Parabolic achromatic color matching functions: Dependence on incremental and decremental luminance.

Either the brightness or lightness of a disk surrounded by an annulus is characterized in the most general case by a parabolic function of the annulus luminance when plotted on a log-log scale. This relationship has been modeled with a theory of achromatic color computation based on edge integration and contrast gain control [J. Vis.10, 1 (2010)1534-736210.1167/10.14.40]. We tested predictions of this model in new psychophysical experiments. Our results support the theory and reveal a previously unobserved property of parabolic matching functions that depends on the disk contrast polarity. We interpret this property in terms of a neural edge integration model incorporating data from macaque monkey physiology that indicates different physiological gain factors for incremental and decremental stimuli.

Duration Comparisons for Vision and Touch Are Dependent on Presentation Order and Temporal Context.

Integrating visual and tactile information in the temporal domain is critical for active perception. To accomplish this, coordinated timing is required. Here, we study perceived duration within and across these two modalities. Specifically, we examined how duration comparisons within and across vision and touch were influenced by temporal context and presentation order using a two-interval forced choice task. We asked participants to compare the duration of two temporal intervals defined by tactile or visual events. Two constant standard durations (700 ms and 1,000 ms in 'shorter' sessions; 1,000 ms and 1,500 ms in 'longer' sessions) were compared to variable comparison durations in different sessions. In crossmodal trials, standard and comparison durations were presented in different modalities, whereas in the intramodal trials, the two durations were presented in the same modality. The standard duration was either presented first () or followed the comparison duration (). In both crossmodal and intramodal conditions, we found that the longer standard duration was overestimated in trials and underestimated in trials whereas the estimation of shorter standard duration was unbiased. Importantly, the estimation of 1,000ms was biased when it was the longer standard duration within the shorter sessions but not when it was the shorter standard duration within the longer sessions, indicating an effect of temporal context. The effects of presentation order can be explained by a central tendency effect applied in different ways to different presentation orders. Both crossmodal and intramodal conditions showed better discrimination performance for trials than trials, supporting the Type B effect for both crossmodal and intramodal duration comparison. Moreover, these results were not dependent on whether the standard duration was defined using tactile or visual stimuli. Overall, our results indicate that duration comparison between vision and touch is dependent on presentation order and temporal context, but not modality.

Neurocomputational Lightness Model Explains the Appearance of Real Surfaces Viewed Under Gelb Illumination.

One of the primary functions of visual perception is to represent, estimate, and evaluate the properties of material surfaces in the visual environment. One such property is surface color, which can convey important information about ecologically relevant object characteristics such as the ripeness of fruit and the emotional reactions of humans in social interactions. This paper further develops and applies a neural model (Rudd, 2013, 2017) of how the human visual system represents the light/dark dimension of color-known as lightness-and computes the colors of achromatic material surfaces in real-world spatial contexts. Quantitative lightness judgments conducted with real surfaces viewed under Gelb (i.e., spotlight) illumination are analyzed and simulated using the model. According to the model, luminance ratios form the inputs to ON- and OFF-cells, which encode local luminance increments and decrements, respectively. The response properties of these cells are here characterized by physiologically motivated equations in which different parameters are assumed for the two cell types. Under non-saturating conditions, ON-cells respond in proportion to a compressive power law of the local incremental luminance in the image that causes them to respond, while OFF-cells respond linearly to local decremental luminance. ON- and OFF-cell responses to edges are log-transformed at a later stage of neural processing and then integrated across space to compute lightness via an edge integration process that can be viewed as a neurally elaborated version of Land's retinex model (Land & McCann, 1971). It follows from the model assumptions that the perceptual weights-interpreted as neural gain factors-that the model observer applies to steps in log luminance at edges in the edge integration process are determined by the product of a polarity-dependent factor 1-by which incremental steps in log luminance (i.e., edges) are weighted by the value <1.0 and decremental steps are weighted by 1.0-and a distance-dependent factor 2, whose edge weightings are estimated to fit perceptual data. The model accounts quantitatively (to within experimental error) for the following: lightness constancy failures observed when the illumination level on a simultaneous contrast display is changed (Zavagno, Daneyko, & Liu, 2018); the degree of dynamic range compression in the staircase-Gelb paradigm (Cataliotti & Gilchrist, 1995; Zavagno, Annan, & Caputo, 2004); partial releases from compression that occur when the staircase-Gelb papers are reordered (Zavagno, Annan, & Caputo, 2004); and the larger compression release that occurs when the display is surrounded by a white border (Gilchrist & Cataliotti, 1994).

