A human extrastriate area functionally homologous to macaque V4

Extrastriate area V4 is crucial for intermediate form vision and visual attention in nonhuman primates. Human neuroimaging suggests that an area in the lingual sulcus/fusiform gyrus may correspond to ventral V4 (V4v). We studied a human neurological patient, AR, with a putative V4v lesion. The lesion does not affect early visual processing (luminance, orientation, and motion perception). However, it does impair hue perception, intermediate form vision, and visual attention in the upper contralateral visual field. Form deficits occur during discrimination of illusory borders, Glass patterns, curvature, and non-Cartesian patterns. Attention deficits occur during discrimination of the relative positions of object parts, detection of low-salience targets, and orientation discrimination in the presence of distractors. This pattern of deficits is consistent with the known properties of area V4 in nonhuman primates, indicating that AR's lesion affects a cortical region functionally homologous to macaque V4.     

Subjective figures and texture perception

A texture discrimination task using the Ehrenstein illusion demonstrates that subjective brightness effects can play an essential role in early vision. The subjectively bright regions of the Ehrenstein can be organized either as discs or as stripes, depending on orientation. The accuracy of discrimination between variants of the Ehrenstein and control patterns was a direct function of the presence of the illusory brightness stripes, being high when they were present and low otherwise. It is argued that neither receptive field structure nor spatial-frequency content can adequately account for these results. We suggest that the subjective brightness illusions, rather than being a high-level, cognitive aspect of vision, are in fact the result of an early visual process.     

Searching the protein structure databank with weak sequence patterns and structural constraints

A method is described in which proteins that match PROSITE patterns are filtered by the root-mean-square deviation of the local 3D structures of the probe and target over the pattern components. This was found to increase the discrimination between true and false members of the protein family but was dependent on how unique the structural features in the pattern were compared to equivalent fragments extracted from the structure databank (for example; if the pattern fell in an alpha-helix, then discrimination was poor.) We then generalised the sequence patterns (by widening the range of amino acid residues allowed at each position) and monitored how well the structural information helped retain specificity. While the discrimination of the pure sequence pattern had generally disappeared at information content values less than ten bits, the discrimination of the combined sequence structure probe remained high at this point before following a similar decay. The displacement between these curves indicates that the structural component is, on average, equivalent to about ten bits. The sequence patterns were also filtered using the structure comparison program SAP, giving a global, rather than local "view" of the proteins. This allowed the information content of the sequence patterns to become even less specific but raised problems of whether some proteins encountered with the same fold but no PROSITE pattern should constitute family members.     

Texture fields and texture flows: sensitivity to differences

There are two large classes of textures, those with an overall orientation structure (texture flows) and those without (texture fields). We investigate human sensitivity to detecting a patch of texture field within a texture flow psychophysically by using random not Moiré patterns. The resultant sensitivity, as a function of patch-size and path-length, is then related to a computational model of orientation selection, which reveals a connection between texture structure and the estimation of curvature. Finally, the connection back to curvature is confirmed by demonstrating a similarity between the patch sensitivity data and previous data on sensitivity to corners in flow patterns.     

The effect of complexity on the discrimination of oriented bars by the honeybee (<Emphasis Type="Italic">Apis mellifera</Emphasis>)

Visual discrimination of black bars by honeybees was studied in a Y-choice apparatus with fixed vertical patterns at constant range. The problem is to discover how bees remember different degrees of complexity of the orientation cue. Previous conclusions with parallel gratings and single bars disagree. With broad bars versus orthogonal bars, the bees learn the orientation cue if the bars are centred at the same place, but they learn the position cue in the vertical direction when the bars are at different places on the two targets. With several bars on each target, the bees learn their orientation and positions. As fixed patterns increase in complexity, the bees follow a simple rule, to look only at the range of places where the cues were displayed. The frame of reference is disrupted when a black spot is added to the training pattern. There is abundant evidence that the bees do not re-assemble the pattern or learn shapes. The filters that detect the position and orientation cues are coarsely tuned, so that they respond in a graded way, but the memory of the range of directions of the cue, as seen from the point of choice, is more exact.     

