Abstract

Observers detected a temporally modulated luminance pattern embedded in dynamic noise. A Gabor function with a carrier frequency, in separate conditions of 0, 1.56, or 3.12Hz, modulated signal contrast. Classification images were constructed in the time, temporal frequency, and temporal phase domains. As stimulus frequency increased, amplitudes of the phase images decreased and amplitudes of the frequency images increased, indicating a corresponding shift in the observers’ criteria. The reduced use of phase attenuated time-domain images from signal-absent trials, but physical interactions between signal and noise components tended to preserve time-domain images from signal-present trials. The results illustrate a frequency-dependent strategy shift in detection that may reflect a degree of stimulus uncertainty in the time domain.

© 2005 Optical Society of America

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References

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  1. R. L. DeValois, I. Abramov, G. H. Jacobs, “Analysis of response patterns of LGN cells,” J. Opt. Soc. Am. 56, 966–977 (1966).
    [CrossRef]
  2. R. L. DeValois, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. USA 97, 4997–5002 (2000).
    [CrossRef]
  3. R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
    [CrossRef]
  4. R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
    [CrossRef]
  5. R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
    [CrossRef]
  6. J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.
  7. L. A. Olzak, J. P. Thomas, “Neural recoding in human pattern vision: model and mechanism,” Vision Res. 39, 231–256 (1999).
    [CrossRef] [PubMed]
  8. S. Magnussen, M. W. Greenlee, “The psychophysics of perceptual memory,” Psychol. Res. 62, 81–92 (1999).
    [CrossRef] [PubMed]
  9. A. J. Ahumada, “Detection of tones masked by noise: a comparison of human observers with digital-computer-simulated energy detectors of varying bandwidths,” Ph.D. thesis (University of California, Los Angeles, 1967).
  10. A. J. Ahumada, J. Lovell, “Stimulus features in signal detection,” J. Acoust. Soc. Am. 49, 1751–1756 (1971).
    [CrossRef]
  11. M. P. Eckstein, A. J. Ahumada, “Classification images: a tool to analyze visual strategies,” J. Vision2, doi:10.1167/2.1.i (2002), http://journalofvision.org/2/1/i/.
  12. K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).
  13. M. D’Zmura, K. Knoblauch, “Spectral bandwidths for the detection of color,” Vision Res. 38, 3117–3128 (1998).
    [CrossRef]
  14. R Development Core Team, “R: a language and environment for statistical computing” (R Foundation for Statistical Computing, Vienna, Austria), http://www.R-project.org.
  15. J. A. Solomon, “Noise reveals visual mechanisms of detection and discrimination,” J. Vision 2, 105–120 doi:10.1167/2.1.7 (2002), http://journalofvision.org/2/1/7/.
    [CrossRef]
  16. B. L. Beard, A. J. Ahumada, “A technique to extract relevant image features for visual tasks,” Proc. SPIE 3299, 79–85 (1998).
    [CrossRef]
  17. A. J. Ahumada, B. L. Beard, “Classification images for detection,” Invest. Ophthalmol. Visual Sci. 40, S572 (1999).
  18. E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
    [CrossRef]
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    [CrossRef]
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    [CrossRef]
  21. R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
    [CrossRef]

2005

R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
[CrossRef]

2002

A. J. Ahumada, “Classification image weights and internal noise level estimation,” J. Vision 2, 121–131, doi:10.1167/2.1.8 (2002), http://journalofvision.org/2/1/8/.
[CrossRef]

C. K. Abbey, M. P. Eckstein, “Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiment,” J. Vision 2, 66–78, doi:10.1167/2.1.5 (2002), http://journalofvision.org/2/1/5/.
[CrossRef]

J. A. Solomon, “Noise reveals visual mechanisms of detection and discrimination,” J. Vision 2, 105–120 doi:10.1167/2.1.7 (2002), http://journalofvision.org/2/1/7/.
[CrossRef]

2000

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

R. L. DeValois, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. USA 97, 4997–5002 (2000).
[CrossRef]

1999

K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).

L. A. Olzak, J. P. Thomas, “Neural recoding in human pattern vision: model and mechanism,” Vision Res. 39, 231–256 (1999).
[CrossRef] [PubMed]

S. Magnussen, M. W. Greenlee, “The psychophysics of perceptual memory,” Psychol. Res. 62, 81–92 (1999).
[CrossRef] [PubMed]

A. J. Ahumada, B. L. Beard, “Classification images for detection,” Invest. Ophthalmol. Visual Sci. 40, S572 (1999).

E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
[CrossRef]

1998

B. L. Beard, A. J. Ahumada, “A technique to extract relevant image features for visual tasks,” Proc. SPIE 3299, 79–85 (1998).
[CrossRef]

M. D’Zmura, K. Knoblauch, “Spectral bandwidths for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[CrossRef]

1982

R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
[CrossRef]

R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
[CrossRef]

1971

A. J. Ahumada, J. Lovell, “Stimulus features in signal detection,” J. Acoust. Soc. Am. 49, 1751–1756 (1971).
[CrossRef]

1966

Abbey, C. K.