Brightness in human rod vision depends on slow neural adaptation to quantum statistics of light.

In human rod-mediated vision, threshold for small, brief flashes rises in proportion to the square root of adapting luminance at all but the lowest and highest adapting intensities. A classical signal detection theory from Rose (1942, 1948) and de Vries (1943) attributed this rise to the perceptual masking of weak flashes by Poisson fluctuations in photon absorptions from the adapting field. However, previous work by Brown and Rudd (1998) demonstrated that the square-root law also holds for suprathreshold brightness judgments, a finding that supports an alternative explanation of the square-root sensitivity changes as a consequence of physiological adaptation (i.e., neural gain control). Here, we employ a dichoptic matching technique to investigate the properties of this brightness gain control. We show that the brightness gain control: 1) affects the brightness of high-intensity suprathreshold flashes for which assumptions of the de Vries-Rose theory are strongly violated; 2) exhibits a long time course of 100-200 s; and 3) is subject to modulation by temporal contrast noise when the mean adapting luminance is held constant. These findings are consistent with the hypothesis that the square-root law results from a slow neural adaptation to statistical noise in the rod pool. We suggest that such adaptation may function to reduce the probability of spurious ganglion cell spiking activity due to photon fluctuation noise as the ambient illumination level is increased.

The phantom illusion.

It is well known that visible luminance gradients may generate contrast effects. In this work we present a new paradoxical illusion in which the luminance range of gradual transitions has been reduced to make them invisible. By adopting the phenomenological method proposed by Kanizsa, we have found that unnoticeable luminance gradients still generate contrast effects. But, most interestingly, we have found that when their width is narrowed, rather than generating contrast effects on the surrounded surfaces, they generate an assimilation effect. Both high- and low-level interpretations of this "phantom" illusion are critically evaluated.

A cortical edge-integration model of object-based lightness computation that explains effects of spatial context and individual differences.

Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

Edge integration in achromatic color perception and the lightness-darkness asymmetry.

To maintain color constancy, the human visual system must distinguish surface reflectance-based variations in wavelength and luminance from variations due to illumination. Edge integration theory proposes that this is accomplished by spatially integrating steps in luminance and color contrast that likely result from reflectance changes. Thus, a neural representation of relative reflectance within the visual scene is constructed. An anchoring rule-the largest reflectance in the neural representation appears white-is then applied to map relative lightness onto an absolute lightness scale. A large body of data on human lightness judgments is here shown to be consistent with an edge integration model in which the visual system performs a weighted sum of steps in log luminance across space. Three hypotheses are proposed regarding how weights are applied to edges. First, weights decline with distance from the target surface whose lightness is being computed. Second, larger weights are given to edges whose dark sides point towards the target. Third, edge integration is carried out along a path leading from a common background field, or surround, to the target location. The theory accounts for simultaneous contrast; quantitative lightness judgments made with classical disk-annulus, Gilchrist dome, and Gelb displays; and perceptual filling-in lightness. A cortical theory of lightness in the ventral stream of visual cortex (areas V1 → V4) is proposed to instantiate the edge integration algorithm. The neural model is shown to be capable of unifying the quantitative laws of edge integration in lightness perception with the laws governing brightness, including Stevens' power law brightness model, and makes novel predictions about the quantitative laws governing induced darkness.

How attention and contrast gain control interact to regulate lightness contrast and assimilation: a computational neural model.

Recent theories of lightness perception assume that lightness (perceived reflectance) is computed by a process that contrasts the target's luminance with that of one or more regions in its spatial surround. A challenge for any such theory is the phenomenon of lightness assimilation, which occurs when increasing the luminance of a surround region increases the target lightness: the opposite of contrast. Here contrast and assimilation are studied quantitatively in lightness matching experiments utilizing concentric disk-and-ring displays. Whether contrast or assimilation is seen depends on a number of factors including: the luminance relations of the target, surround, and background; surround size; and matching instructions. When assimilation occurs, it is always part of a larger pattern in which assimilation and contrast both occur over different ranges of surround luminance. These findings are quantitatively modeled by a theory that assumes lightness is computed from a weighted sum of responses of edge detector neurons in visual cortex. The magnitude of the neural response to an edge is regulated by a combination of contrast gain control acting between neighboring edge detectors and a top-down attentional gain control that selectively weights the response to stimulus edges according to their task relevance.

The challenges natural images pose for visual adaptation.

