Surround masking reveals binocular adding and differencing channels.

Recent studies suggest that binocular adding S+ and differencing S- channels play an important role in binocular vision. To test for such a role in the context of binocular contrast detection and binocular summation, we employed a surround masking paradigm consisting of a central target disk surrounded by a mask annulus. All stimuli were horizontally oriented 0.5c/d sinusoidal gratings. Correlated stimuli were identical in interocular spatial phase while anticorrelated stimuli were opposite in interocular spatial phase. There were four target conditions: monocular left eye, monocular right eye, binocular correlated and binocular anticorrelated, and three surround mask conditions: no surround, binocularly correlated and binocularly anticorrelated. We observed consistent elevation of detection thresholds for monocular and binocular targets across the two binocular surround mask conditions. In addition, we found an interaction between the type of surround and the type of binocular target: both detection and summation were relatively enhanced by surround masks and targets with opposite interocular phase relationships and reduced by surround masks and targets with the same interocular phase relationships. The data were reasonably well accounted for by a model of binocular combination termed MAX (S+S-), in which the decision variable is the probability summation of modeled S+ and S- channel responses, with a free parameter determining the relative gains of the two channels. Our results support the existence of two channels involved in binocular combination, S+ and S-, whose relative gains are adjustable by surround context.

A visual bias for falling objects.

Aristotle believed that objects fell at a constant velocity. However, Galileo Galilei showed that when an object falls, gravity causes it to accelerate. Regardless, Aristotle's claim raises the possibility that people's visual perception of falling motion might be biased away from acceleration towards constant velocity. We tested this idea by requiring participants to judge whether a ball moving in a simulated naturalistic setting appeared to accelerate or decelerate as a function of its motion direction and the amount of acceleration/deceleration. We found that the point of subjective constant velocity (PSCV) differed between up and down but not between left and right motion directions. The PSCV difference between up and down indicated that more acceleration was needed for a downward-falling object to appear at constant velocity than for an upward "falling" object. We found no significant differences in sensitivity to acceleration for the different motion directions. Generalized linear mixed modeling determined that participants relied predominantly on acceleration when making these judgments. Our results support the idea that Aristotle's belief may in part be due to a bias that reduces the perceived magnitude of acceleration for falling objects, a bias not revealed in previous studies of the perception of visual motion.

Detection of vertical interocular phase disparities using luster as cue.

Interocular disparities in contrast generate an impression of binocular luster, providing a cue for their detection. Disparities in the carrier spatial phase of horizontally oriented Gabor patches also generate an impression of luster, so the question arises as to whether it is the disparities in local contrast that accompany the phase disparities that give rise to the luster. We examined this idea by comparing the detection of interocular spatial phase disparities with that of interocular contrast disparities in Gabor patches, in the latter case that differed in overall contrast rather than phase between the eyes. When bandwidth was held constant and Gabor spatial frequency was varied, the detection of phase and contrast disparities followed a similar pattern. However, when spatial frequency was fixed and Gabor envelope standard deviation (and hence number of modulation cycles) was varied, thresholds for detecting phase disparities followed a U-shaped function of Gabor standard deviation, whereas thresholds for contrast disparities, following an initial decline, were more-or-less constant as a function of Gabor standard deviation. After reviewing a number of possible explanations for the U-shape found with phase disparities, we suggest that the likely cause is binocular sensory fusion, the strength of which increases with the number of modulation cycles. Binocular sensory fusion would operate to reduce phase but not contrast disparities, thus selectively elevating phase disparity thresholds.

Different symmetries, different mechanisms.

Three common symmetries exist in the natural visual world: (i) mirror symmetry, i.e., reflections around a vertical axis, (ii) radial symmetry, i.e., rotations around a point, and (iii) translational symmetry, i.e., shifted repetitions. Are these processed by a common class of visual mechanism? Using stimuli comprising arrays of Gaussian blobs we examined this question using a visual search protocol in which observers located a single symmetric target patch among varying numbers of random-blob distractor patches. The testing protocol used a blocked present/absent task and both search times and accuracy were recorded. Search times for mirror and radial symmetry increased significantly with the number of distractors, as did translational-symmetry patterns containing few repetitions. However translational-symmetry patterns with four repeating sectors produced search slopes close to zero. Fourier analysis revealed that, as with images of natural scenes, the structural information in both mirror- and radial-symmetric patterns is carried by the phase spectrum. However, for translational patterns with four repeating sectors, the amplitude spectrum appears to capture the structure, consistent with previous analyses of texture regularity. Modeling revealed that while the mirror and radial patterns produced an approximately Gaussian-shaped energy response profile as a function of spatial frequency, the translational pattern profiles contained a distinctive spike, the magnitude of which increased with the number of repeating sectors. We propose distinct mechanisms for the detection of different symmetry types: a mechanism that encodes local positional information to detect mirror- and radial-symmetric patterns and a mechanism that computes energy in narrowband filters for the detection of translational symmetry containing many sectors.

