 2019. Prospective Memory in the Red Zone: Cognitive Control and Capacity Sharing in a Complex, Multi-Stimulus Task. Journal of Experimental Psychology: Applied. 25(4): pp. 695–715.
    Source Title
    Journal of Experimental Psychology: Applied
    DOI
    10.1037/xap0000224
    ISSN
    1076-898X
    Faculty
    Faculty of Business and Law
    School
    Future of Work Institute
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DP160101891
    URI
    http://hdl.handle.net/20.500.11937/76664
    Collection
    • Curtin Research Publications
    Abstract

    © 2019 American Psychological Association. Remembering to perform a planned action upon encountering a future event requires event-based Prospective Memory (PM). PM is required in many human factors settings in which operators must process a great deal of complex, uncertain information from an interface. We study event-based PM in such an environment. Our task, which previous research has found is very demanding (Palada, Neal, Tay, & Heathcote, 2018), requires monitoring ships as they cross the ocean on a display. We applied the Prospective Memory Decision Control Model (Strickland, Loft, Remington, & Heathcote, 2018) to understand the cognitive mechanisms that underlie PM performance in such a demanding environment. We found evidence of capacity sharing between monitoring for PM items and performing the ongoing surveillance task, whereas studies of PM in simpler paradigms have not (e.g., Strickland et al., 2018). We also found that participants applied proactive and reactive control (Braver, 2012) to adapt to the demanding task environment. Our findings illustrate the value of human factors simulations to study capacity sharing between competing task processes. They also illustrate the value of cognitive models to illuminate the processes underlying adaptive behavior in complex environments.

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