Abstract

Contrast sensitivity under photopic conditions declines with age; however, the cause of this decline remains unknown. To address this issue, we measured detection thresholds for sine wave gratings in noise, under various conditions of spatial-frequency uncertainty, and estimated observers’ internal noise and calculation efficiency. Statistical analyses revealed that efficiencies were lower for old (median age at 68 years) than for young (median age at 22 years) observers; no significant differences in internal noise were found. A control experiment ruled out the possibility that reduced retinal illuminance causes the decline in efficiency with age. Our results demonstrate that age-related neural changes play a major role in the decline in contrast sensitivity with age. Possible contributing mechanisms are considered.

© 1999 Optical Society of America

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    [CrossRef]
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  20. Luminance quantization altered the contrast of the sine wave gratings and noise used in these experiments. The lowest detection thresholds were obtained with the 1 c/deg target with no frequency uncertainty, so the effects of quantization should have been greatest in that condition. We therefore examined the possible effects in that condition. First, in software we re-created the stimulus luminance profiles presented on the screen when pattern contrast was set to detection threshold, and we counted the number of luminance steps in the pattern. At detection threshold (e.g., contrasts of 0.014 and 0.015 for young and old observers, respectively), the gratings had four luminance steps and 95% of the stimulus power was concentrated at the nominal target frequency. The number of luminance steps did not drop below four until stimulus contrast was reduced below 0.01. Thus the quantization effects were small, even for stimuli presented at detection threshold. Next, we examined the raw data to find observers who might have had thresholds below 0.01 by looking for observers who consistently responded correctly for contrasts as low as 0.01. Four old observers and four young observers met this criterion. We then replaced thresholds for those observers with a value of 0.007, which was approximately one half of the average threshold and was the smallest contrast that could be produced with our equipment, and repeated all of our statistical analyses. The results of the new analyses were identical to those reported in Section 3. Thus luminance quantization does not appear to have had a significant effect on our results.
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  22. Some old observers had trouble manipulating the keyboard while viewing the patterns. For these observers the experimenter pressed the key that corresponded to the pattern indicated verbally by the observer. To eliminate any effects of experimenter bias, the experimenter’s view of the display was blocked during each trial.
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  28. For the case in which phase is unknown, the noise and signal-plus-noise distributions for the ideal detector are neither normal nor constant variance. Strictly speaking, therefore, Eq. (5) applies to the detection index dS, not d′. When the distributions are normal and constant variance, dS=d′.
  29. Previous studies have shown that detection versus noise curves obtained from young observers are linear. Pardhan et al.19 obtained similar results with old observers. However, those previous studies used conditions in which position uncertainty was minimized, whereas position uncertainty was maximized in the current experiment. We therefore conducted a preliminary experiment to examine whether contrast versus noise functions were linear in our stimulus conditions. The experiment was identical to the no-uncertainty condition in the main experiment except that four levels of external noise (contrast standard deviations of 0.04, 0.09, 0.16, and 0.25) were used. Four young observers (23–33 years; median age at 24 years) and one old observer (63 years) were tested. Multiple thresholds were obtained at each level of external noise, and the best-fitting line was computed for the data from each observer. In all cases, thresholds were well fit by a straight line (R2>0.87) and the quadratic component of the regression was not statistically significant. Efficiency and equivalent noise were calculated by first fitting the equation E=mN+b to each observer’s data, where E is threshold energy, N is the external noise’s spectral density, m is the line’s slope, and b is the line’s intercept. According to Eq. (6), J=(1/m) * (d′+1/2)2 and Ni=b * J/(d′+1/2)2.
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    [CrossRef] [PubMed]
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  36. The simulation consisted of 2AFC trials in which a detector was presented with a noise stimulus and a signal-plus-noise stimulus. The noise stimulus was an array of random numbers drawn from a zero-mean Gaussian distribution. The signal-plus-noise stimulus was another array of Gaussian random variables to which was added a sine wave target in random phase. The detector decided which stimulus contained the target by computing the power in a frequency band centered on the target frequency and selecting the stimulus with the greatest power. The Gaussian noise consisted of two components, one fixed and the other variable. The fixed component represented the detector’s internal noise and was held constant. The variable component represented the external noise and was varied across simulations to compute the detector’s calculation efficiency. The detector’s threshold was computed by measuring percentage correct for 400 simulated trials at each of 12 simulated target amplitudes, fitting a Weibull function to the data, and calculating the 81% correct point. Thresholds were measured for five levels of external noise, and Eq. (6) was used to estimate the detector’s calculation efficiency and internal noise. As expected, the calculation efficiency of the simulated ideal detector (filter bandwidth = 1 c/image) was 1. Next, calculation efficiency was computed for a detector with a filter bandwidth (W) that ranged from 1 to 30 c/image: Across this range, efficiency equalled 1/W0.4. Finally, spatial-frequency uncertainty was simulated by forcing the detector to compute power at three bands of spatial frequencies centered at 10, 30, and 90 c/image. The bandwidth of each channel was varied with the restriction that the three frequency bands never overlapped. The power from each band was combined in two ways. In the maximum-response simulations, the detector chose the stimulus that yielded the largest number. In the summation-of-response simulations, the three numbers were added and the detector chose the stimulus that yielded the largest sum.
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  40. It is necessary to convert from units of space average luminance to retinal illuminance to compare our results with previous measurements. We did not measure pupil diameters of the observers in our experiments, and so we estimated illuminance in the following way. Subsequent to the main experiments, pupil diameters were measured on five young observers. Average pupil diameter was 5.5 mm for the high-luminance display. We were unable to measure pupil size reliably in the low-luminance condition, but previous studies41,42 have found that pupil diameter increases by 40–50% over this luminance range. On the basis of these measurements it is reasonable to assume that decreasing luminance from 80 to 1.6 cd m-2 reduced retinal illuminance from approximately 1900 to 80 td. Kelly43 reported that contrast sensitivity at 8 c/deg drops by approximately 0.4 log unit, whereas sensitivity for 1 and 3 c/deg remains nearly constant, over this range of retinal illuminances. These values do not differ appreciably from those found in the current study at 9, 3, and 1 c/deg.
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    [CrossRef]
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  50. B. E. Schefrin, J. S. Werner, M. Plach, N. Utlaut, “Sites of age-related sensitivity loss in a short-wave cone pathway,” J. Opt. Soc. Am. A 9, 355–363 (1992).
    [CrossRef] [PubMed]
  51. V. Porciatti, D. C. Burr, M. C. Morrone, A. Fircentini, “The effects of ageing on the pattern electroretinogram and visual evoked potential in humans,” Vision Res. 32, 1199–1209 (1992).
    [CrossRef] [PubMed]
  52. W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
    [CrossRef]
  53. D. J. Tolhurst, J. A. Movshon, I. D. Thompson, “The dependence of response amplitude and variance of cat visualcortical neurones on stimulus contrast,” Exp. Brain Res. 41, 414–419 (1981).
  54. D. J. Tolhurst, J. A. Movshon, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1983).
    [CrossRef] [PubMed]
  55. D. M. Green, “Consistency of auditory detection judgments,” Psychol. Rev. 71, 392–407 (1964).
    [CrossRef] [PubMed]
  56. M. F. Spiegel, D. M. Green, “Two procedures for estimating internal noise,” J. Acoust. Soc. Am. 70, 69–73 (1981).
    [CrossRef] [PubMed]
  57. B. E. Schefrin, M. L. Bieber, J. S. Werner, “The area of complete spatial summation enlarges with age,” Invest. Ophthalmol. Visual Sci. Suppl. 38, S58 (1997).
  58. C. Owsley, R. Sekuler, “Spatial summation, contrast threshold, and aging,” Invest. Ophthalmol. Visual Sci. 22, 130–133 (1982).
  59. L. Ozin, P. J. Bennett, “The effects of aging on spatial frequency tuning,” Invest. Ophthalmol. Visual Sci. Suppl. 37, S1069 (1996).
  60. C. T. Scialfa, D. W. Kline, B. J. Lyman, “Age differences in target identification as a function of retinal loca-tion and noise level: examination of the useful field of view,” Psychol. Aging 2, 14–19 (1987).
    [CrossRef] [PubMed]
  61. R. Sekuler, K. Ball, “Visual localization: age and practice,” J. Opt. Soc. Am. A 3, 864–867 (1986).
    [CrossRef] [PubMed]
  62. P. Rabbit, “An age-decrement in the ability to ignore irrelevant information,” J. Gerontol. 20, 233–237 (1965).
    [CrossRef]
  63. D. J. Madden, “Aging and distraction by highly familiar stimuli during visual search,” Dev. Psychol. 19, 499–507 (1983).
    [CrossRef]
  64. P. E. Comalli, S. Wapner, H. Werner, “Interference effects of a Stroop color-word test in children, adulthood, and aging,” J. Gen. Psychol. 100, 47–53 (1962).
    [CrossRef]
  65. S. P. Tipper, “Less attentional selectivity as a result of declining inhibition in older observers,” Bull. Psychonomic Soc. 29, 45–47 (1991).
    [CrossRef]
  66. U. Lindenberger, P. B. Baltes, “Sensory functioning and intelligence in old age: a strong connection,” Psychol. Aging 2, 339–355 (1994).
    [CrossRef]
  67. T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
    [CrossRef]

