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Journal of the Optical Society of America A

Journal of the Optical Society of America A


  • Vol. 20, Iss. 7 — Jul. 1, 2003
  • pp: 1341–1355

Saccadic and perceptual performance in visual search tasks. I. Contrast detection and discrimination

Brent R. Beutter, Miguel P. Eckstein, and Leland S. Stone  »View Author Affiliations

JOSA A, Vol. 20, Issue 7, pp. 1341-1355 (2003)

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Humans use saccadic eye movements when they search for visual targets. We investigated the relationship between the visual processing used by saccades and perception during search by comparing saccadic and perceptual decisions under conditions in which each had access to equal visual information. We measured the accuracy of perceptual judgments and of the first search saccade over a wide range of target saliences [signal-to-noise ratios (SNRs)] in both a contrast-detection and a contrast-discrimination task. We found that saccadic and perceptual performances (1) were similar across SNRs, (2) showed similar task-dependent differences, and (3) were well described by a model based on signal detection theory that explicitly includes observer uncertainty [EcksteinM. P., J. Opt. Soc. Am. A 14, 2406 (1997)]. Our results demonstrate that the accuracy of the first saccade provides much information about the observer’s perceptual state at the time of the saccadic decision and provide evidence that saccades and perception use similar visual processing mechanisms for contrast detection and discrimination.

© 2003 Optical Society of America

OCIS Codes
(330.1880) Vision, color, and visual optics : Detection
(330.2210) Vision, color, and visual optics : Vision - eye movements
(330.4060) Vision, color, and visual optics : Vision modeling
(330.4300) Vision, color, and visual optics : Vision system - noninvasive assessment

Original Manuscript: July 29, 2002
Revised Manuscript: December 4, 2002
Manuscript Accepted: December 4, 2002
Published: July 1, 2003

Brent R. Beutter, Miguel P. Eckstein, and Leland S. Stone, "Saccadic and perceptual performance in visual search tasks. I. Contrast detection and discrimination," J. Opt. Soc. Am. A 20, 1341-1355 (2003)

