Advertisement

The dynamics of practice effects in an optotype acuity task

  • Sven P. Heinrich
  • Katja Krüger
  • Michael Bach
Basic Science

Abstract

Background

Practice-related improvements of performance are common in many areas of visual processing. There is preliminary evidence that this is also the case for standard optotype acuity tasks. The present study was designed to confirm and quantify the effect of practice under different feedback conditions and to track the dynamics of practice over several sessions.

Methods

Subjects completed a total of 56 runs of a computer-based acuity test with randomly oriented Landolt C optotypes, split evenly over four sessions at intervals of 1 week. Half of the subjects received feedback indicating the correct response.

Results

Over the course of the sessions, the test outcomes increased significantly by 0.11 logMAR with feedback and by 0.055 logMAR without feedback. In addition to an increase in acuity over the first few runs of the first session, a major part of the practice effect with feedback occurred not during a session, but in between the first and the second session. Without feedback, the increase in acuity occurred mainly within the first half of the first session.

Conclusions

Feedback has a drastic effect on the magnitude and dynamics of the practice effect, which is not explained by simple familiarization with the test procedure. If feedback is not given, practice effects can be neglected in most clinical routine applications even when many test repetitions are performed. However, they may become relevant on a group level in clinical studies without an appropriate control.

Keywords

Visual acuity Practice Perceptual learning Repetitive testing Reproducibility Feedback 

Notes

Acknowledgements

We are grateful to our subjects for their participation. The study was supported by the Deutsche Forschungsgemeinschaft (BA 877/18).

Supplementary material

417_2011_1675_MOESM1_ESM.doc (22 kb)
ESM 1 (DOC 24 kb)