1997 (1)

B. E. Schefrin, M. L. Bieber, J. S. Werner, “The area of complete spatial summation enlarges with age,” Invest. Ophthalmol. Visual Sci. Suppl. 38, S58 (1997).

1996 (4)

T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
[CrossRef]

L. Ozin, P. J. Bennett, “The effects of aging on spatial frequency tuning,” Invest. Ophthalmol. Visual Sci. Suppl. 37, S1069 (1996).

S. Pardhan, J. Gilchrist, D. B. Elliott, G. K. Beh, “A comparison of sampling efficiency and internal noise level in young and old subjects,” Vision Res. 36, 1641–1648 (1996).
[CrossRef] [PubMed]

R. Hübner, “Specific effects of spatial-frequency uncertainty and different cue types on contrast detection: data and models,” Vision Res. 36, 3429–3439 (1996).
[CrossRef] [PubMed]

1995 (2)

F. Speranza, G. Moraglia, B. A. Schneider, “Age-related changes in binocular vision: detection of noise-masked targets in young and old observers,” J. Gerontol. B 50B, 114–123 (1995).
[CrossRef]

B. E. Schefrin, K. Shinomori, J. S. Werner, “Contributions of neural pathways to age-related losses in chromatic discrimination,” J. Opt. Soc. Am. A 12, 1233–1241 (1995).
[CrossRef]

1994 (3)

P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
[PubMed]

B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

U. Lindenberger, P. B. Baltes, “Sensory functioning and intelligence in old age: a strong connection,” Psychol. Aging 2, 339–355 (1994).
[CrossRef]

1993 (4)

