A hierarchical Bayesian approach to adaptive vision testing: A case study with the contrast sensitivity function

Journal of Vision

Volumn 16, Issue 6, 2016, Pages

  Gu, Hairong ^a   Kim, Woojae ^a,b   Hou, Fang ^a   Lesmes, Luis Andres ^c   Pitt, Mark A ^a   Lu, Zhong Lin ^a   Myung, Jay I ^a  

^a OHIO STATE UNIVERSITY   (United States)

^b HOWARD UNIVERSITY   (United States)

^c Adaptive Sensory Technology   (United States)

Author keywords

Bayesian adaptive estimation; Contrast sensitivity; Hierarchical Bayesian modeling; Informative priors; Visual psychophysics

Indexed keywords

ADULT; BAYES THEOREM; CONTRAST SENSITIVITY; FEMALE; HUMAN; MALE; PHYSIOLOGY; PROCEDURES; THEORETICAL MODEL; VALIDATION STUDY; VISION TEST; YOUNG ADULT;

ADULT; BAYES THEOREM; CONTRAST SENSITIVITY; FEMALE; HUMANS; MALE; MODELS, THEORETICAL; VISION TESTS; YOUNG ADULT;

EID: 84992163170     PISSN: None     EISSN: 15347362     Source Type: Journal    
DOI: 10.1167/16.6.15     Document Type: Article

References (59)

