September 2017
Volume 17, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   August 2017
Fixation-related Potentials as a Natural Index of Task Difficulty: Single-trial Classification
Author Affiliations
  • Jon Touryan
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
  • David Slayback
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
  • Anthony Ries
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
Journal of Vision August 2017, Vol.17, 530. doi:10.1167/17.10.530
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Jon Touryan, David Slayback, Anthony Ries; Fixation-related Potentials as a Natural Index of Task Difficulty: Single-trial Classification. Journal of Vision 2017;17(10):530. doi: 10.1167/17.10.530.

      Download citation file:


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

      ×
  • Supplements
Abstract

Eye movements are a pervasive element of our everyday interactions with the environment and are essential for many real-world tasks. As such, they provide a natural and frequent event upon which to examine evoked neural activity related to visual perception. Previous studies have shown that the evoked activity around each fixation is a mixture of bottom-up (stimulus driven) and top-down (attentional control) components, and thus modulated by cognitive processes associated with a given task. In this study we sought to quantify the effect of task difficulty on the lambda response, an early component of the fixation related potential (FRP). While prior experiments have shown changes in the lambda amplitude as a function of task difficulty, it is not clear if this effect can be measured on a single-trial basis. We addressed this question by parametrically modulating visual task difficulty in two different paradigms that utilized eye movements. In the first instance, we manipulated difficulty via the working memory load of an N-Back task where gaze position was systematically guided across a stimulus grid. In the second instance, we used a modified Tetris game where difficulty was manipulated via tetrad fall speed while gaze position was unconstrained. Applying linear discriminant analysis to the FRP we were able to classify fixations occurring under conditions of high versus low task difficulty, in both paradigms, at a level of accuracy significantly above chance. As expected, these classifiers identified the lambda component as containing the most discriminant activity within the fixation epoch. We compare these results to other established neural and physiological correlates of task difficulty, also measured during the experiment. This approach may provide a more direct way to index cognitive demands in real-world tasks without having to rely on secondary measures or obtrusive stimulus probes.

Meeting abstract presented at VSS 2017

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×