An Introduction to Perimetry and the Normal Visual Field

  • Jason J. S. Barton
  • Michael Benatar
Chapter
Part of the Current Clinical Neurology book series (CCNEU)

Abstract

The analysis of the visual field is an important part of the neurologic and ophthalmologic examination. The eye exists to see, and more than 40% of the human brain is involved in visual processing in some fashion. Not surprisingly, many diseases of these two structures affect vision. Assessing the visual field is often helpful in localizing, diagnosing, and following the course and efficacy of treatment of these diseases.

Keywords

Visual Field Retinal Ganglion Cell Ocular Hypertension Automate Perimetry Frequency Doubling Technology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Lindenmuth K, Skuta G, Rabbani R, Musch D. Effects of pupillary constriction on automated perimetry in normal eyes. Ophthalmology 1989; 96: 1298–1301.PubMedGoogle Scholar
  2. 2.
    Autzen T, Work K. The effect of learning and age on short-term fluctuation and mean sensitivity of automated static perimetry. Acta Ophthalmol (Copenh) 1990; 68: 327–330.CrossRefGoogle Scholar
  3. 3.
    Stewart WC, Hunt HH. Threshold variation in automated perimetry. Sury Ophthalmol 1993; 37: 353–361.CrossRefGoogle Scholar
  4. 4.
    Wolf E, Nadroski AS. Extent of the visual field: changes with age and oxygen tension. Arch Ophthalmol 1971; 86: 637–642.PubMedCrossRefGoogle Scholar
  5. 5.
    Drance SM, Berry V, Hughes A. Studies on the effects of age on the central and peripheral isopters of the visual field in normal subjects. Am J Ophthalmol 1967; 63: 1667–1672.PubMedGoogle Scholar
  6. 6.
    Drance SM, Berry V, Hughes A. The effects of age on the central isopter of the normal visual field. Can J Ophthalmol 1967; 2: 79–82.PubMedGoogle Scholar
  7. 7.
    Haas A, Flammer J, Schneider U. Influence of age on the visual fields of normal subjects. Am J Ophthalmol 1986; 101: 199–203.PubMedGoogle Scholar
  8. 8.
    Johnson CA, Adams AJ, Lewis RA. Evidence for a neural basis of age-related visual field loss in normal observers. Invest Ophthalmol Vis Sci 1989; 30: 2056–2064.PubMedGoogle Scholar
  9. 9.
    Katz J, Sommer A. Asymmetry and the normal hill of vision. Arch Ophthalmol 1986; 104: 65–68.PubMedCrossRefGoogle Scholar
  10. 10.
    Loewenfeld I. Pupillary changes related to age. In: Thompson H, Daroff R, Frisén L, Glaser J, Sanders M, eds. Topics in Neuro-ophthalmology. Baltimore: Williams & Wilkins, 1979: 124–150.Google Scholar
  11. 11.
    Frisen L. High-pass resolution perimetry and age-related loss of visual pathway neurons. Acta Ophthalmol (Copenh) 1991; 69: 511–515.CrossRefGoogle Scholar
  12. 12.
    Quigley H, Sanchez R, Dunkelberger G, L’Hernault N, Baginski T. Chronic glaucoma selectively damages large optic nerve fibers. Invest Ophthalmol Vis Sci 1987; 28: 913–920.PubMedGoogle Scholar
  13. 13.
    Quigley H, Dunkelberger G, Baginksi T, Green W. Chronic human glaucoma causes selectively greater loss of large optic nerve fibers. Ophthalmology 1988; 95: 357–363.PubMedGoogle Scholar
  14. 14.
    Sample PA, Bosworth CF, Weinreb RN. Short-wavelength automated perimetry and motion automated perimetry in patients with glaucoma. Arch Ophthalmol 1997; 115: 1129–1133.PubMedCrossRefGoogle Scholar
  15. 15.
    Casagrande V. A third parallel visual pathway to primate area VI. Trends Neurosci 1994; 17: 305–310.PubMedCrossRefGoogle Scholar
  16. 16.
    Frisen L, Nikolajeff F. Properties of high-pass resolution perimetry targets. Acta Ophthalmol (Copenh) 1993; 71: 320–326.CrossRefGoogle Scholar
  17. 17.
    Frisen L. High-pass resolution perimetry: central-field neuroretinal correlates. Vision Res 1995; 35: 293–301.PubMedCrossRefGoogle Scholar
  18. 18.
    Frisén L. High-pass resolution perimetry: evidence for parvocellular channel dependence. Neuro-ophthalmology 1992; 12: 257–264.CrossRefGoogle Scholar