1. Alcalá-Quintana, R., & García-Pérez, M. A. (2004). The role of parametric assumptions in adaptive Bayesian estimation. Psychological Methods, 9(2), 250-271
2. Alexander, K. R., Xie, W., & Derlacki, D. J. (1994). Spatial frequency characteristics of letter identification. Journal of the Optical Society of America A, 11, 2375-2382
3. Applegate, R. A., Howland, H. C., Sharp, R. P., Cottingham, A. J., & Yee, R. W. (1997). Corneal aberrations and visual performance after radial keratotomy. Journal of Refractive Surgery, 14(4), 397-407
4. Baek, J., Lesmes, L., & Lu, Z. L. (2014), Bayesian adaptive estimation of the sensory memory decay function: The quick partial report method. Journal of Vision, 14(10): 157, doi:10.1167/14.10.157. [Abstract]
5. Bernardo, J. M., & Smith, A. F. (1994). Bayesian theory. Chichester, UK: Wiley
6. Bush, C. A., & MacEachern, S. N. (1996). A semi-parametric Bayesian model for randomized block designs. Biometrika, 83, 275-285
7. Casella, G. (1985). An introduction to empirical Bayes data analysis. The American Statistician, 39(2), 83-87
8. Cavagnaro, D. R., Myung, J. I., Pitt, M. A., & Kujala, J. V. (2010). Adaptive design optimization: A mutual information-based approach to model discrimination in cognitive science. Neural Computation, 22(4), 887-905
9. Cover, T. M., & Thomas, J. A. (1991). Elements of information theory. New York: Wiley
10. Cristianini, N., & Shawe-Taylor, J. (2000). An introduction to support vector machines. Cambridge, UK: Cambridge University Press
11. DiMattina, C. (2015). Fast adaptive estimation of multi-dimensional psychometric functions. Journal of Vision, 15(9):5, 1-20, doi:10.1167/15.9.5
12. DiMattina, C., & Zhang, K. (2008). How optimal stimuli for sensory neurons are constrained by network architecture. Neural Computation, 20(3), 668-708
13. DiMattina, C., & Zhang, K. (2011). Active data collection for efficient estimation and comparison of nonlinear neural models. Neural Computation, 23(9), 2242-2288
14. Dixon, W. J., & Mood, A. M. (1948). A method for obtaining and analyzing sensitivity data. Journal of the American Statistical Association, 43(241), 109-126
15. Dorr, M., Lesmes, L. A., Lu, Z. L., & Bex, P. J. (2013). Rapid and reliable assessment of the contrast sensitivity function on an iPad. Investigative Ophthalmology & Visual Science, 54(12), 7266-7273
16. Garcia-Perez, M. A. (2001). Yes-no staircases with fixed step size: Psychometric properties and optimal setup. Optometry and Vision Science, 78(1), 56-64
17. Ginsburg, A. P. (1981). Spatial filtering and vision: Implications for normal and abnormal vision. In L. Proenz, J. Enoch, & A. Jampolsky (Eds.), Clinical applications of visual psychophysics (pp. 70-106). Cambridge, UK: Cambridge University Press
18. Ginsburg, A. P. (2003). Contrast sensitivity and functional vision. International Ophthalmology Clinics, 43(2), 5-15
19. Hess, R. F. (1978). Contrast sensitivity assessment of functional amblyopia in humans. Transactions of the Ophthalmological Societies of the United Kingdom, 99(3), 391-397
20. Hess, R. F. (1981). Application of contrast-sensitivity techniques to the study of functional amblyopia. In L. Proenz, J. Enoch, & A. Jampolsky (Eds.), Clinical applications of visual psychophysics (pp. 11-41). Cambridge, UK: Cambridge University Press
21. Hou, F., Huang, C. B., Lesmes, L., Feng, L. X., Tao, L., Zhou, Y. F., & Lu, Z.-L. (2010). qCSF in clinical application: Efficient characterization and classification of contrast sensitivity functions in amblyopia. Investigative Ophthalmology & Visual Science, 51(10), 5365-5377
22. Hou, F., Lesmes, L., Bex, P., Dorr, M., & Lu, Z.-L. (2015). Using 10AFC to further improve the efficiency of quick CSF method. Journal of Vision, 15(9):2, 1-18, doi:10.1167/15.9.2
23. Hou, F., Lesmes, L., Kim, W., Gu, H., Pitt, M., Myung, J., & Lu, Z.-L. (2016). The usefulness of the quick CSF method: A large sample study. Manuscript submitted for publication
24. Hou, F., Lu, Z.-L., & Huang, C. B. (2014). The external noise normalized gain profile of spatial vision. Journal of Vision, 14(13):9, 1-14, doi:10. 1167/14.13.9
25. Huang, C., Tao, L., Zhou, Y., & Lu, Z. L. (2007). Treated amblyopes remain deficient in spatial vision: A contrast sensitivity and external noise study. Vision Research, 47(1), 22-34
26. Jindra, L. F., & Zemon, V. (1989). Contrast sensitivity testing: A more complete assessment of vision. Journal of Cataract & Refractive Surgery, 15(2), 141-148
27. Kaernbach, C. (1991). Simple adaptive testing with the weighted up-down method. Perception & Psychophysics, 49, 227-229
28. Kesten, H. (1958). Accelerated stochastic approximation. The Annals of Mathematical Statistics, 29, 41-59
29. Kim, W., Pitt, M. A., Lu, Z.-L., Steyvers, M., & Myung, J. I. (2014). A hierarchical adaptive approach to optimal experimental design. Neural Computation, 26, 2463-2492