J. Rovamo, H. Hukkonen, K. Tiippana, R. Nasanen, “Effects of luminance and exposure time on contrast sensitivity in spatial noise [letter],” Vision Res. 33, 1123–1129 (1993).
[CrossRef] [PubMed]

S. Pardhan, J. Gilchrist, G. K. Beh, “Contrast detection in noise: a new method for assessing cataract,” Optom. Vision Sci. 70, 914–922 (1993).
[CrossRef]

P. D. Spear, “Neural bases of visual deficits during aging,” Vision Res. 33, 2589–2609 (1993).
[CrossRef] [PubMed]

K. B. Burton, C. Owsley, M. E. Sloane, “Aging and neural spatial contrast sensitivity: photopic vision,” Vision Res. 33, 939–946 (1993).
[CrossRef] [PubMed]

1992 (2)

B. E. Schefrin, J. S. Werner, M. Plach, N. Utlaut, “Sites of age-related sensitivity loss in a short-wave cone pathway,” J. Opt. Soc. Am. A 9, 355–363 (1992).
[CrossRef] [PubMed]

V. Porciatti, D. C. Burr, M. C. Morrone, A. Fircentini, “The effects of ageing on the pattern electroretinogram and visual evoked potential in humans,” Vision Res. 32, 1199–1209 (1992).
[CrossRef] [PubMed]

1991 (1)

S. P. Tipper, “Less attentional selectivity as a result of declining inhibition in older observers,” Bull. Psychonomic Soc. 29, 45–47 (1991).
[CrossRef]

1989 (1)

N. Nameda, T. Kawara, H. Ohzu, “Human visual spatio-temporal frequency performance as a function of age,” Optom. Vision Sci. 66, 760–765 (1989).
[CrossRef]

1988 (4)

1987 (5)

J. E. E. Keunen, D. van Norren, G. J. van Meel, “Density of foveal cone pigments at older age,” Invest. Ophthalmol. Visual Sci. 28, 985–991 (1987).

A. J. Ahumada, “Putting the visual system noise back in the picture,” J. Opt. Soc. Am. A 4, 2372–2378 (1987).
[CrossRef] [PubMed]

G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987).
[CrossRef] [PubMed]

D. B. Elliott, “Contrast sensitivity decline with aging: a neural or optical phenomenon?” Ophthalmic Physiol. Opt. 7, 415–419 (1987).
[CrossRef]

C. T. Scialfa, D. W. Kline, B. J. Lyman, “Age differences in target identification as a function of retinal loca-tion and noise level: examination of the useful field of view,” Psychol. Aging 2, 14–19 (1987).
[CrossRef] [PubMed]

1986 (2)

R. Sekuler, K. Ball, “Visual localization: age and practice,” J. Opt. Soc. Am. A 3, 864–867 (1986).
[CrossRef] [PubMed]

P. E. Kilbride, L. P. Hutman, M. Fishman, J. S. Reed, “Foveal cone pigment density difference in the aging human eye,” Vision Res. 26, 321–325 (1986).
[CrossRef] [PubMed]

1985 (2)

1984 (2)

1983 (5)

A. B. Watson, D. G. Pelli, “quest: a Bayesian adaptive psychometric method,” Percept. Psychophys. 33, 113–120 (1983).
[CrossRef] [PubMed]

C. Owsley, R. Sekuler, D. Siemsen, “Contrast sensitivity throughout adulthood,” Vision Res. 23, 689–699 (1983).
[CrossRef] [PubMed]

E. T. Davis, P. Kramer, N. Graham, “Uncertainty about spatial-frequency, spatial position, or contrast of visual patterns,” Percept. Psychophys. 33, 20–28 (1983).
[CrossRef] [PubMed]

D. J. Tolhurst, J. A. Movshon, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1983).
[CrossRef] [PubMed]

D. J. Madden, “Aging and distraction by highly familiar stimuli during visual search,” Dev. Psychol. 19, 499–507 (1983).
[CrossRef]

1982 (1)

C. Owsley, R. Sekuler, “Spatial summation, contrast threshold, and aging,” Invest. Ophthalmol. Visual Sci. 22, 130–133 (1982).

1981 (2)

D. J. Tolhurst, J. A. Movshon, I. D. Thompson, “The dependence of response amplitude and variance of cat visualcortical neurones on stimulus contrast,” Exp. Brain Res. 41, 414–419 (1981).

M. F. Spiegel, D. M. Green, “Two procedures for estimating internal noise,” J. Acoust. Soc. Am. 70, 69–73 (1981).
[CrossRef] [PubMed]

1977 (1)

D. H. Kelly, “Visual contrast sensitivity,” Opt. Acta 24, 107–129 (1977).
[CrossRef]

1968 (1)

W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
[CrossRef]

1965 (1)

P. Rabbit, “An age-decrement in the ability to ignore irrelevant information,” J. Gerontol. 20, 233–237 (1965).
[CrossRef]

1964 (3)

D. M. Green, “Consistency of auditory detection judgments,” Psychol. Rev. 71, 392–407 (1964).
[CrossRef] [PubMed]

L. A. Jeffress, “Stimulus-oriented approach to detection,” J. Acoust. Soc. Am. 36, 766–774 (1964).
[CrossRef]

N. S. Nagaraja, “Effect of luminance noise on contrast thresholds,” J. Opt. Soc. Am. 54, 950–955 (1964).
[CrossRef]

1962 (1)

P. E. Comalli, S. Wapner, H. Werner, “Interference effects of a Stroop color-word test in children, adulthood, and aging,” J. Gen. Psychol. 100, 47–53 (1962).
[CrossRef]

1960 (1)

C. D. Creelman, “Detection of signals of uncertain frequency,” J. Acoust. Soc. Am. 32, 805–810 (1960).
[CrossRef]

Ahumada, A. J.