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  1. M. P. Eckstein, B. R. Beutter, L. S. Stone, “Quantifying the performance limits of human saccadic targeting during visual search,” Perception 30, 1389–1401 (2001). [CrossRef]
  2. B. R. Beutter, M. P. Eckstein, L. S. Stone, “Parallel differences in contrast-discrimination and detection performance for saccades and perception in visual search,” Invest. Ophthalmol. Visual Sci. (Suppl.) 41, S424 (2000).
  3. J. M. Findlay, “Saccade target selection during visual search,” Vision Res. 37, 617–631 (1997). [CrossRef] [PubMed]
  4. D. M. Green, J. A. Swets, Signal Detection Theory and Psychophysics (Wiley, New York, 1966).
  5. A. E. Burgess, R. F. Wagner, R. J. Jennings, H. B. Barlow, “Efficiency of human visual signal discrimination,” Science 214, 93–94 (1981). [CrossRef] [PubMed]
  6. P. Viviani, R. G. Swensson, “Saccadic eye movements to peripherally discriminated visual targets,” J. Exp. Psychol. Hum. Percept. Perform. 16, 459–478 (1982).
  7. C. Motter, E. J. Belky, “The guidance of eye movements during active visual search,” Vision Res. 38, 1805–1815 (1998). [CrossRef] [PubMed]
  8. T. Hooge, C. J. Erkelens, “Adjustment of fixation duration in visual search,” Vision Res. 38, 1295–1302 (1998). [CrossRef] [PubMed]
  9. T. Hooge, C. J. Erkelens, “Peripheral vision and oculomotor control during visual search,” Vision Res. 39, 1567–1575 (1999). [CrossRef] [PubMed]
  10. J. M. Findlay, V. A. Brown, I. D. Gilchrist, “Saccade target selection in visual search: the influence of information from the previous fixation,” Vision Res. 41, 87–95 (2001). [CrossRef] [PubMed]
  11. L. G. Williams, “The effects of target specification on objects fixated during visual search,” Acta Psychol. 27, 355–360 (1966). [CrossRef]
  12. L. G. Williams, “Target conspicuity and visual search,” Hum. Factors 8, 80–92 (1967).
  13. G. L. Zelinsky, “Using eye saccades to assess the selectivity of search movements,” Vision Res. 36, 2177–2187 (1996). [CrossRef] [PubMed]
  14. G. E. Legge, J. M. Foley, “Contrast masking in human vision,” J. Opt. Soc. Am. 70, 1458–1471 (1980). [CrossRef] [PubMed]
  15. G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987). [CrossRef] [PubMed]
  16. D. G. Pelli, “Uncertainty explains many aspects of visual contrast detection and discrimination,” J. Opt. Soc. Am. A 2, 1508–1532 (1985). [CrossRef] [PubMed]
  17. J. Palmer, “Set-size effects in visual search: the effect of attention is independent of the stimulus for simple tasks,” Vision Res. 34, 1703–1721 (1994). [CrossRef] [PubMed]
  18. J. Palmer, P. Verghese, M. Pavel, “The psychophysics of visual search,” Vision Res. 40, 1227–1268 (2000). [CrossRef] [PubMed]
  19. M. P. Eckstein, A. J. Ahumada, A. B. Watson, “Visual signal detection in structured backgrounds. II. Effect of contrast gain control, background variations and white noise,” J. Opt. Soc. Am. A 14, 2406–2419 (1997). [CrossRef]
  20. The SNRs are slightly different for the discrimination and detection stimuli because we measured each SNR from the stimuli actually used in the experiment rather than relying on the ensemble parameters used to generate the stimuli.
  21. W. Becker, R. Jürgens, “An analysis of the saccadic system by means of double step stimuli,” Vision Res. 19, 967–983 (1979). [CrossRef] [PubMed]
  22. I. T. Hooge, “Control of eye movement in visual search,” Ph.D. thesis (Utrecht University, Utrecht, The Netherlands, 1996).
  23. P. He, E. Kowler, “The role of location probability in the programming of saccades: implications for center-of-gravity tendencies,” Vision Res. 29, 1165–1181 (1989). [CrossRef]
  24. L. S. Stone, B. R. Beutter, M. P. Eckstein, “Salience effects on perceptual and saccadic target localization during search,” Soc. Neurosci. Abstr. 25, 548 (1999).
  25. B. R. Beutter, L. S. Stone, “Human motion perception and smooth eye movements show similar directional biases for elongated apertures,” Vision Res. 38, 1273–1286 (1998). [CrossRef] [PubMed]
  26. R. M. McPeek, A. A. Skavenski, K. Nakayama, “Concurrent processing of saccades in visual search,” Vision Res. 40, 2499–2516 (2000). [CrossRef] [PubMed]
  27. R. M. McPeek, E. L. Keller, “Superior colliculus activity related to concurrent processing of saccade goals in a visual search task,” J. Neurophysiol. 87, 1805–1815 (2002). [PubMed]
  28. An alternative model has been proposed by Lu and Dosher29in which a nonlinear transducer replaces the intrinsic uncertainty.
  29. Z. L. Lu, B. A. Dosher, “Characterizing human perceptual inefficiencies with equivalent internal noise,” J. Opt. Soc. Am. A 16, 764–778 (1999). [CrossRef]
  30. D. G. Pelli, “Effects of visual noise,” Ph.D. thesis (Cambridge University, Cambridge, UK, 1981).
  31. This decision strategy is suboptimal, as discussed in Pelli,16but approximates the ideal decision at high SNRs,32although for the parameters that we use the difference in performance is small.
  32. L. W. Nolte, D. Jaarsma, “More on the detection of one of M orthogonal signals,” J. Acoust. Soc. Am. 41, 497–505 (1967). [CrossRef]
  33. H. B. Barlow, “The absolute efficiency of perceptual decisions,” Proc. R. Soc. London 290, 71–91 (1980).
  34. One should note that when applying the uncertainty equation19to a contrast-discrimination task, one should interpret Uas the effect of uncertainty on performance rather than the number of statistically independent signal-irrelevant responses monitored by the observer. In addition to the discriminability (d1)of the signal with respect to the distractors, an alternative model for the contrast-discrimination task would take into account the discriminability (d2)of the signal with respect to the Uadditional signal-irrelevant mechanisms. This more complete formulation is given by PC=100∫-∞+∞dx[g(x)G(x+d1′)N-1G(x+d2′)UN+Ug(x+d2′)G(x)G(x+d1′)N-1G(x+d2′)UN1],where g(x)is the Gaussian density function, G(x)is the cumulative probability, Uis the number of additional signal-irrelevant mechanisms per location monitored, and Nis the number of possible target locations. This model has two fitting parameters and would require a separate experiment to estimate d2′.Note that if d2′is large, as in the contrast-discrimination task (>2.5 approximately), the irrelevant mechanisms almost never produce the largest response, and increasing Uin the equation above has very little effect on PC.