  19. 19.
    Sample PA, Ahn DS, Lee PC, Weinreb RN. High-pass resolution perimetry in eyes with ocular hypertension and primary open-angle glaucoma. Am J Ophthalmol 1992; 113: 309–316.PubMedGoogle Scholar
  20. 20.
    Iester M, Capris P, Altieri M, Zingirian M, Traverso CE. Correlation between high-pass resolution perimetry and standard threshold perimetry in subjects with glaucoma and ocular hypertension. Int Ophthalmol 1999; 23: 99–103.PubMedCrossRefGoogle Scholar
  21. 21.
    Martinez GA, Sample PA, Weinreb RN. Comparison of high-pass resolution perimetry and standard automated perimetry in glaucoma. Am J Ophthalmol 1995; 119: 195–201.PubMedGoogle Scholar
  22. 22.
    Lindblom B, Hoyt WF. High-pass resolution perimetry in neuro-ophthalmology: clinical impressions. Ophthalmology 1992; 99: 700–705.PubMedGoogle Scholar
  23. 23.
    Chauhan BC, House PH. Intra-test variability in conventional and high-pass resolution perimetry. Ophthalmology 1991; 98: 79–83.PubMedGoogle Scholar
  24. 24.
    Martin-Boglind L, Graves A, Wanger P. The effect of topical antiglaucoma drugs on the results of high-pass resolution perimetry. Am J Ophthalmol 1991; 111: 711–715.PubMedGoogle Scholar
  25. 25.
    Westcott MC, Fitzke FW, Hitchings RA. Abnormal motion displacement thresholds are associated with fine scale luminance sensitivity loss in glaucoma. Vision Res 1998; 38: 3171–3180.PubMedCrossRefGoogle Scholar
  26. 26.
    Wall M, Ketoff KM. Random dot motion perimetry in patients with glaucoma and in normal subjects. Am J Ophthalmol 1995; 120: 587–596.PubMedGoogle Scholar
  27. 27.
    Wall M, Jennisch CS, Munden PM. Motion perimetry identifies nerve fiber bundle-like defects in ocular hypertension. Arch Ophthalmol 1997; 115: 26–33.PubMedCrossRefGoogle Scholar
  28. 28.
    Bosworth CF, Sample PA, Gupta N, Bathija R, Weinreb RN. Motion automated perimetry identifies early glaucomatous field defects. Arch Ophthalmol 1998; 116: 1153–1158.PubMedGoogle Scholar
  29. 29.
    Wall M, Montgomery EB. Using motion perimetry to detect visual field defects in patients with idiopathic intracranial hypertension: a comparison with conventional automated perimetry. Neurology 1995; 45: 1169–1175.PubMedCrossRefGoogle Scholar
  30. 30.
    Barton J, Rizzo M, Nawrot M, Simpson T. Optical blur and the perception of global coherent motion in random dot cinematograms. Vision Res 1996; 36: 3051–3059.PubMedCrossRefGoogle Scholar
  31. 31.
    Maddess T, Henry G. Performance of non-linear visual units in ocular hypertension and glaucoma. Clin Vision Sci 1992; 7: 371–383.Google Scholar
  32. 32.
    Cello K, Nelson-Quigg J, Johnson C. Frequency doubling technology perimetry for detection of glaucomatous visual field loss. Am J Ophthalmol 2000; 129: 314–322.PubMedCrossRefGoogle Scholar
  33. 33.
    Alward WL. Frequency doubling technology perimetry for the detection of glaucomatous visual field loss [editorial]. Am J Ophthalmol 2000; 129: 376–378.PubMedCrossRefGoogle Scholar
  34. 34.
    Patel S, Friedman D, Varadkar P, Robin A. Algorithm for interpreting the results of frequency doubling perimetry. Am J Ophthalmol 2000; 129: 323–327.PubMedCrossRefGoogle Scholar
  35. 35.
    Burnstein Y, Ellish N, Magbalon M, Higginbottom E. Comparison of frequency doubling perimetry with Humphrey visual field analysis in a glaucoma practice. Am J Ophthalmol 2000; 129: 328–333.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Jason J. S. Barton
    • 1
  • Michael Benatar
    • 2
  1. 1.Departments of Neurology and Ophthalmology, Beth Israel-Deaconess Medical Center, Harvard Medical School and Department of BioengineeringBoston UniversityBostonUSA
  2. 2.Department of Neurology, Beth Israel-Deaconess Medical CenterHarvard Medical SchoolBostonUSA

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