Ball, K.

Baltes, P. B.

U. Lindenberger, P. B. Baltes, “Sensory functioning and intelligence in old age: a strong connection,” Psychol. Aging 2, 339–355 (1994).
[CrossRef]

Beh, G. K.

S. Pardhan, J. Gilchrist, D. B. Elliott, G. K. Beh, “A comparison of sampling efficiency and internal noise level in young and old subjects,” Vision Res. 36, 1641–1648 (1996).
[CrossRef] [PubMed]

S. Pardhan, J. Gilchrist, G. K. Beh, “Contrast detection in noise: a new method for assessing cataract,” Optom. Vision Sci. 70, 914–922 (1993).
[CrossRef]

Bennett, P. J.

L. Ozin, P. J. Bennett, “The effects of aging on spatial frequency tuning,” Invest. Ophthalmol. Visual Sci. Suppl. 37, S1069 (1996).

Bieber, M. L.

B. E. Schefrin, M. L. Bieber, J. S. Werner, “The area of complete spatial summation enlarges with age,” Invest. Ophthalmol. Visual Sci. Suppl. 38, S58 (1997).

Burgess, A. E.

Burr, D. C.

V. Porciatti, D. C. Burr, M. C. Morrone, A. Fircentini, “The effects of ageing on the pattern electroretinogram and visual evoked potential in humans,” Vision Res. 32, 1199–1209 (1992).
[CrossRef] [PubMed]

Burton, K. B.

K. B. Burton, C. Owsley, M. E. Sloane, “Aging and neural spatial contrast sensitivity: photopic vision,” Vision Res. 33, 939–946 (1993).
[CrossRef] [PubMed]

C. Owsley, K. B. Burton, “Aging and spatial contrast sensitivity: underlying mechanisms and implications for everyday life,” in The Changing Visual System, P. Bagnoli, W. Hodos, eds. (Plenum, New York, 1991), pp. 119–136.

Caruso, R. C.

Colborne, B.

Comalli, P. E.

P. E. Comalli, S. Wapner, H. Werner, “Interference effects of a Stroop color-word test in children, adulthood, and aging,” J. Gen. Psychol. 100, 47–53 (1962).
[CrossRef]

Creelman, C. D.

C. D. Creelman, “Detection of signals of uncertain frequency,” J. Acoust. Soc. Am. 32, 805–810 (1960).
[CrossRef]

Davis, E. T.

E. T. Davis, P. Kramer, N. Graham, “Uncertainty about spatial-frequency, spatial position, or contrast of visual patterns,” Percept. Psychophys. 33, 20–28 (1983).
[CrossRef] [PubMed]

Dean, A. F.

D. J. Tolhurst, J. A. Movshon, A. F. Dean, “The statistical reliability of signals in single neurons in cat and monkey visual cortex,” Vision Res. 23, 775–785 (1983).
[CrossRef] [PubMed]

deMonasterio, F. M.

Elliott, D. B.

S. Pardhan, J. Gilchrist, D. B. Elliott, G. K. Beh, “A comparison of sampling efficiency and internal noise level in young and old subjects,” Vision Res. 36, 1641–1648 (1996).
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B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

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S. Pardhan, J. Gilchrist, D. B. Elliott, G. K. Beh, “A comparison of sampling efficiency and internal noise level in young and old subjects,” Vision Res. 36, 1641–1648 (1996).
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T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
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P. E. Kilbride, L. P. Hutman, M. Fishman, J. S. Reed, “Foveal cone pigment density difference in the aging human eye,” Vision Res. 26, 321–325 (1986).
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P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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C. T. Scialfa, D. W. Kline, B. J. Lyman, “Age differences in target identification as a function of retinal loca-tion and noise level: examination of the useful field of view,” Psychol. Aging 2, 14–19 (1987).
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Madden, D. J.

D. J. Madden, “Aging and distraction by highly familiar stimuli during visual search,” Dev. Psychol. 19, 499–507 (1983).
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T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
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P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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J. Rovamo, H. Hukkonen, K. Tiippana, R. Nasanen, “Effects of luminance and exposure time on contrast sensitivity in spatial noise [letter],” Vision Res. 33, 1123–1129 (1993).
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L. Ozin, P. J. Bennett, “The effects of aging on spatial frequency tuning,” Invest. Ophthalmol. Visual Sci. Suppl. 37, S1069 (1996).

Pardhan, S.

S. Pardhan, J. Gilchrist, D. B. Elliott, G. K. Beh, “A comparison of sampling efficiency and internal noise level in young and old subjects,” Vision Res. 36, 1641–1648 (1996).
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S. Pardhan, J. Gilchrist, G. K. Beh, “Contrast detection in noise: a new method for assessing cataract,” Optom. Vision Sci. 70, 914–922 (1993).
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A. B. Watson, D. G. Pelli, “quest: a Bayesian adaptive psychometric method,” Percept. Psychophys. 33, 113–120 (1983).
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B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

Plach, M.

Plant, G. T.

D. Kersten, R. F. Hess, G. T. Plant, “Assessing contrast sensitivity behind cloudy media,” Clin. Vision Sci. 2, 143–158 (1988).

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V. Porciatti, D. C. Burr, M. C. Morrone, A. Fircentini, “The effects of ageing on the pattern electroretinogram and visual evoked potential in humans,” Vision Res. 32, 1199–1209 (1992).
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W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in Pascal: The Art of Scientific Computing (Cambridge U. Press, Cambridge, UK, 1989).

