September 2018
Volume 18, Issue 10
Open Access
Vision Sciences Society Annual Meeting Abstract  |   September 2018
Signatures of a probabilistic strategy in the control of saccadic eye movements
Author Affiliations
  • Matteo Lisi
    Centre for Applied Vision Research, City University of London
  • Joshua Solomon
    Centre for Applied Vision Research, City University of London
  • Michael Morgan
    Centre for Applied Vision Research, City University of London
Journal of Vision September 2018, Vol.18, 373. doi:10.1167/18.10.373
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      Matteo Lisi, Joshua Solomon, Michael Morgan; Signatures of a probabilistic strategy in the control of saccadic eye movements. Journal of Vision 2018;18(10):373. doi: 10.1167/18.10.373.

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

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Abstract

Saccades are rapid eye movements that orient the visual axis toward objects of interest to allow their processing by the central, high-acuity part of the retina. Our ability to collect efficiently visual information from the environment relies on the accuracy of saccades, which is limited by a combination of uncertainty in the location of the target and motor noise (van Beers, 2007). Additionally, saccades have a systematic tendency to fall short of their intended targets (hypometria), which is thought to result from a deliberate strategy that seeks to minimize a cost function favouring hypometric errors (e.g. Harris, 1995). In this study, we tested whether this strategy is probabilistic, i.e. whether it seeks to minimize the expected cost of saccadic errors by taking into account uncertainty in a statistically principled way. We asked observers to judge the location of peripheral targets, or make saccades to them, and manipulated their sensory uncertainty by varying the blurriness of the targets. Location judgments became more variable with increased blurriness, confirming the effectiveness of our manipulation. Most interestingly, increasing uncertainty resulted not only in larger spread of the saccade endpoints, but also in more hypometric errors, and in less frequent and more variable corrective saccades. Moreover, under high uncertainty, saccade endpoints were biased toward the average of target locations in a given block, suggesting that prior knowledge was integrated into saccade planning. In sum, we report that saccades made under varying levels of uncertainty about target location do indeed carry the signatures of a probabilistic-Bayesian strategy.

Meeting abstract presented at VSS 2018

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