March 2012
Volume 53, Issue 14
ARVO Annual Meeting Abstract  |   March 2012
Cone Distribution Variations across Young Healthy Subjects
Author Affiliations & Notes
  • Ann E. Elsner
    Optometry, Indiana University, Bloomington, Indiana
  • Toco Y. Chui
    Optometry, Indiana University, Bloomington, Indiana
  • Lei Feng
    Eye center, Second Affiliated Hospital, College of Medicine, Zhejiang University, Zhejiang, China
  • Stephen A. Burns
    Optometry, Indiana University, Bloomington, Indiana
  • Footnotes
    Commercial Relationships  Ann E. Elsner, None; Toco Y. Chui, None; Lei Feng, None; Stephen A. Burns, None
  • Footnotes
    Support  NIH Grant EY007624, NIH Grant EY004395, NIH Grant P3019008
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 4645. doi:
  • Views
  • Share
  • Tools
    • Alerts
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Ann E. Elsner, Toco Y. Chui, Lei Feng, Stephen A. Burns; Cone Distribution Variations across Young Healthy Subjects. Invest. Ophthalmol. Vis. Sci. 2012;53(14):4645.

      Download citation file:

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

  • Supplements

Purpose: : To quantify the individual differences in cone distribution variations in young, healthy subjects, minimizing the previously reported effects of refractive error and eye length, aging, and disease on cone distribution.

Methods: : Seventeen subjects were recruited with these criteria: 18 - 35 yr of age, normal fundus, refractive error ≤ +3 D, and axial length ≤ 26 mm. Cone densities were assessed using a second generation Adaptive Optics Scanning Laser Ophthalmoscope, with samples of 820 to 840 nm +/- 20 nm at 185 microwatts covering 530 x 550 microns of the retina. Samples formed a + shape around the fovea, then were montaged. Cones were measured at a nominal 270, 630, 1480, and 2070 microns from the foveal center with custom software (Matlab, Mathworks) To avoid potential artifact in counting the cones due to shadowing from large retinal vessels, the temporal data were used. Axial length measurements were used to correct both the cone sampling positions and retinal area in mm2 (IOL Master, Zeiss Meditec).

Results: : Cone densities varied across subjects at all 4 positions, with a roughly 2:1 variation from maximum to minimum. Samples of particular interest are: A) 630 microns (28700 + 3600 cones/mm2), which is in a cone rich area but not in the central fovea where large aging changes occur and B) 2070 microns (11700 + 1530 cones/mm2), which is 7 deg eccentric and where rods begin to outnumber cones. The coefficients of variation were similar, 0.125 vs. 0.131; the normalized variances were not significantly different (F =1.101, p = 0.459). Cone density at the two regions was not strongly correlated and had a slope of 0.974, R2 = .114, P = .200). However, linear regression showed that the eyes with the higher cone densities at 630 microns had lower values for the ratio of cones at 2070: cones at 630, r2 = .632, p = .0002.

Conclusions: : In young, healthy eyes that are not strongly ametropic, there are still sizeable individual differences in cone densities. The lack of a constant ratio between more central and more peripheral cone densities indicates that there is not a nomogram for cone density vs. eccentricity that scales across individuals. Instead, cones from outside the fovea are likely lower in numbers when a larger proportion have migrated to provide foveal specialization.

Keywords: photoreceptors • imaging/image analysis: non-clinical • visual fields 

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.