July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
The Shape of the Psychometric Function in Blur Discrimination Judgments
Author Affiliations & Notes
  • Glen L McCormack
    Vision Science, New England Coll of Optometry, Boston, Massachusetts, United States
  • Jeffrey Ferrucci
    Vision Science, New England Coll of Optometry, Boston, Massachusetts, United States
  • Anthony Guarino
    Vision Science, New England Coll of Optometry, Boston, Massachusetts, United States
  • Peter J. Bex
    Psychology, Northeastern University, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Glen McCormack, None; Jeffrey Ferrucci, None; Anthony Guarino, None; Peter Bex, None
  • Footnotes
    Support  New England College of Optometry Research Fund
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 4756. doi:
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      Glen L McCormack, Jeffrey Ferrucci, Anthony Guarino, Peter J. Bex; The Shape of the Psychometric Function in Blur Discrimination Judgments. Invest. Ophthalmol. Vis. Sci. 2018;59(9):4756.

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

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Abstract

Purpose : The effect of motion on blur sensitivity (“motion sharpening”) could affect the detectability of blur caused by accommodative error in 3D displays. Discrimination of blur during motion has been tested by rapid adaptive psychophysical methods which assume that the shape of the psychometric function is a logistic curve (“PEST”) or a Weibull curve (“QUEST”). Because the accuracy of these adaptive methods might depend on the actual shape of the psychometric function, we have tested whether a logistic curve or a Weibull curve more accurately fits blur discrimination data.

Methods : Six healthy young adults wearing full refractive corrections viewed images on an Asus 3D display at 1M. The test images were 1°w x 2°h bars of 50% contrast on a dark gray background, with 42 minute of arc gaussian blurs on the vertical edges. The bars moved leftward or rightward at 1.0°/s, either above or below a small fixation point. Motion sharpening reduced perceived edge blur, with the trailing edge more sharpened than the leading edge. We evaluated the shape of the psychometric function for matching the leading edge blur to the trailing edge blur. The approximate match blur was initially determined by PEST, after which the psychometric function was sampled by a constant stimulus method with 20 repeated trials at each of nine leading edge blur values centered on the initial PEST match value. Levenberg-Marquardt algorithms in LabView software fit logistic and Weibull curves to the constant stimulus data. Match values and chi-square goodness of fit values were determined for each curve.

Results : In leftward motion the logistic curve more accurately fit the data than the Weibull curve in all subjects, and for rightward motion the logistic curve more accurately fit the data in two thirds of subjects. To determine differences between the logistic and Weibull match-values, two separate paired t-tests of match values were conducted with alpha adjusted by the Bonferroni technique (p < .025) to control for inflated Type I error rates. The logistic analysis produced statistically significantly lower match values than the Weibull analysis in both leftward motion (p<.001) and rightward motion (p<.021).

Conclusions : The logistic curve more accurately represented the psychometric function in blur discrimination judgments than did the Weibull curve.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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