October 2020
Volume 20, Issue 11
Open Access
Vision Sciences Society Annual Meeting Abstract  |   October 2020
The Effect of Spatial Uncertainty on Visual Efficiency
Author Affiliations & Notes
  • Darshan Thapa
    New York University
  • Sangita Chakraborty
    Bronx High School of Science
  • Denis Pelli
    New York University
  • Footnotes
    Acknowledgements  NIH grant R01 EY027964 to DGP & NYU Dean's Undergraduate Research Fund to DT
Journal of Vision October 2020, Vol.20, 1717. doi:https://doi.org/10.1167/jov.20.11.1717
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      Darshan Thapa, Sangita Chakraborty, Denis Pelli; The Effect of Spatial Uncertainty on Visual Efficiency. Journal of Vision 2020;20(11):1717. doi: https://doi.org/10.1167/jov.20.11.1717.

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

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Abstract

Intuition suggests that increasing uncertainty (the number of possible options) will make it harder to choose correctly. We compared the effects of uncertainty on human and ideal observers, where the “ideal” makes the maximum likelihood choice. In signal detection theory, efficiency is calculated as the fraction of the energy used by a human that is required by an ideal observer to attain the same performance. Humans identify a gabor or a letter in noise with an efficiency of 3% or 15%, respectively. If introducing spatial uncertainty affects the human and ideal observers differently, then there will be a change in efficiency. We assess this by comparing human vs ideal recognition of fixed-size targets (a gabor of two possible orientations or a Sloan letter of nine possible) in noise at several degrees of spatial uncertainty. Results from 38 observers show that increasing spatial uncertainty from 1 to 104 locations affects efficiency differently for the two tasks. For gabors, efficiency increased by 3.6x from 3.2%±0.5% to 11.6%±2.5%, but for letters the 5.3% efficiency was unchanged due to similar small increases in the thresholds of the human and ideal. This suggests that more complex tasks (with a greater number of more complex objects) are less affected by uncertainty.

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