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P. Rabbit, “An age-decrement in the ability to ignore irrelevant information,” J. Gerontol. 20, 233–237 (1965).
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P. E. Kilbride, L. P. Hutman, M. Fishman, J. S. Reed, “Foveal cone pigment density difference in the aging human eye,” Vision Res. 26, 321–325 (1986).
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J. Rovamo, H. Hukkonen, K. Tiippana, R. Nasanen, “Effects of luminance and exposure time on contrast sensitivity in spatial noise [letter],” Vision Res. 33, 1123–1129 (1993).
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T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
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Schefrin, B. E.

Schneider, B. A.

F. Speranza, G. Moraglia, B. A. Schneider, “Age-related changes in binocular vision: detection of noise-masked targets in young and old observers,” J. Gerontol. B 50B, 114–123 (1995).
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C. T. Scialfa, D. W. Kline, B. J. Lyman, “Age differences in target identification as a function of retinal loca-tion and noise level: examination of the useful field of view,” Psychol. Aging 2, 14–19 (1987).
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R. Sekuler, A. B. Sekuler, “Visual perception and cognition,” in Oxford Textbook of Geriatric Medicine, J. G. Evans, T. F. Williams, eds. (Oxford University, Oxford, UK, 1992), pp. 572–580.

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R. Sekuler, K. Ball, “Visual localization: age and practice,” J. Opt. Soc. Am. A 3, 864–867 (1986).
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C. Owsley, R. Sekuler, D. Siemsen, “Contrast sensitivity throughout adulthood,” Vision Res. 23, 689–699 (1983).
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C. Owsley, R. Sekuler, “Spatial summation, contrast threshold, and aging,” Invest. Ophthalmol. Visual Sci. 22, 130–133 (1982).

R. Sekuler, A. B. Sekuler, “Visual perception and cognition,” in Oxford Textbook of Geriatric Medicine, J. G. Evans, T. F. Williams, eds. (Oxford University, Oxford, UK, 1992), pp. 572–580.

Shinomori, K.

Siemsen, D.

C. Owsley, R. Sekuler, D. Siemsen, “Contrast sensitivity throughout adulthood,” Vision Res. 23, 689–699 (1983).
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K. B. Burton, C. Owsley, M. E. Sloane, “Aging and neural spatial contrast sensitivity: photopic vision,” Vision Res. 33, 939–946 (1993).
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P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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F. Speranza, G. Moraglia, B. A. Schneider, “Age-related changes in binocular vision: detection of noise-masked targets in young and old observers,” J. Gerontol. B 50B, 114–123 (1995).
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D. J. Tolhurst, J. A. Movshon, I. D. Thompson, “The dependence of response amplitude and variance of cat visualcortical neurones on stimulus contrast,” Exp. Brain Res. 41, 414–419 (1981).

Tiippana, K.

J. Rovamo, H. Hukkonen, K. Tiippana, R. Nasanen, “Effects of luminance and exposure time on contrast sensitivity in spatial noise [letter],” Vision Res. 33, 1123–1129 (1993).
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D. J. Tolhurst, J. A. Movshon, I. D. Thompson, “The dependence of response amplitude and variance of cat visualcortical neurones on stimulus contrast,” Exp. Brain Res. 41, 414–419 (1981).

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P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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van Meel, G. J.

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van Norren, D.

J. E. E. Keunen, D. van Norren, G. J. van Meel, “Density of foveal cone pigments at older age,” Invest. Ophthalmol. Visual Sci. 28, 985–991 (1987).

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B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

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B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

Xue, J. T.

P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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Appl. Opt. (1)

Bull. Psychonomic Soc. (1)

S. P. Tipper, “Less attentional selectivity as a result of declining inhibition in older observers,” Bull. Psychonomic Soc. 29, 45–47 (1991).
[CrossRef]

Clin. Vision Sci. (1)

D. Kersten, R. F. Hess, G. T. Plant, “Assessing contrast sensitivity behind cloudy media,” Clin. Vision Sci. 2, 143–158 (1988).

Dev. Psychol. (1)

D. J. Madden, “Aging and distraction by highly familiar stimuli during visual search,” Dev. Psychol. 19, 499–507 (1983).
[CrossRef]

Exp. Brain Res. (1)

D. J. Tolhurst, J. A. Movshon, I. D. Thompson, “The dependence of response amplitude and variance of cat visualcortical neurones on stimulus contrast,” Exp. Brain Res. 41, 414–419 (1981).

Invest. Ophthalmol. Visual Sci. (3)

J. E. E. Keunen, D. van Norren, G. J. van Meel, “Density of foveal cone pigments at older age,” Invest. Ophthalmol. Visual Sci. 28, 985–991 (1987).

B. Winn, D. Whitaker, D. B. Elliott, N. J. Phillips, “Factors affecting light-adapted pupil size in normal human subjects,” Invest. Ophthalmol. Visual Sci. 35, 1132–1137 (1994).

C. Owsley, R. Sekuler, “Spatial summation, contrast threshold, and aging,” Invest. Ophthalmol. Visual Sci. 22, 130–133 (1982).

Invest. Ophthalmol. Visual Sci. Suppl. (2)

L. Ozin, P. J. Bennett, “The effects of aging on spatial frequency tuning,” Invest. Ophthalmol. Visual Sci. Suppl. 37, S1069 (1996).

B. E. Schefrin, M. L. Bieber, J. S. Werner, “The area of complete spatial summation enlarges with age,” Invest. Ophthalmol. Visual Sci. Suppl. 38, S58 (1997).

