April 2009
Volume 50, Issue 13
Free
ARVO Annual Meeting Abstract  |   April 2009
Optical and Neural Contributions to the Equivalent Intrinsic Blur of the Visual System
Author Affiliations & Notes
  • J. McAnany
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois
  • M. Shahidi
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois
  • R. Zelkha
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois
  • K. Alexander
    Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, Illinois
  • Footnotes
    Commercial Relationships  J. McAnany, None; M. Shahidi, None; R. Zelkha, None; K. Alexander, None.
  • Footnotes
    Support  NIH research grants EY014275 (MS) and EY08301 (KA). NIH core grant EY01792, Dept of Veterans Affairs (MS), and an unrestricted departmental grant from Research to Prevent Blindness.
Investigative Ophthalmology & Visual Science April 2009, Vol.50, 3045. doi:
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    • Get Citation

      J. McAnany, M. Shahidi, R. Zelkha, K. Alexander; Optical and Neural Contributions to the Equivalent Intrinsic Blur of the Visual System. Invest. Ophthalmol. Vis. Sci. 2009;50(13):3045.

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

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Abstract

Purpose: : Although equivalent intrinsic blur has been evaluated psychophysically in visually normal subjects and in individuals with visual dysfunction, the relative contribution of optical and neural factors to equivalent intrinsic blur has not been addressed systematically. The purpose of this study was to develop a method for partitioning equivalent intrinsic blur into the underlying neural and optical components.

Methods: : The visual acuity of fifteen visually normal individuals (ages 23 to 58) was measured for tumbling E optotypes presented briefly (80 ms) on a computer display with a background luminance of 110 cd/m2. Stimuli were either unblurred or blurred through convolution with Gaussians of different widths (σ = 0.8, 3.2 or 12.9 arcmin). The observers’ equivalent intrinsic blur int) was estimated with a standard model: MAR = MAR0[1 + (σstim/ σint)2 ]0.5, where σstim is the width (σ) of the Gaussian convolved with the stimulus, MAR is visual acuity for a given value of σstim, and MAR0 is visual acuity for the unblurred stimulus. Optical blur (σopt) was defined as the width of the point spread function derived from Shack-Hartmann aberrometry. Neural blur neu) was defined as (σint2 - σopt2)0.5, under the assumption that σint can be modeled as the sum of two independent Gaussian distributions representing σopt and σneu.

Results: : The estimate of unblurred visual acuity (MAR0) ranged from 0.9 to 2.7 arcmin, and intrinsic blur (σint) was correlated significantly with MAR0 (r=0.97, p<0.001). Partitioning σint into σopt and σneu demonstrated that optical blur was the primary determinant of visual acuity in subjects with smaller values of MAR0 (better visual acuity), whereas neural blur was the main factor in subjects with larger values of MAR0.

Keywords: visual acuity • optical properties • pattern vision 
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