Advances in our understanding of natural image statistics and of gain control within the retinal circuitry are leading to new insights into the classic problem of retinal light adaptation. Here we review what we know about how rapid adaptation occurs during active exploration of the visual scene. Adaptational mechanisms must balance the competing demands of adapting quickly, locally, and reliably, and this balance must be maintained as lighting conditions change. Multiple adaptational mechanisms in different locations within the retina act in concert to accomplish this task, with lighting conditions dictating which mechanisms dominate.

The revelation effect for autobiographical memory: a mixture-model analysis.

Participants provided information about their childhood by rating their confidence about whether they had experienced various events (e.g., "broke a window playing ball"). On some trials, participants unscrambled a key word from the event phrase (e.g., wdinwo-window) or an unrelated word (e.g., gnutge-nugget) before seeing the event and giving their confidence ratings. The act of unscrambling led participants to increase their confidence that the event occurred in their childhood, but only when the confidence rating immediately followed the act of unscrambling. This increase in confidence mirrors the "revelation effect" observed in word recognition experiments. In the present article, we analyzed our data using a new signal detection mixture distribution model that does not require the researcher to know the veracity of memory judgments a priori. Our analysis reveals that unscrambling a key word or an unrelated word affects response bias and discriminability in autobiographical memory tests in ways that are very similar to those that have been previously found for word recognition tasks.

Metacontrast masking and the cortical representation of surface color: dynamical aspects of edge integration and contrast gain control.

This paper reviews recent theoretical and experimental work supporting the idea that brightness is computed in a series of neural stages involving edge integration and contrast gain control. It is proposed here that metacontrast and paracontrast masking occur as byproducts of the dynamical properties of these neural mechanisms. The brightness computation model assumes, more specifically, that early visual neurons in the retina, and cortical areas V1 and V2, encode local edge signals whose magnitudes are proportional to the logarithms of the luminance ratios at luminance edges within the retinal image. These local edge signals give rise to secondary neural lightness and darkness spatial induction signals, which are summed at a later stage of cortical processing to produce a neural representation of surface color, or achromatic color, in the case of the chromatically neutral stimuli considered here. Prior to the spatial summation of these edge-based induction signals, the weights assigned to local edge contrast are adjusted by cortical gain mechanisms involving both lateral interactions between neural edge detectors and top-down attentional control. We have previously constructed and computer-simulated a neural model of achromatic color perception based on these principles and have shown that our model gives a good quantitative account of the results of several brightness matching experiments. Adding to this model the realistic dynamical assumptions that 1) the neurons that encode local contrast exhibit transient firing rate enhancement at the onset of an edge, and 2) that the effects of contrast gain control take time to spread between edges, results in a dynamic model of brightness computation that predicts the existence Broca-Sulzer transient brightness enhancement of the target, Type B metacontrast masking, and a form of paracontrast masking in which the target brightness is enhanced when the mask precedes the target in time.

Protective buffering and emotional desynchrony among spousal caregivers of cancer patients.

OBJECTIVE: To examine protective buffering and emotional desynchrony among spousal caregivers of cancer survivors. DESIGN: Repeated measures; 42 caregivers engaged in 2 videotaped, oral emotional expression exercises: 1 in the presence of their patient and 1 in the absence of their patient. MAIN OUTCOME MEASURES: Felt emotion (self-report) and expressed emotion (lexical expression or words uttered and coder-derived facial expression). Other measures assessed mental and physical health, dyadic satisfaction, and dispositional emotional inhibition. RESULTS: Protective buffering differed by communicative channel (lexical vs. facial). Caregivers' facial expressions were more positive when the patient was present versus absent. In contrast, the valence of caregivers' words did not differ per patient presence. Facial protective buffering was unrelated to health and dyadic outcomes. Lexical protective buffering was inversely related to both caregiver and patient marital satisfaction. Dispositional emotional inhibition was inversely related to caregiver mental health and marital satisfaction. Desynchrony occurred when the patient was present but was counter to prediction; felt emotion was more positive than expressed emotion. CONCLUSION: Results provide behavioral evidence of facial protective buffering. To the extent that lexical buffering occurs, it poses a dyadic risk, and chronic inhibition poses both psychological and dyadic risks. Future research is needed to refine the operational definition of desynchrony and to examine the biopsychosocial sequelae of buffering.

Stevens's brightness law, contrast gain control, and edge integration in achromatic color perception: a unified model.