References

  1. 1.
    Fine I, Jacobs RA (2002) Comparing perceptual learning tasks: a review. J Vis 2:190–203PubMedGoogle Scholar
  2. 2.
    Fahle M, Edelman S, Poggio T (1995) Fast perceptual learning in hyperacuity. Vis Res 35:3003–3013PubMedCrossRefGoogle Scholar
  3. 3.
    Karni A, Sagi D (1993) The time course of learning a visual skill. Nature 365:250–252PubMedCrossRefGoogle Scholar
  4. 4.
    Censor N, Bonneh Y, Arieli A, Sagi D (2009) Early-vision brain responses which predict human visual segmentation and learning. J Vis 9:12.1–12.9CrossRefGoogle Scholar
  5. 5.
    Gold J, Bennett PJ, Sekuler AB (1999) Signal but not noise changes with perceptual learning. Nature 402:176–178PubMedCrossRefGoogle Scholar
  6. 6.
    Westheimer G (2001) Is peripheral visual acuity susceptible to perceptual learning in the adult? Vis Res 41:47–52PubMedCrossRefGoogle Scholar
  7. 7.
    Cavazos H, Schulz E, Rassow B, Wesemann W (1990) Vergleich des Kindersehsch¨arfetests nach Lithander (Kolt-Test) mit dem standardisierten Landoltring. Klin Monatsbl Augenheilkd 197:324–328PubMedCrossRefGoogle Scholar
  8. 8.
    Rassow B, Cavazos H, Wesemann W (1990) Normgerechte Sehschärfebestimmung mit Buchstaben. Augenarztl Fortbild 13:105–114Google Scholar
  9. 9.
    Johnson CA, Leibowitz HW (1979) Practice effects for visual resolution in the periphery. Percept Psychophys 25:439–442PubMedCrossRefGoogle Scholar
  10. 10.
    Bennett RG, Westheimer G (1991) The effect of training on visual alignment discrimination and grating resolution. Percept Psychophys 49:541–546PubMedCrossRefGoogle Scholar
  11. 11.
    Moke PS, Turpin AH, Beck RW, Holmes JM, Repka MX, Birch EE, Hertle RW, Kraker RT, Miller JM, Johnson CA (2001) Computerized method of visual acuity testing: adaptation of the amblyopia treatment study visual acuity testing protocol. Am J Ophthalmol 132:903–909PubMedCrossRefGoogle Scholar
  12. 12.
    Beck RW, Moke PS, Turpin AH, Ferris FL 3rd, SanGiovanni JP, Johnson CA, Birch EE, Chandler DL, Cox TA, Blair RC, Kraker RT (2003) A computerized method of visual acuity testing: adaptation of the early treatment of diabetic retinopathy study testing protocol. Am J Ophthalmol 135:194–205PubMedCrossRefGoogle Scholar
  13. 13.
    Bourne RRA, Rosser DA, Sukudom P, Dineen B, Laidlaw DAH, Johnson GJ, Murdoch IE (2003) Evaluating a new logMAR chart designed to improve visual acuity assessment in population-based surveys. Eye 17:754–758PubMedCrossRefGoogle Scholar
  14. 14.
    Laidlaw DAH, Tailor V, Shah N, Atamian S, Harcourt C (2008) Validation of a computerised logMAR visual acuity measurement system (COMPlog): comparison with ETDRS and the electronic ETDRS testing algorithm in adults and amblyopic children. Br J Ophthalmol 92:241–244PubMedCrossRefGoogle Scholar
  15. 15.
    Heinrich SP, Krüger K, Bach M (2010) The effect of optotype presentation duration on acuity estimates revisited. Graefes Arch Clin Exp Ophthalmol 248:389–394PubMedCrossRefGoogle Scholar
  16. 16.
    Lange C, Feltgen N, Junker B, Schulze-Bonsel K, Bach M (2009) Resolving the clinical acuity categories “hand motion” and “counting fingers” using the Freiburg Visual Acuity Test (FrACT). Graefes Arch Clin Exp Ophthalmol 247:137–142PubMedCrossRefGoogle Scholar
  17. 17.
    Reeves BC, Wood JM, Hill AR (1991) Vistech VCTS 6500 charts–within- and between-session reliability. Optom Vis Sci 68:728–737PubMedCrossRefGoogle Scholar
  18. 18.
    Pointer JS (2008) Recognition versus resolution: a comparison of visual acuity results using two-alternative test chart optotype. J Optom 1:65–70CrossRefGoogle Scholar
  19. 19.
    Arditi A, Cagenello R (1993) On the statistical reliability of letter-chart visual acuity measurements. Invest Ophthalmol Vis Sci 34:120–129PubMedGoogle Scholar
  20. 20.
    Simpson TL, Regan D (1995) Test-retest variability and correlations between tests of texture processing, motion processing, visual acuity, and contrast sensitivity. Optom Vis Sci 72:11–16PubMedCrossRefGoogle Scholar
  21. 21.
    Ruamviboonsuk P, Tiensuwan M, Kunawut C, Masayaanon P (2003) Repeatability of an automated Landolt C test, compared with the early treatment of diabetic retinopathy study (ETDRS) chart testing. Am J Ophthalmol 136:662–669PubMedCrossRefGoogle Scholar
  22. 22.
    Stifter E, König F, Lang T, Bauer P, Richter-Müksch S, Velikay-Parel M, Radner W (2004) Reliability of a standardized reading chart system: variance component analysis, test-retest and inter-chart reliability. Graefes Arch Clin Exp Ophthalmol 242:31–39PubMedCrossRefGoogle Scholar
  23. 23.
    Lim L, Frost NA, Powell RJ, Hewson P (2010) Comparison of the ETDRS logMAR, ‘compact reduced log- Mar’ and Snellen charts in routine clinical practice. Eye 24:673–677PubMedCrossRefGoogle Scholar
  24. 24.
    Polat U, Ma-Naim T, Belkin M, Sagi D (2004) Improving vision in adult amblyopia by perceptual learning. Proc Natl Acad Sci USA 101:6692–6697PubMedCrossRefGoogle Scholar
  25. 25.
    Fronius M, Cirina L, Cordey A, Ohrloff C (2005) Visual improvement during psychophysical training in an adult amblyopic eye following visual loss in the contralateral eye. Graefes Arch Clin Exp Ophthalmol 243:278–280PubMedCrossRefGoogle Scholar
  26. 26.
    Li RW, Young KG, Hoenig P, Levi DM (2005) Perceptual learning improves visual performance in juvenile amblyopia. Invest Ophthalmol Vis Sci 46:3161–3168PubMedCrossRefGoogle Scholar
  27. 27.
