Person:
Sierra Vázquez, Vicente

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First Name
Vicente
Last Name
Sierra Vázquez
URI
https://hdl.handle.net/20.500.14352/84038
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Psicología
Department
Area
Psicología Básica
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20132
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Start date: 2010 × Subject: 159.9.07 ×

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    Comparing the effect of the interaction between fine and coarse scales and surround suppression on motion discrimination.
    (Journal of vision, 2013) Serrano Pedraza, Ignacio; Gamonoso Cruz, María J; Sierra Vázquez, Vicente; Derrington, Andrew M
    Our ability to discriminate motion direction in a Gabor patch diminishes with increasing size and contrast, indicating surround suppression. Discrimination is also impaired by a static low-spatial-frequency patch added to the moving stimulus, suggesting an antagonism between sensors tuned to fine and coarse features. Using Bayesian staircases, we measured duration thresholds in motion-direction discrimination tasks using vertically oriented Gabor patches moving at 2°/s. In two experiments, we tested two contrasts (2.8% and 46%), five window sizes (from 0.7° to 5°), and two spatial frequencies (1 c/deg and 3 c/deg), either presented alone or added to a static pattern. When the moving pattern was presented alone, duration thresholds increased with size at high contrast and decreased with size at low contrast. At low contrast, when a static pattern of 3 c/deg was added to a moving pattern of 1 c/deg, duration thresholds were similar to the case when the moving pattern was presented alone; however, at high contrast, duration thresholds were facilitated, eliminating the effect of surround suppression. When a static pattern of 1 c/deg was added to a moving pattern of 3 c/deg, duration thresholds increased about 4 times for high contrast and 2 times for low contrast. These results show that the antagonism between sensors tuned to fine and coarse scales is more complex than surround suppression, suggesting that it reflects the operation of a different mechanism.
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    Power spectrum model of visual masking: simulations and empirical data
    (Journal of the Optical Society of America. A, Optics, image science, and vision, 2013) Serrano Pedraza, Ignacio; Sierra Vázquez, Vicente; Derrington, Andrew M
    In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.