Mach bands, the illusory brightness maxima and minima perceived at the initiation and termination of luminance gradients, respectively, are generally considered a direct perceptual manifestation of lateral inhibitory interactions among retinal or other lower order visual neurons. Here we examine an alternative explanation, namely that Mach bands arise as a consequence of real-world luminance gradients. In this first of two companion papers, we analyze the natural sources of luminance gradients, demonstrating that real-world gradients arising from curved surfaces are ordinarily adorned by photometric highlights and lowlights in the position of the illusory bands. The prevalence of such gradients provides an empirical basis for the generation of this perceptual phenomenon. (+info)
Mach bands as empirically derived associations.
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If Mach bands arise as an empirical consequence of real-world luminance profiles, several predictions follow. First, the appearance of Mach bands should accord with the appearance of naturally occurring highlights and lowlights. Second, altering the slope of an ambiguous luminance gradient so that it corresponds more closely to gradients that are typically adorned with luminance maxima and minima in the position of Mach bands should enhance the illusion. Third, altering a luminance gradient so that it corresponds more closely to gradients that normally lack luminance maxima and minima in the position of Mach bands should diminish the salience of the illusion. Fourth, the perception of Mach bands elicited by the same luminance gradient should be changed by contextual cues that indicate whether the gradient is more or less likely to signify a curved or a flat surface. Because each of these predictions is met, we conclude that Mach bands arise because the association elicited by the stimulus (the percept) incorporates these features as a result of past experience. (+info)
Multiple time scales is well named.
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Staddon and Higa's article is a critique of scalar expectancy theory, and a proposed alternative, multiple time scales. The critique is generally flawed, both factually and logically. The alternative is bewildering in its flexibility, opaque in its quantitative description, and never addressed to real data. (+info)
Modeling modeling.
(20/3601)
Models are tools; they need to fit both the hand and the task. Presence or absence of a feature such as a pacemaker or a cascade is not in itself good. Or bad. Criteria for model evaluation involve benefit-cost ratios, with the numerator a function of the range of phenomena explained, goodness of fit, consistency with other nearby models, and intangibles such as beauty. The denominator is a function of complexity, the number of phenomena that must be ignored, and the effort necessary to incorporate the model into one's parlance. Neither part of the ratio can yet be evaluated for MTS, whose authors provide some cogent challenges to SET. (+info)
Segmentation by color influences responses of motion-sensitive neurons in the cortical middle temporal visual area.
(21/3601)
We previously showed that human subjects are better able to discriminate the direction of a motion signal in dynamic noise when the signal is distinguished (segmented) from the noise by color. This finding suggested a hitherto unexplored avenue of interaction between motion and color pathways in the primate visual system. To examine whether chromatic segmentation exerts a similar influence on cortical neurons that contribute to motion direction discrimination, we have now compared the discriminative capacity of single MT neurons and psychophysical observers viewing motion signals with and without chromatic segmentation. All data were obtained from rhesus monkeys trained to discriminate motion direction in dynamic stimuli containing varying proportions of coherently moving (signal) and randomly moving (noise) dots. We obtained psychophysical and neurophysiological data in the same animals, on the same trials, and using the same visual display. Chromatic segmentation of the signal from the noise enhanced both neuronal and psychophysical sensitivity to the motion signal but had a smaller influence on neuronal than on psychophysical sensitivity. Hence the ratio of neuronal to psychophysical thresholds, one measure of the relation between neuronal and psychophysical performance, depended on chromatic segmentation. Increased neuronal sensitivity to chromatically segmented displays stemmed from larger and less noisy responses to motion in the preferred directions of the neurons, suggesting that specialized mechanisms influence responses in the motion pathway when color segments motion signal in visual scenes. These findings lead us to reevaluate potential mechanisms for pooling of MT responses and the role of MT in motion perception. (+info)
Neuronal basis of contrast discrimination.
(22/3601)
Psychophysical contrast increment thresholds were compared with neuronal responses, inferred from functional magnetic resonance imaging (fMRI) to test the hypothesis that contrast discrimination judgements are limited by neuronal signals in early visual cortical areas. FMRI was used to measure human brain activity as a function of stimulus contrast, in each of several identifiable visual cortical areas. Contrast increment thresholds were measured for the same stimuli across a range of baseline contrasts using a temporal 2AFC paradigm. FMRI responses and psychophysical measurements were compared by assuming that: (1) fMRI responses are proportional to local average neuronal activity; (2) subjects choose the stimulus interval that evoked the greater average neuronal activity; and (3) variability in the observer's psychophysical judgements was due to additive (IID) noise. With these assumptions, FMRI responses in visual areas V1, V2d, V3d and V3A were found to be consistent with the psychophysical judgements, i.e. a contrast increment was detected when the fMRI responses in each of these brain areas increased by a criterion amount. Thus, the pooled activity of large numbers of neurons can reasonably well predict behavioral performance. The data also suggest that contrast gain in early visual cortex depends systematically on spatial frequency. (+info)
Noisy templates explain area summation.
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The noisy template model is a variant of an ideal detector for a signal known except for contrast. The ideal detector cross-correlates the stimulus with a normalised template which is matched to the known signal pattern. The noisy template model simply adds noise to the matched template every time it is cross-correlated with the signal. This paper outlines the predictions of the noisy template model for area summation. The noisy template model explains Piper's Law, as does the ideal-observer, but it also explains critical area phenomena and the lack of area summation for contrast discrimination. (+info)
Does the visual system exploit projective geometry to help solve the motion correspondence problem?
(24/3601)
Projective geometry determines how the retinal image of an object deforms as it moves through three-dimensional space. Does the visual system use constraints derived from this information, such as rigidity, to aid the tracking of moving objects? A novel psychophysical technique is introduced for assessing which of two competing motion transformations is 'preferred' by the visual system, in a two-frame sequence. In the first experiment, relative preference strengths for translations parallel and perpendicular to the major axis of a wire-frame object were measured by pitting the two against each other. It was found that parallel translations were preferred to perpendicular ones. On the basis of these data a proximity measure for normalising different transformations, independent of any effects of figural similarity, was developed. In the second experiment, two wire-frame planar structures were used to pit one of five transformations (rotation, expansion, vertical expansion, shear and random jitter) against a translation. Preference strength was measured as the translation distance at which the transformation and the translation were perceived with equal frequency. The PSEs were found to collapse on to a single line when plotted against the proximity magnitude, with the exception of a residual preference for pure translation over all other transformations. In general, these results suggest that preference strength for moving wire-frame figures is determined primarily by the proximity of local features on the displacing contour, with little regard for the projective shape transformation. (+info)