C. K. Abbey, M. P. Eckstein, “Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiment,” J. Vision 2, 66–78, doi:10.1167/2.1.5 (2002), http://journalofvision.org/2/1/5/.
[CrossRef]

Abramov, I.

Adelson, E. H.

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.

Ahumada, A. J.

A. J. Ahumada, “Classification image weights and internal noise level estimation,” J. Vision 2, 121–131, doi:10.1167/2.1.8 (2002), http://journalofvision.org/2/1/8/.
[CrossRef]

A. J. Ahumada, B. L. Beard, “Classification images for detection,” Invest. Ophthalmol. Visual Sci. 40, S572 (1999).

E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
[CrossRef]

B. L. Beard, A. J. Ahumada, “A technique to extract relevant image features for visual tasks,” Proc. SPIE 3299, 79–85 (1998).
[CrossRef]

A. J. Ahumada, J. Lovell, “Stimulus features in signal detection,” J. Acoust. Soc. Am. 49, 1751–1756 (1971).
[CrossRef]

A. J. Ahumada, “Detection of tones masked by noise: a comparison of human observers with digital-computer-simulated energy detectors of varying bandwidths,” Ph.D. thesis (University of California, Los Angeles, 1967).

M. P. Eckstein, A. J. Ahumada, “Classification images: a tool to analyze visual strategies,” J. Vision2, doi:10.1167/2.1.i (2002), http://journalofvision.org/2/1/i/.

Albrecht, D. G.

R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
[CrossRef]

Barth, E.

E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
[CrossRef]

Beard, B. L.

E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
[CrossRef]

A. J. Ahumada, B. L. Beard, “Classification images for detection,” Invest. Ophthalmol. Visual Sci. 40, S572 (1999).

B. L. Beard, A. J. Ahumada, “A technique to extract relevant image features for visual tasks,” Proc. SPIE 3299, 79–85 (1998).
[CrossRef]

Bennett, P. J.

R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
[CrossRef]

Cottaris, N. P.

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

D’Zmura, M.

K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).

M. D’Zmura, K. Knoblauch, “Spectral bandwidths for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[CrossRef]

DeValois, R. L.

R. L. DeValois, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. USA 97, 4997–5002 (2000).
[CrossRef]

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
[CrossRef]

R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
[CrossRef]

R. L. DeValois, I. Abramov, G. H. Jacobs, “Analysis of response patterns of LGN cells,” J. Opt. Soc. Am. 56, 966–977 (1966).
[CrossRef]

Eckstein, M. P.

C. K. Abbey, M. P. Eckstein, “Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiment,” J. Vision 2, 66–78, doi:10.1167/2.1.5 (2002), http://journalofvision.org/2/1/5/.
[CrossRef]

M. P. Eckstein, A. J. Ahumada, “Classification images: a tool to analyze visual strategies,” J. Vision2, doi:10.1167/2.1.i (2002), http://journalofvision.org/2/1/i/.

Elfar, S. D.

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

Gizzi, M. S.

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.

Greenlee, M. W.

S. Magnussen, M. W. Greenlee, “The psychophysics of perceptual memory,” Psychol. Res. 62, 81–92 (1999).
[CrossRef] [PubMed]

Hepler, N.

R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
[CrossRef]

Jacobs, G. H.

Knoblauch, K.

K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).

M. D’Zmura, K. Knoblauch, “Spectral bandwidths for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[CrossRef]

Lovell, J.

A. J. Ahumada, J. Lovell, “Stimulus features in signal detection,” J. Acoust. Soc. Am. 49, 1751–1756 (1971).
[CrossRef]

Magnussen, S.

S. Magnussen, M. W. Greenlee, “The psychophysics of perceptual memory,” Psychol. Res. 62, 81–92 (1999).
[CrossRef] [PubMed]

Mahon, L. E.

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

Movshon, J. A.

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.

Murray, R. F.

R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
[CrossRef]

Newsome, W. T.

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.

Olzak, L. A.

L. A. Olzak, J. P. Thomas, “Neural recoding in human pattern vision: model and mechanism,” Vision Res. 39, 231–256 (1999).
[CrossRef] [PubMed]

Sekuler, A. B.

R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
[CrossRef]

Solomon, J. A.

J. A. Solomon, “Noise reveals visual mechanisms of detection and discrimination,” J. Vision 2, 105–120 doi:10.1167/2.1.7 (2002), http://journalofvision.org/2/1/7/.
[CrossRef]

Thomas, J. P.

L. A. Olzak, J. P. Thomas, “Neural recoding in human pattern vision: model and mechanism,” Vision Res. 39, 231–256 (1999).
[CrossRef] [PubMed]

K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).

Thorell, L. G.

R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
[CrossRef]

Wilson, J. A.

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

Yund, E. W.

R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
[CrossRef]

Invest. Ophthalmol. Visual Sci.

K. Knoblauch, J. P. Thomas, M. D’Zmura, “Feedback, temporal frequency, and stimulus classification,” Invest. Ophthalmol. Visual Sci. 40, S792 (1999).