Small-angle attraction in the tilt illusion.

The tilt illusion (TI) describes the phenomenon in which a surround inducer grating of a particular orientation influences the perceived orientation of a central test grating. Typically, inducer-test orientation differences of 5 to 40 degrees cause the test orientation to appear shifted away from the inducer orientation (i.e. repulsion). For orientation differences of 60 to 90 degrees, the inducer typically causes the test grating orientation to appear shifted toward the inducer orientation, termed here "large-angle" attraction. Both repulsion and large-angle attraction effects have been observed in contrast-modulated as well as luminance-modulated grating patterns. Here, we show that a secondary, "small-angle" 0 to 10 degrees attraction effect is observed in contrast-modulated and orientation-modulated gratings, as well as in luminance-modulated gratings that are relatively low in spatial frequency, low in contrast, or contain added texture. The observed small-angle attraction, which can exceed in magnitude that of the repulsion and large-angle attraction effects, is dependent on the spatial phase relationship between the inducer and test, being maximal when in-phase. Both small-angle attraction and repulsion effects are reduced when a gap is introduced between the test and inducer. Our findings suggest that small-angle attraction in the TI is a result of assimilation of the inducer pattern into the receptive fields of neurons sensitive to the test.

Visual perception of texture regularity: Conjoint measurements and a wavelet response-distribution model.

Texture regularity, such as the repeating pattern in a carpet, brickwork or tree bark, is a ubiquitous feature of the visual world. The perception of regularity has generally been studied using multi-element textures in which the degree of regularity has been manipulated by adding random jitter to the elements' positions. Here we used three-factor Maximum Likelihood Conjoint Measurement (MLCM) for the first time to investigate the encoding of regularity information under more complex conditions in which element spacing and size, in addition to positional jitter, were manipulated. Human observers were presented with large numbers of pairs of multi-element stimuli with varying levels of the three factors, and indicated on each trial which stimulus appeared more regular. All three factors contributed to regularity perception. Jitter, as expected, strongly affected regularity perception. This effect of jitter on regularity perception is strongest at small element spacing and large texture element size, suggesting that the visual system utilizes the edge-to-edge distance between elements as the basis for regularity judgments. We then examined how the responses of a bank of Gabor wavelet spatial filters might account for our results. Our analysis indicates that the peakedness of the spatial frequency (SF) distribution, a previously favored proposal, is insufficient for regularity encoding since it varied more with element spacing and size than with jitter. Instead, our results support the idea that the visual system may extract texture regularity information from the moments of the SF-distribution across orientation. In our best-performing model, the variance of SF-distribution skew across orientations can explain 70% of the variance of estimated texture regularity from our data, suggesting that it could provide a candidate read-out for perceived regularity.

Binocular summation and efficient coding.

Two eyes are better than one at detecting a pattern, an advantage termed binocular summation. It is widely believed that binocular summation is mediated by neurons that sum the two eyes' inputs. Here we suggest an alternative model based on a model of binocular interactions proposed by Cohn, Leong & Lasley (Vision Research, 1981, 21, 1017-1023) and further motivated by the efficient coding framework proposed by Li & Atick (Network: Computation in Neural Systems, 1994, 5, 157-174). In the model, termed MAX(S+S-), binocular summation is mediated by channels that compute the sum, S+, and difference, S-, of the two eyes' monocular signals. The S+ and S- signals are assumed to be perturbed by independent noise, have independent gains and contribute independently to detection via the MAX rule. To test the model we measured binocular summation for horizontally-oriented Gabor patches at a range of spatial-frequencies and bandwidths, at both contrast detection threshold and for increment thresholds on binocular pedestals at contrasts set to 10x detection threshold. The model's performance was compared to that of two conventional models of binocular summation, one in which the two eyes' signals remain separate at the decision stage, termed MAX(LR), the other in which the two eye's signals are summed by a single channel, termed B+, with both models incorporating interocular inhibition. The MAX(S+S-) model gave as good a performance as the other two models. Together with the evidence for the involvement of separately gain controlled S+ and S- signals underpinning a wide range of binocular behaviors, we conclude that the MAX(S+S-) model can and should be considered as a viable model for binocular summation.

Negative afterimages facilitate the detection of real images.

