Biomedical subjects

L Pessoa

Publications and source records attributed to L Pessoa.

11 recordsLinked to original sources

PubMed2002

Neural processing of emotional faces requires attention.

Attention gates the processing of stimuli relatively early in visual cortex. Yet, existing data suggest that emotional stimuli activate brain regions automatically, largely immune from attentional control. To resolve this puzzle, we used functional magnetic resonance imaging to first measure activation in regions that responded differentially to faces with emotional expressions (fearful and happy) compared with neutral faces. We then measured the modulation of these responses by attention, using a competing task with a high attentional load. Contrary to the prevailing view, all brain regions responding differentially to emotional faces, including the amygdala, did so only when sufficient attentional resources were available to process the faces. Thus, the processing of facial expression appears to be under top-down control.

Adult↗

PubMed2001

Visual filling-in for computing perceptual surface properties.

The visual system is constantly confronted with the problem of integrating local signals into more global arrangements. This arises from the nature of early cell responses, whether they signal localized measures of luminance, motion, retinal position differences, or discontinuities. Consequently, from sparse, local measurements, the visual system must somehow generate the most likely hypothesis that is consistent with them. In this paper, we study the problem of determining achromatic surface properties, namely brightness. Mechanisms of brightness filling-in have been described by qualitative as well as quantitative models, such as by the one proposed by Cohen and Grossberg. We demonstrate that filling-in from contrast estimates leads to a regularized solution for the computational problem of generating brightness representations from sparse estimates. This provides deeper insights into the nature of filling-in processes and the underlying objective function one wishes to compute. This particularly guided the proposal of a new modified version of filling-in, namely confidence-based filling-in which generates more robust brightness representations. Our investigation relates the modeling of perceptual data for biological vision to the mathematical frameworks of regularization theory and linear spatially variant diffusion. It therefore unifies different research directions that have so far coexisted in different scientific communities.

Animals↗

PubMed2000

Lightness from contrast: a selective integration model.

As has been observed by Wallach (1948), perceived lightness is proportional to the ratio between the luminances of adjacent regions in simple disk-annulus or bipartite scenes. This psychophysical finding resonates with neurophysiological evidence that retinal mechanisms of receptor adaptation and lateral inhibition transform the incoming illuminance array into local measures of luminance contrast. In many scenic configurations, however, the perceived lightness of a region is not proportional to its ratio with immediately adjacent regions. In a particularly striking example of this phenomenon, called White's illusion, the relationship between the perceived lightnesses of two gray regions is the opposite of what is predicted by local edge ratios or contrasts. This paper offers a new treatment of how local measures of luminance contrast can be selectively integrated to simulate lightness percepts in a wide range of image configurations. Our approach builds on a tradition of edge integration models (Horn, 1974; Land & McCann, 1971) and contrast/filling-in models (Cohen & Grossberg, 1984; Gerrits & Vendrik 1970; Grossberg & Mingolla, 1985a, 1985b). Our selective integration model (SIM) extends the explanatory power of previous models, allowing simulation of a number of phenomena, including White's effect, the Benary Cross, and shading and transparency effects reported by Adelson (1993), as well as aspects of motion, depth, haploscopic, and Gelb induced contrast effects. We also include an independently derived variant of a recent depthful version of White's illusion, showing that our model can inspire new stimuli.

Contrast Sensitivity↗

PubMed1999

Interaction of ON and OFF pathways for visual contrast measurement.

We propose a novel model of visual contrast measurement based on segregated On and Off pathways. Two driving forces have shaped our investigation: (1) establishing a mechanism selective for sharp local transitions in the luminance distribution; (2) generating a robust scheme of oriented contrast detection. Our starting point was the architecture of early stages in the mammalian visual system. We show that the circuit behaves as a soft AND-gate and analyze the scale-space selectivity properties of the model in detail. The theoretical analysis is supplemented by computer simulations in which we selectively investigate key functionalities of the proposed contrast detection scheme. We demonstrate that the model is capable of successfully processing synthetic as well as natural images, thus illustrating the potential of the method for computer vision applications.

Computer Simulation↗

PubMed1998

Texture segregation, surface representation and figure-ground separation.

A widespread view is that most texture segregation can be accounted for by differences in the spatial frequency content of texture regions. Evidence from both psychophysical and physiological studies indicate, however, that beyond these early filtering stages, there are stages of 3-D boundary segmentation and surface representation that are used to segregate textures. Chromatic segregation of element-arrangement patterns--as studied by Beck and colleagues--cannot be completely explained by the filtering mechanisms previously employed to account for achromatic segregation. An element arrangement pattern is composed of two types of elements that are arranged differently in different image regions (e.g. vertically on top and diagonally on the bottom). FACADE theory mechanisms that have previously been used to explain data about 3-D vision and figure-ground separation are here used to simulate chromatic texture segregation data, including data with equiluminant elements on dark or light homogeneous backgrounds, or backgrounds composed of vertical and horizontal dark or light stripes, or horizontal notched stripes. These data include the fact that segregation of patterns composed of red and blue squares decreases with increasing luminance of the interspaces. Asymmetric segregation properties under 3-D viewing conditions with the equiluminant elements close or far are also simulated. Two key model properties are a spatial impenetrability property that inhibits boundary grouping across regions with non-collinear texture elements and a boundary-surface consistency property that uses feedback between boundary and surface representations to eliminate spurious boundary groupings and separate figures from their backgrounds.

Color Perception↗

PubMed1998

Finding out about filling-in: a guide to perceptual completion for visual science and the philosophy of perception.