Symmetry: Modeling the Effects of Masking Noise,Axial Cueing and Salience

Symmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the prior information about the symmetry axis affects symmetry detection under noise-masking conditions. The target stimuli were random-dot displays structured to be symmetric about vertical, horizontal, or diagonal axes and viewed through eight apertures (1.2° diameter) evenly distributed around a 6° diameter circle. The information about axis orientation was manipulated by (1) cueing of axis orientation before the trial and (2) varying axis salience by including or excluding the axis region within the noise apertures. The percentage of correct detection of the symmetry was measured at for a range of both target and masking noise densities. The threshold vs. noise density function was flat at low noise density and increased with a slope of 0.75–0.8 beyond a critical density. Axis cueing reduced the target threshold 2–4fold at all noise densities while axis salience had an effect only at high noise density. Our results are inconsistent with an ideal observer or signal-to-noise account of symmetry detection but can be explained by a multiple-channel model is which the response in each channel is the ratio between the nonlinear transform of the responses of sets of early symmetry detectors and the sum of external and intrinsic sources of noise.     

Texture discrimination asymmetries across the visual field

Texture discrimination is sometimes asymmetrical; texture A embedded in texture B is more easily detected than texture B embedded in texture A. Furthermore, texture discrimination often improves as the disparate texture is moved into the periphery; this has been referred to as the central performance drop (CPD). The interaction of these interesting and counter-intuitive aspects of texture discrimination has received very little attention. Using four stimulus pattern pairs that were previously shown to elicit asymmetrical texture discrimination, we examined texture discrimination asymmetries as a function of eccentricity. We found three patterns of results; (i) both texture arrangements (A in B, and B in A) elicit a CPD but do not show an asymmetry, (ii) both texture arrangements elicit a monotonic decrease in performance with eccentricity (i.e. no CPD) but an asymmetry is seen at each eccentricity and (iii) discrimination asymmetries are minimal at fixation and in the far periphery and maximal about 3 degrees from fixation with a CPD generally shown for the 'stronger' member of the pair. These results emphasize that one cannot talk about the 'discriminability' of a particular texture pair without reference to the arrangement of the two textures and the eccentricity of presentation.     

Asymmetries in visual texture discrimination

Recent results have shown that texture discrimination is an asymmetrical process; texture A within texture B may be much easier to detect than texture B within texture A. Two questions regarding discrimination asymmetries are addressed: (i) what sorts of textural properties are associated with discrimination asymmetries; and (ii) what sort of architecture would yield asymmetries. Two experiments show that discrimination asymmetries obtain when textures comprise circles of different sizes (large circles are easier to detect in small than vice versa) and when circles differ only in the regularity of their placement (irregularly placed circles are easier to detect in a background of regularly placed circles than vice versa). A plausible account of texture discrimination would involve the decomposition of images via a set orientation and scale selective filters followed by a second layer of filtering to detect energy differences between adjacent regions in the original convolutions. Discrimination asymmetries provide prima facie evidence against such a model because it involves only local measurements and comparisons. We propose that discrimination asymmetries are elegantly explained if it is assumed that the responses of the orientation and scale selective filters are normalized by the degree to which similarly tuned operators are responding elsewhere in the image; viz., global normalization of filter responses. However, there are cases where such global normalization is not required to explain asymmetrical discrimination.     

Detection of irregular spatial structures

Wilson et al.'s (1997) study on Glass patterns suggested that the integration of stimulus features into a linear shape occurs quite locally, whereas curved structures--such as circular--require global summation. Their conclusion was based on experiments in which they varied the size of the signal area containing a spatial structure. In the present study, we tested the integration of constant-sized linear and curved Glass patterns by varying their global irregularity. If the mechanisms underlying the detection of a Glass pattern pool features globally throughout the stimulus, the irregularity should have a strong effect on detection performance. The irregular Glass patterns were composed of a variable number of sub-areas, each of which contained its own linear or curved structure. The structural irregularity impaired the detection of the curved patterns, whereas the thresholds for the linear patterns were not affected. Thus, our results are in line with the notion that the integration of curved Glass patterns occurs more globally than the integration of linear patterns.     