J. Acoust. Soc. Am. (3)

M. F. Spiegel, D. M. Green, “Two procedures for estimating internal noise,” J. Acoust. Soc. Am. 70, 69–73 (1981).
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J. Gen. Psychol. (1)

P. E. Comalli, S. Wapner, H. Werner, “Interference effects of a Stroop color-word test in children, adulthood, and aging,” J. Gen. Psychol. 100, 47–53 (1962).
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J. Gerontol. (1)

P. Rabbit, “An age-decrement in the ability to ignore irrelevant information,” J. Gerontol. 20, 233–237 (1965).
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J. Gerontol. B (2)

T. A. Salthouse, H. E. Hancock, E. J. Meinz, D. Z. Hambrick, “Interrelations of age, visual acuity, and cognitive functioning,” J. Gerontol. B 51B, P317–P330 (1996).
[CrossRef]

F. Speranza, G. Moraglia, B. A. Schneider, “Age-related changes in binocular vision: detection of noise-masked targets in young and old observers,” J. Gerontol. B 50B, 114–123 (1995).
[CrossRef]

J. Math. Psychol. (1)

W. A. Wickelgren, “Unidimensional strength theory and component analysis of noise in absolute and comparative judgments,” J. Math. Psychol. 5, 102–122 (1968).
[CrossRef]

J. Neurophysiol. (1)

P. D. Spear, R. J. Moore, C. B. Kim, J. T. Xue, N. Tumosa, “Effects of aging on the primate visual system: spatial and temporal processing by lateral geniculate neurons in young adult and old rhesus monkeys,” J. Neurophysiol. 72, 402–420 (1994).
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J. Opt. Soc. Am. (1)

J. Opt. Soc. Am. A (10)

K. E. Higgens, M. J. Jaffee, R. C. Caruso, F. M. deMonasterio, “Spatial contrast sensitivity: effects of age, test–retest, and psychophysical method,” J. Opt. Soc. Am. A 5, 2173–2180 (1988).
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P. Kramer, N. Graham, D. Yager, “Simultaneous measurement of spatial-frequency summation and uncertainty effects,” J. Opt. Soc. Am. A 2, 1533–1542 (1985).
[CrossRef] [PubMed]

A. E. Burgess, B. Colborne, “Visual signal detection. IV. Observer inconsistency,” J. Opt. Soc. Am. A 5, 617–627 (1988).
[CrossRef] [PubMed]

G. E. Legge, D. Kersten, A. E. Burgess, “Contrast discrimination in noise,” J. Opt. Soc. Am. A 4, 391–404 (1987).
[CrossRef] [PubMed]

A. J. Ahumada, A. B. Watson, “Equivalent-noise model for contrast detection and discrimination,” J. Opt. Soc. Am. A 2, 1133–1139 (1985).
[CrossRef] [PubMed]

A. J. Ahumada, “Putting the visual system noise back in the picture,” J. Opt. Soc. Am. A 4, 2372–2378 (1987).
[CrossRef] [PubMed]

J. S. Werner, V. G. Steele, “Sensitivity of human foveal color mechanisms throughout the life span,” J. Opt. Soc. Am. A 5, 2122–2130 (1988).
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B. E. Schefrin, K. Shinomori, J. S. Werner, “Contributions of neural pathways to age-related losses in chromatic discrimination,” J. Opt. Soc. Am. A 12, 1233–1241 (1995).
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B. E. Schefrin, J. S. Werner, M. Plach, N. Utlaut, “Sites of age-related sensitivity loss in a short-wave cone pathway,” J. Opt. Soc. Am. A 9, 355–363 (1992).
[CrossRef] [PubMed]

R. Sekuler, K. Ball, “Visual localization: age and practice,” J. Opt. Soc. Am. A 3, 864–867 (1986).
[CrossRef] [PubMed]

Ophthalmic Physiol. Opt. (1)

D. B. Elliott, “Contrast sensitivity decline with aging: a neural or optical phenomenon?” Ophthalmic Physiol. Opt. 7, 415–419 (1987).
[CrossRef]

Opt. Acta (1)

D. H. Kelly, “Visual contrast sensitivity,” Opt. Acta 24, 107–129 (1977).
[CrossRef]

Optom. Vision Sci. (2)

N. Nameda, T. Kawara, H. Ohzu, “Human visual spatio-temporal frequency performance as a function of age,” Optom. Vision Sci. 66, 760–765 (1989).
[CrossRef]

S. Pardhan, J. Gilchrist, G. K. Beh, “Contrast detection in noise: a new method for assessing cataract,” Optom. Vision Sci. 70, 914–922 (1993).
[CrossRef]

Percept. Psychophys. (2)

A. B. Watson, D. G. Pelli, “quest: a Bayesian adaptive psychometric method,” Percept. Psychophys. 33, 113–120 (1983).
[CrossRef] [PubMed]

E. T. Davis, P. Kramer, N. Graham, “Uncertainty about spatial-frequency, spatial position, or contrast of visual patterns,” Percept. Psychophys. 33, 20–28 (1983).
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Other (18)

R. Sekuler, A. B. Sekuler, “Visual perception and cognition,” in Oxford Textbook of Geriatric Medicine, J. G. Evans, T. F. Williams, eds. (Oxford University, Oxford, UK, 1992), pp. 572–580.

C. Owsley, K. B. Burton, “Aging and spatial contrast sensitivity: underlying mechanisms and implications for everyday life,” in The Changing Visual System, P. Bagnoli, W. Hodos, eds. (Plenum, New York, 1991), pp. 119–136.

