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Human Visual Search Does Not Maximize the Post-Saccadic Probability of Identifying Targets

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  • Camille Morvan
  • Laurence T Maloney

Abstract

Researchers have conjectured that eye movements during visual search are selected to minimize the number of saccades. The optimal Bayesian eye movement strategy minimizing saccades does not simply direct the eye to whichever location is judged most likely to contain the target but makes use of the entire retina as an information gathering device during each fixation. Here we show that human observers do not minimize the expected number of saccades in planning saccades in a simple visual search task composed of three tokens. In this task, the optimal eye movement strategy varied, depending on the spacing between tokens (in the first experiment) or the size of tokens (in the second experiment), and changed abruptly once the separation or size surpassed a critical value. None of our observers changed strategy as a function of separation or size. Human performance fell far short of ideal, both qualitatively and quantitatively. Author Summary: Vision is most sensitive to fine detail at the center of gaze (the fovea). We typically move our eyes several times a second to build up an accurate picture of the world around us and find objects of interest. Very recently, researchers have developed models of how a visual system like ours could search a scene for a specific target with the smallest possible number of eye fixations. In two experiments, we tested the assumptions underlying such models. We set up visual “games” in which observers were rewarded for their performance in moving their eyes once to recognize simple targets. To do well (earn the maximum possible reward), observers had to move their eyes according to the predictions of recent models of eye movement. We found that our observers failed to choose optimal eye movement strategies and failed to maximize their potential winnings. Our results suggest a simpler picture of eye movement selection, driven by a few simple heuristic rules that lead to good but not optimal performance in everyday tasks.

Suggested Citation

  • Camille Morvan & Laurence T Maloney, 2012. "Human Visual Search Does Not Maximize the Post-Saccadic Probability of Identifying Targets," PLOS Computational Biology, Public Library of Science, vol. 8(2), pages 1-11, February.
  • Handle: RePEc:plo:pcbi00:1002342
    DOI: 10.1371/journal.pcbi.1002342
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    References listed on IDEAS

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    1. Jiri Najemnik & Wilson S. Geisler, 2005. "Optimal eye movement strategies in visual search," Nature, Nature, vol. 434(7031), pages 387-391, March.
    2. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, April.
    3. Herbert A. Simon, 1991. "Bounded Rationality and Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 125-134, February.
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    Cited by:

    1. Emre Akbas & Miguel P Eckstein, 2017. "Object detection through search with a foveated visual system," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-28, October.

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