The brightness of an isolated test patch is related to its luminance by a power law having an exponent of about 1/3, a result known as Stevens's brightness law. The brightness law exponent characterizes the rate at which brightness grows with luminance and can thus be thought of as an "exponential" gain factor. We studied changes in this gain factor for incremental and decremental test squares as a function of the size of a surrounding frame of homogeneous luminance. For incremental targets, the gain decreased as an approximately linear function of the frame width. For decremental targets, the gain increased as an approximately linear function of the frame width. We modeled the brightness of the frame-embedded target with a quantitative theory based on the assumption that the target brightness is determined by the sum of achromatic color induction signals originating from the inner and outer edges of the surround, a theory that has previously been used to account for the results of several other brightness matching experiments. To account for the frame-width-dependent gain changes observed in the present study, we elaborate this edge integration theory by proposing the existence of a cortical contrast gain control mechanism by which the gains applied to neural edge detectors are influenced by the responses of other edge detectors responding to the nearby edges.

Effects of surround articulation on lightness depend on the spatial arrangement of the articulated region.

We investigated the effect of surround articulation on the perceived lightness of a target disk. Surround articulation was manipulated by varying either the number of wedges in a surround consisting of wedges of alternating luminance or the number of checks in a surround consisting of a radial checkerboard pattern. In most conditions, increased articulation caused incremental targets to appear lighter and decremental targets to appear darker. But increasing the surround articulation in a way that did not increase the number of target-coaligned edges in the display did not affect the target lightness. We propose that the effects of surround articulation depend on the relationship between the orientations and contrast polarities of the target edges and those of edges present within the surround.

Contrast polarity and edge integration in achromatic color perception.

Previous work has shown that the achromatic color of a target patch embedded in simple two-dimensional display depends not only on the luminance contrast between the target and its immediate surround but also on the contrasts of other nearby edges. Quantitative models have been proposed in which the target color is modeled as a spatially weighted sum of edge contrasts in which the target edge receives the largest weight. Rudd and Arrington [Vision Res.41, 3649 (2001)] elaborated on this idea to include an additional mechanism whereby effects of individual color-inducing edges are "partially blocked" by edges lying along the path between the inducing edge and the target. We tested the blockage model in appearance matching experiments performed with disk-and-single-ring stimuli having all four possible combinations of inner and outer ring edge contrast polarities. Evidence was obtained for both "blockage" (attenuation) and "antiblockage" (amplification) of achromatic color induction signals, depending on the contrast polarities of the inner and outer ring edges. A neural model is proposed to account for our data on the basis of the contrast gain control occurring between cortical edge detector neurons.

The highest luminance anchoring rule in achromatic color perception: some counterexamples and an alternative theory.

It has been hypothesized that lightness is computed in a series of stages involving: (1) extraction of local contrast or luminance ratios at borders; (2) edge integration, to combine contrast or luminance ratios across space; and (3) anchoring, to relate the relative lightness scale computed in Stage 2 to the scale of real-world reflectances. The results of several past experiments have been interpreted as supporting the highest luminance anchoring rule, which states that the highest luminance in a scene always appears white. We have previously proposed a quantitative model of achromatic color computation based on a distance-dependent edge integration mechanism. In the case of two disks surrounded by lower luminance rings, these two theories--highest luminance anchoring and distance--dependent edge integration-make different predictions regarding the luminance of a matching disk required to for an achromatic color match to a test disk of fixed luminance. The highest luminance rule predicts that luminance of the ring surrounding the test should make no difference, whereas the edge integration model predicts that increasing the surround luminance should reduce the luminance required for a match. The two theories were tested against one another in two experiments. The results of both experiments support the edge integration model over the highest luminance rule.

Quantitative properties of achromatic color induction: an edge integration analysis.

Edge integration refers to a hypothetical process by which the visual system combines information about the local contrast, or luminance ratios, at luminance borders within an image to compute a scale of relative reflectances for the regions between the borders. The results of three achromatic color matching experiments, in which a test and matching ring were surrounded by one or more rings of varying luminance, were analyzed in terms of three alternative quantitative edge integration models: (1) a generalized Retinex algorithm, in which achromatic color is computed from a weighted sum of log luminance ratios, with weights free to vary as a function of distance from the test (Weighted Log Luminance Ratio model); (2) an elaboration of the first model, in which the weights given to distant edges are reduced by a percentage that depends on the log luminance ratios of borders lying between the distant edges and the target (Weighted Log Luminance Ratio model with Blockage); and (3) an alternative modification of the first model, in which Michelson contrasts are substituted for log luminance ratios in the achromatic color computation (Weighted Michelson Contrast model). The experimental results support the Weighted Log Luminance Ratio model over the other two edge integration models. The Weighted Log Luminance Ratio model is also shown to provide a better fit to the achromatic color matching data than does Wallach's Ratio Rule, which states that the two disks will match in achromatic color when their respective disk/ring luminance ratios are equal.