30. King-Smith, P. E., Grigsby, S. S., Vingrys, A. J., Benes, S. C., & Supowit, A. (1994). Efficient and unbiased modifications of the QUEST threshold method: Theory, simulations, experimental evaluation and practical implementation. Vision Research, 34(7), 885-912
31. Kleiner, M., Brainard, D., Pelli, D., Ingling, A., Murray, R., & Broussard, C. (2007). What's new in Psychtoolbox-3. Perception, 36(14), 1-16
32. Kontsevich, L. L., & Tyler, C. W. (1999). Bayesian adaptive estimation of psychometric slope and threshold. Vision Research, 39(16), 2729-2737
33. Kujala, J. V., & Lukka, T. J. (2006). Bayesian adaptive estimation: The next dimension. Journal of Mathematical Psychology, 50(4), 369-389
34. Lee, M. D. (2006). A hierarchical Bayesian model of human decision-making on an optimal stopping problem. Cognitive Science, 30(3), 1-26
35. Lehmann, E. L., & Casella, G. (1998). Theory of point estimation (2nd ed.). New York: Springer
36. Lesmes, L. A., Jeon, S. T., Lu, Z. L., & Dosher, B. A. (2006). Bayesian adaptive estimation of threshold versus contrast external noise functions: The quick TvC method. Vision Research, 46(19), 3160-3176
37. Lesmes, L. A., Lu, Z. L., Baek, J., & Albright, T. D. (2010). Bayesian adaptive estimation of the contrast sensitivity function: The quick CSF method. Journal of Vision, 10(3):17, 1-21, doi:10.1167/10.3. 17
38. Lesmes, L. A., Lu, Z.-L., Baek, J., Tran, N., Dosher, B. A., & Albright, T. D. (2015). Developing Bayesian adaptive methods for estimating sensitivity thresholds (d0) in Yes-No and forced-choice tasks. Frontiers in Psychology, 6, 1070, http://doi.org/10. 3389/fpsyg.2015.01070
39. Levitt, H. (1971). Transformed up-down methods in psychoacoustics. The Journal of the Acoustical Society of America, 49, 467-477
40. Lu, Z.-L., & Dosher, B. A. (2013). Visual psychophysics: From laboratory to theory. Cambridge, MA, MIT Press
41. Lu, Z.-L., Neuse, J., Madigan, S., & Dosher, B. A. (2005). Fast decay of iconic memory in observers with mild cognitive impairments. Proceedings of the National Academy of Sciences, USA, 102(5), 1797-1802
42. Marmor, M. F. (1981). Contrast sensitivity and retinal disease. Annals of Ophthalmology, 13(9), 1069-1071
43. McAnany, J. J., & Alexander, K. R. (2006). Contrast sensitivity for letter optotypes vs. gratings under conditions biased toward parvocellular and magnocellular pathways. Vision Research, 46(10), 1574-1584
44. Oshika, T., Okamoto, C., Samejima, T., Tokunaga, T., & Miyata, K. (2006). Contrast sensitivity function and ocular higher-order wavefront aberrations in normal human eyes. Ophthalmology, 113(10), 1807-1812
45. Pentland, A. (1980). Maximum likelihood estimation: The best PEST. Attention, Perception, & Psychophysics, 28(4), 377-379
46. Rodriguez, A., Dunson, D. B., & Gelfand, A. E. (2008). The nested Dirichlet process. Journal of the American Statistical Association, 103, 1131-1154
47. Rouder, J. N., & Lu, J. (2005). An introduction to Bayesian hierarchical models with an application in the theory of signal detection. Psychonomic Bulletin & Review, 12(4), 573-604
48. Scott, D. W. (1992). Multivariate density estimation: Theory, practice, and visualization. New York: Wiley
49. Sperling, G. (1960). The information available in brief visual presentation. Psychological Monographs, 74, 1-29
50. Taylor, M., & Creelman, C. D. (1967). PEST: Efficient estimates on probability functions. The Journal of the Acoustical Society of America, 41, 782-787
51. Teh, Y. W., Jordan, M. I., Beal, M. J., & Blei, D. M. (2006). Hierarchical Dirichlet processes. Journal of the American Statistical Association, 101, 1566-1581
52. Tyler, C. W. (1997). Colour bit-stealing to enhance the luminance resolution of digital displays on a single pixel basis. Spatial Vision, 10(4), 369-377
53. Wackerly, D., Mendenhall, W., & Scheaffer, R. (2007). Mathematical statistics with applications. Belmont, CA: Cengage Learning
54. Wagenmakers, E. J., Lee, M., Lodewyckx, T., & Iverson, G. J. (2008). Bayesian versus frequentist inference. In H. Hoijtink, I. Klugkist, P. A. Boelen (Eds.), Bayesian evaluation of informative hypotheses. (pp. 181-207). New York: Springer
55. Watson, A. B., & Ahumada, A. J. (2005). A standard model for foveal detection of spatial contrast. Journal of Vision, 5(9):6, 717-740, doi:10.1167/5.9. 6
56. Watson, A. B., & Pelli, D. G. (1983). QUEST: A Bayesian adaptive psychometric method. Perception & Psychophysics, 33(2), 113-120
57. Wolkstein, M., Atkin, A., & Bodis-Wollner, I. (1980). Contrast sensitivity in retinal disease. Ophthalmology, 87(11), 1140-1149
58. Wyszecki, G., & Stiles, W. S. (1982). Color science: Concepts and methods, quantitative data and formulae (2nd ed.). New York: Wiley-Interscience
59. Zhou, Y., Huang, C., Xu, P., Tao, L., Qiu, Z., Li, X., & Lu, Z. L. (2006). Perceptual learning improves contrast sensitivity and visual acuity in adults with anisometropic amblyopia. Vision Research, 46(5), 739-750