A. J. Ahumada, B. L. Beard, “Classification images for detection,” Invest. Ophthalmol. Visual Sci. 40, S572 (1999).

J. Acoust. Soc. Am.

A. J. Ahumada, J. Lovell, “Stimulus features in signal detection,” J. Acoust. Soc. Am. 49, 1751–1756 (1971).
[CrossRef]

J. Opt. Soc. Am.

J. Vision

A. J. Ahumada, “Classification image weights and internal noise level estimation,” J. Vision 2, 121–131, doi:10.1167/2.1.8 (2002), http://journalofvision.org/2/1/8/.
[CrossRef]

C. K. Abbey, M. P. Eckstein, “Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiment,” J. Vision 2, 66–78, doi:10.1167/2.1.5 (2002), http://journalofvision.org/2/1/5/.
[CrossRef]

R. F. Murray, P. J. Bennett, A. B. Sekuler, “Classification images predict absolute efficiency,” J. Vision 5, 139–149, doi:10.1167/5.2.5 (2005), http://journalofvision.org/5/2/5/.
[CrossRef]

J. A. Solomon, “Noise reveals visual mechanisms of detection and discrimination,” J. Vision 2, 105–120 doi:10.1167/2.1.7 (2002), http://journalofvision.org/2/1/7/.
[CrossRef]

Proc. Natl. Acad. Sci. USA

R. L. DeValois, “Some transformations of color information from lateral geniculate nucleus to striate cortex,” Proc. Natl. Acad. Sci. USA 97, 4997–5002 (2000).
[CrossRef]

Proc. SPIE

B. L. Beard, A. J. Ahumada, “A technique to extract relevant image features for visual tasks,” Proc. SPIE 3299, 79–85 (1998).
[CrossRef]

E. Barth, B. L. Beard, A. J. Ahumada, “Nonlinear features in vernier acuity,” Proc. SPIE 3644, 88–96 (1999).
[CrossRef]

Psychol. Res.

S. Magnussen, M. W. Greenlee, “The psychophysics of perceptual memory,” Psychol. Res. 62, 81–92 (1999).
[CrossRef] [PubMed]

Vision Res.

R. L. DeValois, E. W. Yund, N. Hepler, “The orientation and direction selectivity of cells in macaque visual cortex,” Vision Res. 22, 531–544 (1982).
[CrossRef]

R. L. DeValois, D. G. Albrecht, L. G. Thorell, “Spatial frequency selectivity of cells in macaque visual cortex,” Vision Res. 22, 545–559 (1982).
[CrossRef]

R. L. DeValois, N. P. Cottaris, L. E. Mahon, S. D. Elfar, J. A. Wilson, “Spatial and temporal receptive fields of geniculate and cortical cells and directional selectivity,” Vision Res. 40, 3685–3702 (2000).
[CrossRef]

M. D’Zmura, K. Knoblauch, “Spectral bandwidths for the detection of color,” Vision Res. 38, 3117–3128 (1998).
[CrossRef]

L. A. Olzak, J. P. Thomas, “Neural recoding in human pattern vision: model and mechanism,” Vision Res. 39, 231–256 (1999).
[CrossRef] [PubMed]

Other

R Development Core Team, “R: a language and environment for statistical computing” (R Foundation for Statistical Computing, Vienna, Austria), http://www.R-project.org.

J. A. Movshon, E. H. Adelson, M. S. Gizzi, W. T. Newsome, “The analysis of moving visual patterns,” in Pattern Recognition Mechanisms, C. Chagas, R. Gattass, and C. Gross, eds. (Springer, 1985), pp. 117–151.

A. J. Ahumada, “Detection of tones masked by noise: a comparison of human observers with digital-computer-simulated energy detectors of varying bandwidths,” Ph.D. thesis (University of California, Los Angeles, 1967).

M. P. Eckstein, A. J. Ahumada, “Classification images: a tool to analyze visual strategies,” J. Vision2, doi:10.1167/2.1.i (2002), http://journalofvision.org/2/1/i/.

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Figures (4)

Fig. 1
Fig. 1

Classification images for the 0 Hz condition. The first row shows images in the time domain; the second row shows images in the temporal frequency domain; and the third row shows images in the temporal phase domain. Column 1 shows the luminance modulation profile and spectra of the Gabor signal. Columns 2 and 3 show the classification images for observers KK and JPT, respectively. Each data point is a z score, calculated as described in Section 2. Open circles are calculated from signal-present trials; solid circles are calculated from signal-absent trials.

Fig. 2
Fig. 2

Classification images for the 1.56 Hz condition. Other details are the same as in Fig. 1.

Fig. 3
Fig. 3

Classification images for the 3.12 Hz condition. Other details are the same as in Fig. 1.

Fig. 4
Fig. 4

Simulated time-domain images in the 3.12 Hz condition for an observer who uses only frequency information. The decision variable is the dot product between the magnitude spectrum of the signal and the magnitude spectrum of the stimulus. Open circles are calculated for signal-present trials; solid circles represent calculations for signal-absent trials.

Metrics