D. G. Pelli, “The quantum efficiency of vision,” in Vision: Coding and Efficiency, C. Blakemore, ed. (Cambridge U. Press, Cambridge, UK, 1990), pp. 3–24.

Luminance quantization altered the contrast of the sine wave gratings and noise used in these experiments. The lowest detection thresholds were obtained with the 1 c/deg target with no frequency uncertainty, so the effects of quantization should have been greatest in that condition. We therefore examined the possible effects in that condition. First, in software we re-created the stimulus luminance profiles presented on the screen when pattern contrast was set to detection threshold, and we counted the number of luminance steps in the pattern. At detection threshold (e.g., contrasts of 0.014 and 0.015 for young and old observers, respectively), the gratings had four luminance steps and 95% of the stimulus power was concentrated at the nominal target frequency. The number of luminance steps did not drop below four until stimulus contrast was reduced below 0.01. Thus the quantization effects were small, even for stimuli presented at detection threshold. Next, we examined the raw data to find observers who might have had thresholds below 0.01 by looking for observers who consistently responded correctly for contrasts as low as 0.01. Four old observers and four young observers met this criterion. We then replaced thresholds for those observers with a value of 0.007, which was approximately one half of the average threshold and was the smallest contrast that could be produced with our equipment, and repeated all of our statistical analyses. The results of the new analyses were identical to those reported in Section 3. Thus luminance quantization does not appear to have had a significant effect on our results.

W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, Numerical Recipes in Pascal: The Art of Scientific Computing (Cambridge U. Press, Cambridge, UK, 1989).

Some old observers had trouble manipulating the keyboard while viewing the patterns. For these observers the experimenter pressed the key that corresponded to the pattern indicated verbally by the observer. To eliminate any effects of experimenter bias, the experimenter’s view of the display was blocked during each trial.

A. E. Burgess, “High level visual decision efficiencies,” in Vision: Coding and Efficiency, C. Blakemore, ed. (Cambridge U. Press, Cambridge, UK, 1990), pp. 431–440.

The performance of a quantum-limited observer is constrained by quantal fluctuations, and therefore one might expect the threshold versus noise curve to intercept the abscissa at the spectral density of the photon noise. However, in our framework photon noise is an external noise added to the stimulus. If it were possible to reduce photon noise, then the quantum-limited threshold would approach zero. Pelli12 showed that the spectral density of photon noise equals the reciprocal of the photon flux and that it is approximately two orders of magnitude less than the spectral density of the equivalent noise estimated in most grating detection experiments. Our experiments used one-dimensional static noise and did not consider the effects of photon noise.

It is necessary to convert from units of space average luminance to retinal illuminance to compare our results with previous measurements. We did not measure pupil diameters of the observers in our experiments, and so we estimated illuminance in the following way. Subsequent to the main experiments, pupil diameters were measured on five young observers. Average pupil diameter was 5.5 mm for the high-luminance display. We were unable to measure pupil size reliably in the low-luminance condition, but previous studies41,42 have found that pupil diameter increases by 40–50% over this luminance range. On the basis of these measurements it is reasonable to assume that decreasing luminance from 80 to 1.6 cd m-2 reduced retinal illuminance from approximately 1900 to 80 td. Kelly43 reported that contrast sensitivity at 8 c/deg drops by approximately 0.4 log unit, whereas sensitivity for 1 and 3 c/deg remains nearly constant, over this range of retinal illuminances. These values do not differ appreciably from those found in the current study at 9, 3, and 1 c/deg.

Y. Le Grand, Light, Colour and Vision (Chapman & Hall, London, 1957).

The simulation consisted of 2AFC trials in which a detector was presented with a noise stimulus and a signal-plus-noise stimulus. The noise stimulus was an array of random numbers drawn from a zero-mean Gaussian distribution. The signal-plus-noise stimulus was another array of Gaussian random variables to which was added a sine wave target in random phase. The detector decided which stimulus contained the target by computing the power in a frequency band centered on the target frequency and selecting the stimulus with the greatest power. The Gaussian noise consisted of two components, one fixed and the other variable. The fixed component represented the detector’s internal noise and was held constant. The variable component represented the external noise and was varied across simulations to compute the detector’s calculation efficiency. The detector’s threshold was computed by measuring percentage correct for 400 simulated trials at each of 12 simulated target amplitudes, fitting a Weibull function to the data, and calculating the 81% correct point. Thresholds were measured for five levels of external noise, and Eq. (6) was used to estimate the detector’s calculation efficiency and internal noise. As expected, the calculation efficiency of the simulated ideal detector (filter bandwidth = 1 c/image) was 1. Next, calculation efficiency was computed for a detector with a filter bandwidth (W) that ranged from 1 to 30 c/image: Across this range, efficiency equalled 1/W0.4. Finally, spatial-frequency uncertainty was simulated by forcing the detector to compute power at three bands of spatial frequencies centered at 10, 30, and 90 c/image. The bandwidth of each channel was varied with the restriction that the three frequency bands never overlapped. The power from each band was combined in two ways. In the maximum-response simulations, the detector chose the stimulus that yielded the largest number. In the summation-of-response simulations, the three numbers were added and the detector chose the stimulus that yielded the largest sum.

N. Graham, Visual Pattern Analyzers (Oxford University, New York, 1989).

For the case in which phase is unknown, the noise and signal-plus-noise distributions for the ideal detector are neither normal nor constant variance. Strictly speaking, therefore, Eq. (5) applies to the detection index dS, not d′. When the distributions are normal and constant variance, dS=d′.