Negative, or complementary afterimages are experienced following brief adaptation to chromatic or achromatic stimuli, and are believed to be formed in the post-receptoral layers of the retinae. Afterimages can be cancelled by the addition of real images, suggesting that afterimages and real images are processed by similar mechanisms. However given their retinal origin, afterimage signals represented at the cortical level might have different spatio-temporal properties from their real images counterparts. To test this we determined whether afterimages reduce the contrast threshold of added real images, i.e. produce the classic "dipper" function characteristic of contrast discrimination, a behavior believed to be cortically mediated. Stimuli were chromatic and achromatic disks on a grey background. Observers adapted for 1.0 s to two side-by-side disks of a particular color. Following stimulus offset, a test disk added to one side was ramped downwards for 1.5 s to approximately match the temporal characteristic of the afterimage, and the observer was required to indicate the side containing the test disk. The test hue/brightness was either the same as that of the afterimage or a different hue/brightness. The independent variable was the contrast of the adaptor. A dipper followed by masking was observed in most conditions in which the afterimage and test colors had the same hue or brightness. We conclude that afterimages are represented similarly to their real image counterparts at the cortical level.

Stereoscopic depth adaptation from binocularly correlated versus anti-correlated noise: Test of an efficient coding theory of stereopsis.

Stereoscopic, or "3D" vision in humans is mediated by neurons sensitive to the disparities in the positions of objects in the two eyes' views. A disparity-sensitive neuron is typically characterized by its responses to left- and right-eye monocular signals, SL and SR, respectively. However, it can alternatively be characterized by sensitivity to the sum of the two eyes' inputs, S+ = SL + SR, and the difference, S- = SL - SR. Li and Atick's theory of efficient binocular encoding proposes that the S+ and S- signals can be separately weighted to maximize the efficiency with which binocular information is encoded. This adaptation changes each neuron's sensitivity and preferred binocular disparity, resulting in predicted effects on the perceived stereoscopic depth of objects. To test these predictions, we measured the apparent depth of a random-dot stereogram with an 'in-front' target following adaptation to binocularly correlated or anti-correlated horizontally-oriented grating stimuli, which reduce sensitivity to the S+ and S- signals, respectively, but which contain no conventional stereo-depth signals. The anti-correlated noise adaptation made the target appear relatively closer to the background than the correlated noise adaptation, with differences of up to 60%. We show how this finding can be accommodated by a standard model of binocular disparity processing, modified to incorporate the binocular adaptation suggested by Li and Atick's theory.

Interocular difference thresholds are mediated by binocular differencing, not summing, channels.

Patterns in the two eyes' views that are not identical in hue or contrast often elicit an impression of luster, providing a cue for discriminating them from perfectly matched patterns. Here we attempt to determine the mechanisms for detecting interocular differences in luminance contrast, in particular in relation to the possible contributions of binocular differencing and binocular summing channels. Test patterns were horizontally oriented multi-spatial-frequency luminance-grating patterns subject to variable amounts of interocular difference in grating phase, resulting in varying degrees of local interocular contrast difference. Two types of experiment were conducted. In the first, subjects discriminated between a pedestal with an interocular difference that ranged upward from zero (i.e., binocularly correlated) and a test pattern that contained a bigger interocular difference. In the second type of experiment, subjects discriminated between a pedestal with an interocular difference that ranged downward from a maximum (i.e., binocularly anticorrelated) and a test pattern that contained smaller interocular difference. The two types of task could be mediated by a binocular differencing and a binocular summing channel, respectively. However, we found that the results from both experiments were well described by a simpler model in which a single, linear binocular differencing channel is followed by a standard nonlinear transducer that is expansive for small signals but strongly compressive for large ones. Possible reasons for the lack of involvement of a binocular summing channel are discussed in the context of a model that incorporates the responses of both monocular and binocular channels.

Luminance-contrast properties of texture-shape and texture-surround suppression of contour shape.

Studies have revealed that textures suppress the processing of the shapes of contours they surround. One manifestation of texture-surround suppression is the reduction in the magnitude of adaptation-induced contour-shape aftereffects when the adaptor contour is surrounded by a texture. Here we utilize this phenomenon to investigate the nature of the first-order inputs to texture-surround suppression of contour shape by examining its selectivity to luminance polarity and the magnitude of luminance contrast. Stimuli were constructed from sinusoidal-shaped strings of either "bright" or "dark" elongated Gaussians. Observers adapted to pairs of contours, and the aftereffect was measured as the shift in the apparent shape frequency of subsequently presented test contours. We found that the suppression of the contour-shape aftereffect by a surround texture made of similar contours was maximal when the adaptor's center and surround contours were of the same polarity, revealing polarity specificity of the surround-suppression effect. We also measured the effect of varying the relative contrasts of the adaptor's center and surround and found that the reduction in the contour-shape aftereffect was determined by the surround-to-center contrast ratio. Finally, we measured the selectivity to luminance polarity of the texture-shape aftereffect itself and found that it was reduced when the adaptors and tests were of opposite luminance polarity. We conclude that texture-surround suppression of contour-shape as well as texture-shape processing itself depend on "on-off" luminance-polarity channel interactions. These selectivities may constitute an important neural substrate underlying efficient figure-ground segregation and image segmentation.

