The Effect of White-Noise Mask Level on Sinewave Contrast Detection Thresholds and the Critical-Band-Masking Model

Serrano‐Pedraza, Ignacio; Sierra-Vázquez, Vicente

doi:10.1017/s1138741600006156

Cited by 5 publications

(3 citation statements)

References 37 publications

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“…Our results go beyond those of Petrov et al (2005) by measuring this bandwidth as a function of center spatial frequency. Our results are consistent with the decreasing spatial frequency bandwidth of simple cells in striate cortex as a function of preferred spatial frequency (De Valois et al, 1982), and the decreasing bandwidth of psychophysical spatial frequency channels (Schofield & Georgeson, 2003; Serrano-Pedraza & Sierra-Vázquez, 2006; Solomon, 2000; Wilson, McFarlane, & Phillips, 1983). This suggests that surround suppression at contrast threshold may largely reflect inhibition by cells tuned to the same spatial frequency as the center.…”

Section: Discussionsupporting

confidence: 88%

“…In order to control the target’s contrast independent of the surround’s contrast, we presented target and surround in different frames and temporally interleaved them (Schofield & Georgeson, 1999; Serrano-Pedraza & Sierra-Vázquez, 2006). Thus, although the frame rate of the monitor was 120 Hz, the stimuli were in practice presented at 60 Hz after frame interleaving.…”

Section: Methodsmentioning

confidence: 99%

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Spatial frequency bandwidth of surround suppression tuning curves

2012

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The contrast detection threshold of a grating located in the periphery is increased if a surrounding grating of the same frequency and orientation is present. This inhibition between center and surround has been termed surround suppression. In this work we measured the spatial frequency bandwidth of surround suppression in the periphery for different spatial frequencies (0.5, 1.1, 3, and 5 cycles/deg) of a sinusoidal grating (target) surrounded by a grating with different spatial frequencies (surround). Using a Bayesian adaptive staircase, we measured contrast detection thresholds in an 8AFC detection task in which the target (grating with a 2.3-deg Butterworth window) could appear in one of eight possible positions at 4° eccentricity. The target was surrounded by a grating (with a 18° Butterworth window) with the same or an orthogonal orientation. In each session we fixed the spatial frequency of the target and changed the spatial frequency and the orientation of the surround. When the surround was orthogonal to the target, the thresholds were similar to those obtained without surround, independent of the surrounding spatial frequency. However, when the target and surround had the same orientation and spatial frequency, the contrast threshold was increased by a factor ranging from 3 to 6 across subjects. This suppression reduced rapidly as the spatial frequency of the surround moved away from that of the target. The bandwidth of the suppressive effect depended on spatial frequency, declining from 2.9 octaves at 0.5 c/deg to 1 octave for frequencies above 3 c/deg. This is consistent with the bandwidth of individual simple cells in visual cortex and of spatial frequency channels measured psychophysically, both of which decline with increasing spatial frequency. This suggests that surround suppression may be due to relatively precise inhibition by cells with the same tuning as the target.

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Section: Discussionsupporting

confidence: 88%

Section: Methodsmentioning

confidence: 99%

Spatial frequency bandwidth of surround suppression tuning curves

2012

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“…Fifth, we wanted to present on the screen all images with a fixed c RMS (c RMS 0.2); then, we needed to obtain the specific value of m for each image (see Figure 1D). The equation (Serrano-Pedraza & Sierra-Vázquez, 2006) used to obtain m was Ekman & Friesen,1976).…”

Section: Appendix B Procedures Used To Construct the Images With A Desmentioning

confidence: 99%

Symmetrical interaction of sex and expression in face classification tasks

Aguado

Garcı́a-Gutiérrez

Serrano‐Pedraza

2009

Perception & Psychophysics

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Classification of faces as to their sex or their expression-with sex and expression varying orthogonally-was studied in three experiments. In Experiment 1, expression classification was influenced by sex, with angry male faces being classified faster than angry female faces. Complementarily, sex classification was faster for happy than for angry female faces. In Experiment 2, mutual interaction of sex and expression was also found when the participants were asked to classify top and bottom face segments. In Experiment 3, a face inversion effect was found for both sex and expression classification of whole faces. However, a symmetrical interaction between sex and expression was again found. The results are discussed in terms of configural versus feature processing in the perception of face sex and expression and of their relevance to face perception models that postulate independent processing of different facial features.

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Testing the horizontal-vertical stereo anisotropy with the critical-band masking paradigm

2013

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Stereo vision has a well-known anisotropy: At low frequencies, horizontally oriented sinusoidal depth corrugations are easier to detect than vertically oriented corrugations (both defined by horizontal disparities). Previously, Serrano-Pedraza and Read (2010) suggested that this stereo anisotropy may arise because the stereo system uses multiple spatial-frequency disparity channels for detecting horizontally oriented modulations but only one for vertically oriented modulations. Here, we tested this hypothesis using the critical-band masking paradigm. In the first experiment, we measured disparity thresholds for horizontal and vertical sinusoids near the peak of the disparity sensitivity function (0.4 cycles/°), in the presence of either broadband or notched noise. We fitted the power-masking model to our results assuming a channel centered on 0.4 cycles/°. The estimated channel bandwidths were 2.95 octaves for horizontal and 2.62 octaves for vertical corrugations. In our second experiment we measured disparity thresholds for horizontal and vertical sinusoids of 0.1 cycles/° in the presence of band-pass noise centered on 0.4 cycles/° with a bandwidth of 0.5 octaves. This mask had only a small effect on the disparity thresholds, for either horizontal or vertical corrugations. We simulated the detection thresholds using the power-masking model with the parameters obtained in the first experiment and assuming either single-channel and multiple-channel detection. The multiple-channel model predicted the thresholds much better for both horizontal and vertical corrugations. We conclude that the human stereo system must contain multiple independent disparity channels for detecting horizontally oriented and vertically oriented depth modulations.

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The Effect of White-Noise Mask Level on Sinewave Contrast Detection Thresholds and the Critical-Band-Masking Model

Cited by 5 publications

References 37 publications

Spatial frequency bandwidth of surround suppression tuning curves

Spatial frequency bandwidth of surround suppression tuning curves

Symmetrical interaction of sex and expression in face classification tasks

Testing the horizontal-vertical stereo anisotropy with the critical-band masking paradigm

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