  35. W. S. Geisler, L. Chou, “Separation of low-level and high-level factors in complex tasks: visual search,” Psychol. Rev. 102, 356–378 (1995). [CrossRef] [PubMed]
  36. D. J. Tolhurst, J. A. Movshon, F. A. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1983). [CrossRef] [PubMed]
  37. W. S. Geisler, D. G. Albrecht, “Bayesian analysis of identification performance in monkey visual cortex: nonlinear mechanisms and stimulus certainty,” Vision Res. 35, 2723–2730 (1995). [CrossRef] [PubMed]
  38. W. S. Geisler, D. G. Albrecht, “Visual cortex neurons in monkeys and cats: detection, discrimination and identification,” Visual Neurosci. 14, 897–919 (1997). [CrossRef]
  39. A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988). [CrossRef] [PubMed]
  40. M. P. Eckstein, B. R. Beutter, L. S. Stone, “Accumulation of information across saccades during visual search depends on how far the first saccade lands from the target,” Perception (Suppl.)29 (2000), http://www.perceptionweb.com/perception/ecvp00/0029.html .
  41. M. P. Eckstein, B. R. Beutter, L. S. Stone, “Task information increases from the first to the second saccade in visual search of a target among distractors,” Invest. Ophthalmol. Visual Sci. 41, 759 (2000).
  42. R. F. Hess, A. Hayes, “The coding of spatial position by the human visual system: effects of spatial scale and retinal eccentricity,” Vision Res. 34, 625–643 (1994). [CrossRef] [PubMed]
  43. R. M. McPeek, V. Maljkovic, K. Nakayama, “Saccades require focal attention and are facilitated by a short-term memory system,” Vision Res. 39, 1555–1566 (1999). [CrossRef] [PubMed]
  44. D. Gilchrist, C. A. Heywood, J. M. Findlay, “Saccade selection in visual search: evidence for spatial frequency specific between-item interactions,” Vision Res. 39, 1373–1383 (1999). [CrossRef] [PubMed]
  45. B. R. Beutter, L. S. Stone, M. P. Eckstein, “Correlated saccadic and perceptual decisions in a visual-search detection task reveal spatial-filter overlap,” presented at the Vision Sciences Society Meeting, May 4–8, 2001, Sarasota, Fla., J. Vision1, No. 1 (Abstract 263) (2001), http://www.journalofvision.org/1/3/263/ .
  46. B. R. Beutter, M. P. Eckstein, L. S. Stone, “Similar internal noise levels limit saccadic and perceptual performance in a visual-search task,” Program No. 418. 13 (2002). Abstract Viewer/Itinerary Planner. Society for Neuroscience, Washington, D.C., 2002. Online. http://sfn.scholarone.com/itin2002/index.html .
  47. R. F. Murray, B. R. Beutter, M. P. Eckstein, L. S. Stone, “Saccadic and perceptual performance in visual search tasks. II. Letter discrimination” J. Opt. Soc. Am. A 20, 1356–1370 (2003). [CrossRef]
  48. R. J. Krauzlis, A. Z. Zivotofsky, F. A. Miles, “Target selection for pursuit and saccadic eye movements in humans,” J. Cogn. Neurosci. 11, 641–649 (1999). [CrossRef] [PubMed]
  49. M. A. Basso, R. H. Wurtz, “Modulation of neuronal activity by target uncertainty,” Nature (London) 389, 66–69 (1997). [CrossRef]
  50. M. A. Basso, R. H. Wurtz, “Modulation of neuronal activity in superior colliculus by changes in target probability,” J. Neurosci. 18, 7519–7534 (1998). [PubMed]
  51. J. D. Schall, “Neural basis of saccade target selection,” Rev. Neurosci. 6, 63–85 (1995). [CrossRef] [PubMed]
  52. J. D. Schall, K. G. Thompson, “Neural selection and control of visually guided eye movements,” Annu. Rev. Neurosci. 22, 241–259 (1999). [CrossRef] [PubMed]
  53. J. P. Gottlieb, M. Kusunoki, M. E. Goldberg, “The representation of visual salience in monkey parietal cortex,” Nature (London) 391, 481–484 (1998). [CrossRef]
  54. C. L. Colby, M. E. Goldberg, “Space and attention in parietal cortex,” Annu. Rev. Neurosci. 23, 319–349 (1999). [CrossRef]
  55. P. W. Glimcher, “Making choices: the neurophysiology of visual-saccadic decision making,” Trends Neurosci. 24, 654–659 (2001). [CrossRef] [PubMed]
  56. L. Chelazzi, E. K. Miller, J. Duncan, R. Desimone, “A neural basis for visual search in inferior temporal cortex,” Nature (London) 363, 345–347 (1993). [CrossRef]
  57. M. P. Eckstein, J. S. Whiting, “Visual signal detection in structured backgrounds. I. Effect of number of possible signal locations and signal contrast,” J. Opt. Soc. Am. A 13, 1777–1787 (1996). [CrossRef]
  58. M. P. Eckstein, J. S. Whiting, J. P. Thomas, “Role of knowledge in human visual temporal integration in spatiotemporal noise,” J. Opt. Soc. Am. A 13, 1960–1968 (1996). [CrossRef]
  59. M. P. Eckstein, “The lower efficiency for conjunctions is due to noise and not serial visual attention,” Psychol. Sci. 9, 111–118 (1998). [CrossRef]
  60. W. W. Peterson, T. G. Birdsall, W. C. Fox, “The theory of signal detectability,” IRE Trans. Inf. Theory PGIT-4, 171–212 (1954). [CrossRef]
  61. This definition compares human- and ideal-observer performances at the same SNR. As suggested by a reviewer, it is also possible to define efficiency as a comparison between the human- and ideal-observer SNRs required to achieve the same performance level. In this alternative definition, efficiency is equal to (SNRideal/SNRhuman)2.The two definitions are equivalent if human d′is directly proportional to SNR (uncertainty is equal to zero), as is the case for our discrimination task. They are not the same for nonzero uncertainty (nonzero intercept), as is the case for our detection task.

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