Previous studies have shown that detection versus noise curves obtained from young observers are linear. Pardhan et al.19 obtained similar results with old observers. However, those previous studies used conditions in which position uncertainty was minimized, whereas position uncertainty was maximized in the current experiment. We therefore conducted a preliminary experiment to examine whether contrast versus noise functions were linear in our stimulus conditions. The experiment was identical to the no-uncertainty condition in the main experiment except that four levels of external noise (contrast standard deviations of 0.04, 0.09, 0.16, and 0.25) were used. Four young observers (23–33 years; median age at 24 years) and one old observer (63 years) were tested. Multiple thresholds were obtained at each level of external noise, and the best-fitting line was computed for the data from each observer. In all cases, thresholds were well fit by a straight line (R2>0.87) and the quadratic component of the regression was not statistically significant. Efficiency and equivalent noise were calculated by first fitting the equation E=mN+b to each observer’s data, where E is threshold energy, N is the external noise’s spectral density, m is the line’s slope, and b is the line’s intercept. According to Eq. (6), J=(1/m) * (d′+1/2)2 and Ni=b * J/(d′+1/2)2.

R. E. Kirk, Experimental Design: Procedures for the Behavioral Sciences (Wadsworth, Belmont, Calif., 1968).

Thresholds from individual subjects are available from P. J. Bennett on request.

D. W. Kline, “Light, ageing and visual performance,” in The Susceptible Visual Apparatus, J. Marshall, ed. (Macmillan, London, 1991), pp. 150–161.

R. A. Weale, The Aging Eye (Lewis, London, 1963).

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Figures (7)

Fig. 1
Fig. 1

Hypothetical contrast detection versus noise functions that illustrate the effects of altering equivalent noise and calculation efficiency. Threshold signal energy is a linear function of noise spectral density. Curve A illustrates the function for an ideal detector. When threshold is defined as d=1, the curve has a slope of 1 and calculation efficiency equals 1. Also, the curve intercepts the abscissa at the origin, so equivalent noise is zero. Curve B has a slope of 1 (calculation efficiency is 1) and an intercept of -1 (equivalent noise is 1). Curve C has a slope of 2 (calculation efficiency is 0.5) and an intercept of 0 (equivalent noise is 0). Curve D has a slope of 2 (calculation efficiency is 0.5) and an intercept of -1 (equivalent noise is 1).

Fig. 2
Fig. 2

Simple model of a real observer. The stimulus is the sum of a grating (contrast energy is E) and external noise (spectral density is N). A constant internal noise (spectral density is Ni) is added to the input. Finally, a contrast-invariant calcula-tion yields a decision variable (adapted from Pelli12).

Fig. 3
Fig. 3

Grating detection thresholds, expressed in terms of contrast energy, in the (a) no-uncertainty and (b) frequency-uncertainty conditions plotted as a function of spatial frequency. Thresholds from old and young observers are indicated by filled and open symbols, respectively. Data in the high-noise and low- noise conditions are shown by the dashed and solid lines, respectively. Each symbol shows the geometric mean; error bars show ±1 standard error. In conditions in which no error bar is visible, the standard error is smaller than the width of the symbol.

Fig. 4
Fig. 4

The effect of spatial-frequency uncertainty on grating detection thresholds in the (a) low-noise and (b) high-noise conditions. The effect of spatial-frequency uncertainty was defined as the logarithm of the ratio obtained by dividing energy detection thresholds in the frequency-uncertainty condition by thresholds in the no-uncertainty condition. The uncertainty effect was computed for each observer and then averaged across observers in each condition. Data from old and young observers are indicated by filled and open symbols, respectively. Error bars show ±1 standard error.

Fig. 5
Fig. 5

Calculation efficiency in the (a) no-uncertainty and (b) frequency-uncertainty conditions plotted as a function of spatial frequency. Efficiencies from old and young observers are indicated by filled and open circles, respectively. Efficiencies from low-luminance control observers are plotted as open diamonds. Efficiency was computed for each observer with Eq. (6) and then averaged across observers in each condition. Each symbol shows the geometric mean. Error bars in (a) show 1 standard error and in (b) show ±1 standard error. Note that old observers have the lowest calculation efficiency in all conditions.

Fig. 6
Fig. 6

Equivalent noise in the (a) no-uncertainty and (b) frequency-uncertainty conditions plotted as a function of spatial frequency. Symbol conventions are the same as in Fig. 5. Equivalent noise was computed for each observer with Eq. (6) and then averaged across observers. The symbols on the left- and right-hand sides of (a) show the median equivalent noise for 1 and 9 c/deg. All other symbols show group means; error bars show ±1 standard error. For clarity, the medians at 3 c/deg and for the low-luminance control group at 1 c/deg have been omitted, but they were essentially identical to the means.

Fig. 7
Fig. 7

Grating detection thresholds, expressed in terms of contrast energy, measured in young observers in the (a) low-noise and (b) high-noise conditions in the low-luminance control experiment. Also shown are the detection thresholds from old and young observers in the no-uncertainty condition of the main experiment. Symbol conventions are the same as in Fig. 5. The symbols indicate geometric means; error bars show ±1 standard error.

Equations (7)

Equations on this page are rendered with MathJax. Learn more.

E=(d2)J(N+Ni),
c(x, y)=[L(x, y)-La]/La,
c(x, y)=α cos(2πfy-Φ)+G(y, σ),
E=D c22,
E=d+122N,
E=d+122J(N+Ni).
J=1/W0.4,

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