September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Neural Markers of Switch-Cost Predict Cognitive Demand Avoidance.
Author Affiliations
  • Jeffrey Nador
    Wright State University
  • Ion Juvina
    Wright State University
  • Brad Minnery
    Wright State Research Institute
  • Assaf Harel
    Wright State University
Journal of Vision September 2018, Vol.18, 976. doi:https://doi.org/10.1167/18.10.976
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      Jeffrey Nador, Ion Juvina, Brad Minnery, Assaf Harel; Neural Markers of Switch-Cost Predict Cognitive Demand Avoidance.. Journal of Vision 2018;18(10):976. https://doi.org/10.1167/18.10.976.

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

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Abstract

Generally, people tend to match their cognitive effort to the demands of tasks they encounter. For example, minimizing the costs of switching tasks when given free choice between low- and high-demand variants of the same task. This cognitive demand avoidance (DA) usually manifests overtly in behavior, though it likely also occurs covertly. We sought to assess covert DA by recording Event-Related Potentials (ERPs) in a task-switching go/no-go paradigm. To begin each trial, participants would freely choose between two decks of cards. Upon choosing one, a cue card would appear, its color specifying the task, followed by a target card. Participants were instructed to press spacebar on target appearance if the cue card was red (go), but withhold their response if the target was an ace (no-go); alternatively, if the cue was black, participants were required to press spacebar (go) unless the target was a ten (no-go). Critically, the decks varied in their trial-to-trial probability of task-switching: the low-demand deck switched on 10% of trials, the high-demand deck on 90%. We could thus measure participants' DA as their proportion of low-demand deck selections. To elucidate the covert cognitive decision process underlying DA, we recorded both cue- and target-evoked ERPs. We focused on the P3 component to assess changes related to task switches as a function of DA. Validating our task-switching go/no-go paradigm, we found higher P3 amplitudes for no-go than go trials. Further, we found that P3 amplitude varied as a function of task-switching, with higher amplitude for switch compared to no-switch trials (switch-cost). Critically, this neural marker of task switching was predictive of DA: people with higher P3 switch-cost demonstrated higher DA. We conclude that individual differences in covert DA can be assessed using electrophysiological measures.

Meeting abstract presented at VSS 2018

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