In visual science the term filling-in is used in different ways, which often leads to confusion. This target article presents a taxonomy of perceptual completion phenomena to organize and clarify theoretical and empirical discussion. Examples of boundary completion (illusory contours) and featural completion (color, brightness, motion, texture, and depth) are examined, and single-cell studies relevant to filling-in are reviewed and assessed. Filling-in issues must be understood in relation to theoretical issues about neural-perceptual isomorphism and linking propositions. Six main conclusions are drawn: (1) visual filling-in comprises a multitude of different perceptual completion phenomena; (2) certain forms of visual completion seem to involve spatially propagating neural activity (neural filling-in) and so, contrary to Dennett's (1991; 1992) recent discussion of filling-in, cannot be described as results of the brain's "ignoring an absence" or "jumping to a conclusion"; (3) in certain cases perceptual completion seems to have measurable effects that depend on neural signals representing a presence rather than ignoring an absence; (4) neural filling-in does not imply either "analytic isomorphism" or "Cartesian materialism," and thus the notion of the bridge locus--a particular neural stage that forms the immediate substrate of perceptual experience--is problematic and should be abandoned; (5) to reject the representational conception of vision in favor of an "enactive" or "animate" conception reduces the importance of filling-in as a theoretical category in the explanation of vision; and (6) the evaluation of perceptual content should not be determined by "subpersonal" considerations about internal processing, but rather by considerations about the task of vision at the level of the animal or person interacting with the world.

Humans↗

PubMed1996

Perceived texture segregation in chromatic element-arrangement patterns: high intensity interference.

An element-arrangement pattern is composed of two types of elements that differ in the ways in which they are arranged in different regions of the pattern. We report experiments on the perceived segregation of chromatic element-arrangement patterns composed of equal-size red and blue squares as the luminances of the surround, the interspaces and the background (surround plus interspaces) are varied. Perceived segregation was markedly reduced by increasing the luminance of the interspaces. Perceived segregation was approximately constant for constant ratios of interspace luminance to square luminance and increased with the contrast ratio of the squares. Unlike achromatic element-arrangement patterns composed of squares differing in lightness [Beck et al (1991). Vision Research, 32, 719-743] perceived segregation did not decrease when the luminance of the interspaces was below that of the squares. Similar results were obtained for red and yellow, red and green, green and yellow, green and blue, and blue and yellow squares. Perceived segregation based on edge alignment was not interfered with by high intensity interspaces. Stereoscopic cues that caused the squares composing the element-arrangement pattern to be seen in front of the interspaces did not greatly improve perceived segregation. One explanation of the results is in terms of inhibitory interactions among achromatic and chromatic cortical cells tuned to spatial frequency and orientation. Alternately, the results may be explained in terms of how the luminance of the interspaces affects the grouping of the squares for encoding surface representations. Neither explanation accounts fully for the data and both mechanisms may be involved.

Color Perception↗

PubMed1996

Mach bands: how many models are possible? Recent experimental findings and modeling attempts.

Mach bands are illusory bright and dark bands seen where a luminance plateau meets a ramp, as in half-shadows or penumbras. A tremendous amount of work has been devoted to studying the psychophysics and the potential underlying neural circuitry concerning this phenomenon. A number of theoretical models also have been proposed, originating in the seminal studies of Mach himself. The present article reviews the main experimental findings after 1965 and the main recent theories of early vision that have attempted to account for the effect. It is shown that the different theories share working principles and can be grouped into three classes: (a) feature-based; (b) rule-based; and (c) filling-in. In order to evaluate individual proposals, it is necessary to consider them in the larger picture of visual science and to determine how they contribute to the understanding of vision in general.

Humans↗

PubMed1996

Mach-band attenuation by adjacent stimuli: experiment and filling-in simulations.

Mach bands are illusory bright and dark bands seen where a luminance plateau meets a ramp, as in half shadows or penumbras. It has previously been shown that Mach bands are attenuated by placing stimuli, such as bars, nearby. It was shown in an experiment in which Mach-band attenuation for bar and Craik-O'Brien stimuli was compared that they are equally effective in attenuating Mach bands. The results suggest that the abrupt luminance transition of a stimulus adjacent to a ramp is responsible for the attenuation. The findings are interpreted in terms of a recent filling-in model of brightness perception and the results of computer simulations of stimuli are shown.

Attention↗

PubMed1996

The perception of lightness in 3-D curved objects.

Lightness constancy in complex scenes requires that the visual system take account of information concerning variations of illumination falling on visible surfaces. Three experiments on the perception of lightness for three-dimensional (3-D) curved objects show that human observers are better able to perform this accounting for certain scenes than for others. The experiments investigate the effect of object curvature, illumination direction, and object shape on lightness perception. Lightness constancy was quite good when a rich local gray-level context was provided. Deviations occurred when both illumination and reflectance changed along the surface of the objects. Does the perception of a 3-D surface and illuminant layout help calibrate lightness judgments? Our results showed a small but consistent improvement between lightness matches on ellipsoid shapes, relative to flat rectangle shapes, under illumination conditions that produce similar image gradients. Illumination change over 3-D forms is therefore taken into account in lightness perception.

Adult↗

PubMed1995

A contrast- and luminance-driven multiscale network model of brightness perception.

A neural network model of brightness perception is developed to account for a wide variety of data, including the classical phenomenon of Mach bands, low- and high-contrast missing fundamental, luminance staircases, and non-linear contrast effects associated with sinusoidal waveforms. The model builds upon previous work on filling-in models that produce brightness profiles through the interaction of boundary and feature signals. Boundary computations that are sensitive to luminance steps and to continuous luminance gradients are presented. A new interpretation of feature signals through the explicit representation of contrast-driven and luminance-driven information is provided and directly addresses the issue of brightness "anchoring". Computer simulations illustrate the model's competencies.

Contrast Sensitivity↗