Color improves edge classification in human vision.

Despite the complexity of the visual world, humans rarely confuse variations in illumination, for example shadows, from variations in material properties, such as paint or stain. This ability to distinguish illumination from material edges is crucial for determining the spatial layout of objects and surfaces in natural scenes. In this study, we explore the role that color (chromatic) cues play in edge classification. We conducted a psychophysical experiment that required subjects to classify edges into illumination and material, in patches taken from images of natural scenes that either contained or did not contain color information. The edge images were of various sizes and were pre-classified into illumination and material, based on inspection of the edge in the context of the whole image from which the edge was extracted. Edge classification performance was found to be superior for the color compared to grayscale images, in keeping with color acting as a cue for edge classification. We defined machine observers sensitive to simple image properties and found that they too classified the edges better with color information, although they failed to capture the effect of image size observed in the psychophysical experiment. Our findings are consistent with previous work suggesting that color information facilitates the identification of material properties, transparency, shadows and the perception of shape-from-shading.

The Pupillary Response to the Unknown: Novelty Versus Familiarity.

Object recognition is a type of perception that enables observers to recognize familiar shapes and categorize them into real-world identities. In this preregistered study, we aimed to determine whether pupil size changes occur during the perception and recognition of identifiable objects. We compared pupil size changes for familiar objects, nonobjects, and random noise. Nonobjects and noise produced greater pupil dilation than familiar objects. Contrary to previous evidence showing greater pupil dilation to stimuli with more perceptual and affective content, these results indicate a greater pupil dilation to stimuli that are unidentifiable. This is consistent with the relative salience of novelty compared to familiarity at the physiological level driving the pupil response.

Unmasking the dichoptic mask.

Previously, it has been shown that dichoptic color-contrast masking can be dramatically reduced by the introduction of task-irrelevant binocular features. It is unclear, however, whether or not the task-irrelevant features need to be matched in the two eyes in order to reduce dichoptic masking. We measured dichoptic masking between target and mask luminance decrement patches and between target and mask isoluminant violet patches. The stimuli were surrounded by a task-irrelevant feature that consisted of a ring of various widths: either a luminance decrement, an isoluminant violet, or an isoluminant red. When the ring was presented to just the target eye-that is, the eye opposite to that of the mask-dichoptic masking was reduced just as much as when the ring was binocular-that is, presented to both eyes. A model that incorporated the combined influence of interocular inhibition from all stimulus components-that is, mask, target, and rings-was found to give a good account of the pattern of dichoptic masking across the full range of conditions.

The processing of compound radial frequency patterns.

Radial frequency (RF) patterns can be combined to construct complex shapes. Previous studies have suggested that such complex shapes may be encoded by multiple, narrowly-tuned RF shape channels. To test this hypothesis, thresholds were measured for detection and discrimination of various combinations of two RF components. Results show evidence of summation: sensitivity for the compounds was better than that for the components, with little effect of the components' relative phase. If both RF components are processed separately at the point of detection, they would combine by probability summation (PS), resulting in only a small increase in sensitivity for the compound compared to the components. Summation exceeding the prediction of PS suggests a form of additive summation (AS) by a common mechanism. Data were compared to predictions of winner-take-all, where only the strongest component contributes to detection, a single channel AS model, and multi-channel PS and AS models. The multi-channel PS and AS models were modelled under both Fixed and Matched Attention Window scenarios, the former assuming a single internal noise source for both components and compounds or different internal noise sources for components and compounds respectively. The winner-take-all and single channel models could be rejected. Of the remaining models, the best performing one was an AS model with a Fixed Attention Window, consistent with detection being mediated by channels that are efficiently combined and limited by a single source of noise for both components and compounds.

Perceived regularity of a texture is influenced by the regularity of a surrounding texture.

