Person: Serrano Pedraza, Ignacio
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First Name
Ignacio
Last Name
Serrano Pedraza
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Psicología
Department
Psicología Experimental, Procesos Cognitivos y Logopedia
Area
Psicología Básica
Identifiers
4 results
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Item Evidence for reciprocal antagonism between motion sensors tuned to coarse and fine features(Journal of vision, 2007) Serrano Pedraza, Ignacio; Goddard, Paul; Derrington, Andrew MEarly visual processing analyses fine and coarse image features separately. Here we show that motion signals derived from fine and coarse analyses are combined in rather a surprising way: Coarse and fine motion sensors representing the same direction of motion inhibit one another and an imbalance can reverse the motion perceived. Observers judged the direction of motion of patches of filtered two-dimensional noise, centered on 1 and 3 cycles/deg. When both sets of noise were present and only the 3 cycles/deg noise moved, judgments were reversed at short durations. When both sets of noise moved, judgments were correct but sensitivity was impaired. Reversals and impairments occurred both with isotropic noise and with orientation-filtered noise. The reversals and impairments could be simulated in a model of motion sensing by adding a stage in which the outputs of motion sensors tuned to 1 and 3 cycles/deg and the same direction of motion were subtracted from one another. The subtraction model predicted and we confirmed in experiments with orientation-filtered noise that if the 1 cycle/deg noise flickered and the 3 cycles/deg noise moved, the 1 cycle/deg noise appeared to move in the opposite direction to the 3 cycles/deg noise even at long durations.Item 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 MOur 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.Item Antagonism between fine and coarse motion sensors depends on stimulus size and contrast(Journal of vision, 2010) Serrano Pedraza, Ignacio; Derrington, Andrew MThe perceived direction of motion of a brief visual stimulus that contains fine features reverses if static coarser features are added to it. Here we show that the reversal in perceived direction disappears if the stimulus is reduced in size from 2.8 deg to 0.35 deg radius. We show that for a stimulus with 1.4 deg radius, the reversals occur when the ratio between the contrast of the fine features and of the coarser features is higher than 0.8 and lower than 4. For stimulus with 0.35 deg radius, the reversals never appear for any contrast ratio. We also show that if the stimulus is presented within an annular window with small radius, errors disappear but they return if the radius is increased to 2 deg. The errors in motion discrimination described here can be explained by a model of motion sensing in which the signals from fine-scale and coarse-scale sensors are subtracted from one another (I. Serrano-Pedraza, P. Goddard, & A. M. Derrington, 2007). The model produces errors in direction when the signals in the fine and coarse sensors are approximately balanced. The errors disappear when stimulus size is reduced because the reduction in size differentially reduces the response of the low spatial frequency motion sensors.Item 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 MIn 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.