    Zhou Y, Huang C, Xu P, Tao L, Qiu Z, Li X, Lu ZL (2006) Perceptual learning improves contrast sensitivity and visual acuity in adults with anisometropic amblyopia. Vis Res 46:739–750PubMedCrossRefGoogle Scholar
  28. 28.
    Durrie D, McMinn PS (2007) Computer-based primary visual cortex training for treatment of low myopia and early presbyopia. Trans Am Ophthalmol Soc 105:132–138PubMedGoogle Scholar
  29. 29.
    Tan DTH, Fong A (2008) Efficacy of neural vision therapy to enhance contrast sensitivity function and visual acuity in low myopia. J Cataract Refract Surg 34:570–577PubMedCrossRefGoogle Scholar
  30. 30.
    Polat U (2009) Making perceptual learning practical to improve visual functions. Vis Res 49:2566–2573PubMedCrossRefGoogle Scholar
  31. 31.
    International Organization for Standardization (2009) ISO 8596, Ophthalmic optics—Visual acuity testing—Standard optotype and its presentation. International Organization for Standardization, GenevaGoogle Scholar
  32. 32.
    International Council of Ophthalmology (1988) Visual acuity measurement standard. Ital J Ophthalmol II/I:1–15Google Scholar
  33. 33.
    Deutsches Institut fur Normung (2009) DIN 58220–3, Sehschärfeprüfung — Teil 3: Prüfung fur Gutachten. Beuth Verlag, BerlinGoogle Scholar
  34. 34.
    Bach M (1996) The “Freiburg Visual Acuity Test”—Automatic measurement of the visual acuity. Optom Vis Sci 73:49–53PubMedCrossRefGoogle Scholar
  35. 35.
    Howell DC (1997) Statistical methods for psychology, 4th edn. Brooks/Cole, Pacific GroveGoogle Scholar
  36. 36.
    Coppens JE, van den Berg TJTP (2004) A new source of variance in visual acuity. Vis Res 44:951–958PubMedCrossRefGoogle Scholar
  37. 37.
    Macmillan NA, Creelman CD (2005) Detection theory: a user’s guide, 2nd edn. Erlbaum, MahwahGoogle Scholar
  38. 38.
    Vertes RP, Siegel JM (2005) Time for the sleep community to take a critical look at the purported role of sleep in memory processing. Sleep 28:1228–1229PubMedGoogle Scholar
  39. 39.
    Stickgold R (2005) Sleep-dependent memory consolidation. Nature 437:1272–1278PubMedCrossRefGoogle Scholar
  40. 40.
    Wagner U, Gais S, Haider H, Verleger R, Born J (2004) Sleep inspires insight. Nature 427:352–355PubMedCrossRefGoogle Scholar
  41. 41.
    Mednick SC, Nakayama K, Cantero JL, Atienza M, Levin AA, Pathak N, Stickgold R (2002) The restorative effect of naps on perceptual deterioration. Nat Neurosci 5:677–681PubMedGoogle Scholar
  42. 42.
    Aberg KC, Tartaglia EM, Herzog MH (2009) Perceptual learning with chevrons requires a minimal number of trials, transfers to untrained directions, but does not require sleep. Vis Res 49:2087–2094PubMedCrossRefGoogle Scholar
  43. 43.
    Mednick SC, Arman AC, Boynton GM (2005) The time course and specificity of perceptual deterioration. Proc Natl Acad Sci USA 102:3881–3885PubMedCrossRefGoogle Scholar
  44. 44.
    Hussain Z, Sekuler AB, Bennett PJ (2008) Robust perceptual learning of faces in the absence of sleep. Vis Res 48:2785–2792PubMedCrossRefGoogle Scholar
  45. 45.
    Hussain Z, Sekuler AB, Bennett PJ (2009) How much practice is needed to produce perceptual learning? Vis Res 49:2624–2634PubMedCrossRefGoogle Scholar
  46. 46.
    Randle RJ (1970) Volitional control of visual accommodation. In: Conference Proceedings, vol. 82, Advisory Group for Aerospace Research and Development, pp 15–17Google Scholar
  47. 47.
    Cornsweet TN, Crane HD (1973) Training the visual accommodation system. Vis Res 13:713–715PubMedCrossRefGoogle Scholar
  48. 48.
    Montés-Micó R (2007) Role of the tear film in the optical quality of the human eye. J Cataract Refract Surg 33:1631–1635PubMedCrossRefGoogle Scholar
  49. 49.
    Beatty J (1982) Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychol Bull 91:276–292PubMedCrossRefGoogle Scholar
  50. 50.
    Cagenello R, Arditi A, Halpern DL (1993) Binocular enhancement of visual acuity. J Opt Soc Am A 10:1841–1848CrossRefGoogle Scholar
  51. 51.
    Blake R (2001) A primer on binocular rivalry, including current controversies. Brain Mind 2:5–38CrossRefGoogle Scholar
  52. 52.
    Pointer JS (2008) Habitual vs optimal distance visual acuity. Ophthalmic Physiol Opt 28:457–466PubMedCrossRefGoogle Scholar
  53. 53.
    Berntsen DA, Merchea MM, Richdale K, Mack CJ, Barr JT (2009) Higher-order aberrations when wearing sphere and toric soft contact lenses. Optom Vis Sci 86:115–122PubMedCrossRefGoogle Scholar
  54. 54.
    Li S, Xiong Y, Li J, Wang N, Dai Y, Xue L, Zhao H, JiangW ZY, He JC (2009) Effects of monochromatic aberration on visual acuity using adaptive optics. Optom Vis Sci 86:868–874PubMedCrossRefGoogle Scholar
  55. 55.
    Pesudovs K (2005) Involvement of neural adaptation in the recovery of vision after laser refractive surgery. J Refract Surg 21:144–147PubMedGoogle Scholar
  56. 56.
    Liu L, Klein SA, Xue F, Zhang JY, Yu C (2009) Using geometric moments to explain human letter recognition near the acuity limit. J Vis 9:26.1–26.18CrossRefGoogle Scholar
  57. 57.
    Lithander J (1996) Two techniques to evaluate visual acuity from the age of 18 months. Strabismus 4:15–23PubMedCrossRefGoogle Scholar
  58. 58.
    Chung STL, Levi DM, Li RW (2006) Learning to identify contrast-defined letters in peripheral vision. Vis Res 46:1038–1047PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Sven P. Heinrich
    • 1
  • Katja Krüger
    • 1
  • Michael Bach
    • 1
  1. 1.Sektion Funktionelle SehforschungUniv.-AugenklinikFreiburgGermany

Personalised recommendations