Previous studies have shown that texture regularity is adaptable, and have suggested that texture regularity might be coded by the peakedness of the underlying spatial frequency distribution. Here we demonstrate the related phenomenon of simultaneous regularity contrast (SRC), in which the perceived regularity of a central texture is influenced by the regularity of a surrounding texture. We presented center-surround arrangements of textures and measured the perceived regularity of the centre, using a centre-only comparison stimulus and a 2AFC procedure. From the resulting psychometric functions the SRC was measured as the difference between test and comparison regularity at the PSE (point of subjective equality). Observers generally exhibited asymmetric bidirectional SRC, in that more regular surrounds decreased the perceived regularity of the centre by between 20-40%, while less regular surrounds increased the perceived regularity of the centre by about 10%. Consistent with previous studies, a wavelet spatial frequency (SF) analysis of the stimuli revealed that their SF distributions became sharper with increased regularity, and therefore that distribution statistics such as kurtosis and SF bandwidth might be used to code regularity.

Co-circularity opponency in visual texture.

It is well known that the human visual system is sensitive to co-circularity among oriented edges, which are ubiquitous features of object contours. Here, we report a novel aftereffect in which the appearance of a texture is dramatically altered after adaptation to a texture composed of elements with co-circular structure. Following prolonged viewing of a texture made of pairs of adjacent Gabor elements arranged to form obtuse angle co-circular pairs, i.e. shallow curves, a subsequently viewed random texture appears to be composed of acute angle, i.e. near-parallel pairs. Conversely, adaptation to a texture made of parallel pairs causes a random texture to appear to be composed of shallow curves. This suggests that mechanisms sensitive to co-circularity are organized in an opponent manner, with one pole sensitive to shallow curves the other parallel shapes. This notion was tested further in a non-adaptation experiment in which co-circular and non-co-circular Gabor pairs were mixed within a single texture. Results revealed summation between pairs that fell on one side of the opponent continuum, and cancellation between pairs that fell on opposite sides of the continuum. Taken together these results support opponent interactions between mechanisms sensitive to pairwise co-circular texture features.

Applying the Model-Comparison Approach to Test Specific Research Hypotheses in Psychophysical Research Using the Palamedes Toolbox.

In the social sciences it is common practice to test specific theoretically motivated research hypotheses using formal statistical procedures. Typically, students in these disciplines are trained in such methods starting at an early stage in their academic tenure. On the other hand, in psychophysical research, where parameter estimates are generally obtained using a maximum-likelihood (ML) criterion and data do not lend themselves well to the least-squares methods taught in introductory courses, it is relatively uncommon to see formal model comparisons performed. Rather, it is common practice to estimate the parameters of interest (e.g., detection thresholds) and their standard errors individually across the different experimental conditions and to 'eyeball' whether the observed pattern of parameter estimates supports or contradicts some proposed hypothesis. We believe that this is at least in part due to a lack of training in the proper methodology as well as a lack of available software to perform such model comparisons when ML estimators are used. We introduce here a relatively new toolbox of Matlab routines called Palamedes which allows users to perform sophisticated model comparisons. In Palamedes, we implement the model-comparison approach to hypothesis testing. This approach allows researchers considerable flexibility in targeting specific research hypotheses. We discuss in a non-technical manner how this method can be used to perform statistical model comparisons when ML estimators are used. With Palamedes we hope to make sophisticated statistical model comparisons available to researchers who may not have the statistical background or the programming skills to perform such model comparisons from scratch. Note that while Palamedes is specifically geared toward psychophysical data, the core ideas behind the model-comparison approach that our paper discusses generalize to any field in which statistical hypotheses are tested.

Simultaneous density contrast and binocular integration.

Most research on texture density has utilized textures rendered as two-dimensional (2D) planar surfaces, consistent with the conventional definition of density as the number of texture elements per unit area. How the brain represents texture density information in the three-dimensional (3D) world is not yet clear. Here we tested whether binocular information affects density processing using simultaneous density contrast (SDC), in which the perceived density of a texture region is changed by a surround of different density. We considered the effect on SDC of two types of binocular information: the stereoscopic depth relationships and the interocular relationships between the center and surround textures. Observers compared the perceived density of two random dot patterns, one with a surround (test stimulus) and one without (match), using a 2AFC staircase procedure. In Experiment 1 we manipulated the stereo-depth of the surround plane systematically from near to far, relative to the center plane. SDC was reduced when the difference in stereo-depth between test center and surround increased. In Experiment 2 we spread the surround dots randomly across a stereo-depth volume from small to large volume sizes, and found that SDC was slightly reduced with volume size. The decrease of SDC in both experiments was observed with dense surrounds only, but not with sparse surrounds. In the last experiment we presented center and surround in the same depth plane but dichopticly, monopticly, and binocularly. A strong interocular transfer of SDC was found in the dichoptic condition. Together these results show that texture density processing is sensitive to binocularity.