Effects of Texture Component Orientation on Orientation Flow Visibility for 3-D Shape Perception

In images of textured 3-D surfaces, orientation flows created by the texture components parallel to the surface slant play a critical role in conveying the surface slant and shape. This study examines the visibility of these orientation flows in complex patterns. Specifically, we examine the effect of orientation of neighboring texture components on orientation flow visibility. Complex plaids consisting of gratings equally spaced in orientation were mapped onto planar and curved surfaces. The visibility of the component that creates the orientation flows was quantified by measuring its contrast threshold (CT) while varying the combination of neighboring components present in the pattern. CTs were consistently lowest only when components closest in orientation to that of the orientation flows were subtracted from the pattern. This finding suggests that a previously reported frequency-selective cross-orientation suppression mechanism involved with the perception of 3-D shape from texture is affected by proximity in orientation of concurrent texture components.     

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.     

Some new phenomena in the perception of glass patterns

Glass patterns are dot pattern displays producing percepts of local orientation and global organization. Our observations suggest that the organizational principles involved in our perception of such patterns may be more consistent with a cortical simple-cell-like mechanisms (i.e., a king of neural summation within various feature maps) than with symbolic processing based on feature similarity.     

A computational model to link psychophysics and cortical cell activation patterns in human texture processing

The human visual system uses texture information to automatically, or pre-attentively, segregate parts of the visual scene. We investigate the neural substrate underlying human texture processing using a computational model that consists of a hierarchy of bi-directionally linked model areas. The model builds upon two key hypotheses, namely that (i) texture segregation is based on boundary detection--rather than clustering of homogeneous items--and (ii) texture boundaries are detected mainly on the basis of a large scenic context that is analyzed by higher cortical areas within the ventral visual pathway, such as area V4. Here, we focus on the interpretation of key results from psychophysical studies on human texture segmentation. In psychophysical studies, texture patterns were varied along several feature dimensions to systematically characterize human performance. We use simulations to demonstrate that the activation patterns of our model directly correlate with the psychophysical results. This allows us to identify the putative neural mechanisms and cortical key areas which underlie human behavior. In particular, we investigate (i) the effects of varying texture density on target saliency, and the impact of (ii) element alignment and (iii) orientation noise on the detectability of a pop-out bar. As a result, we demonstrate that the dependency of target saliency on texture density is linked to a putative receptive field organization of orientation-selective neurons in V4. The effect of texture element alignment is related to grouping mechanisms in early visual areas. Finally, the modulation of cell activity by feedback activation from higher model areas, interacting with mechanisms of intra-areal center-surround competition, is shown to result in the specific suppression of noise-related cell activities and to improve the overall model capabilities in texture segmentation. In particular, feedback interaction is crucial to raise the model performance to the level of human observers.     

A theory for the use of visual orientation information which exploits the columnar structure of striate cortex

A neural model is constructed based on the structure of a visual orientation hypercolumn in mammalian striate cortex. It is then assumed that the perceived orientation of visual contours is determined by the pattern of neuronal activity across orientation columns. Using statistical estimation theory, limits on the precision of orientation estimation and discrimination are calculated. These limits are functions of single unit response properties such as orientation tuning width, response amplitude and response variability, as well as the degree of organization in the neural network. It is shown that a network of modest size, consisting of broadly orientation selective units, can reliably discriminate orientation with a precision equivalent to human performance. Of the various network parameters, the discrimination threshold depends most critically on the number of cells in the hypercolumn. The form of the dependence on cell number correctly predicts the results of psychophysical studies of orientation discrimination. The model system's performance is also consistent with psychophysical data in two situations in which human performance is not optimal. First, interference with orientation discrimination occurs when multiple stimuli activate cells in the same hypercolumn. Second, systematic errors in the estimation of orientation can occur when a stimulus is composed of intersecting lines. The results demonstrate that it is possible to relate neural activity to visual performance by an examination of the pattern of activity across orientation columns. This provides support for the hypothesis that perceived orientation is determined by the distributed pattern of neural activity. The results also encourage the view of neural activity. The results also are determined by the responses of many neurons rather than the sensitivity of individual cells.     

Factors limiting peripheral pattern discrimination

Previous reports indicate that some foveally discriminable compound gratings are indiscriminable in peripheral vision, even when they are scaled by the ratio of peripheral to foveal grating acuity. To determine the stimulus properties that limit peripheral discrimination, we used Gaussian derivatives of various orders. These patterns are spatially localized and have intrinsic even or odd symmetry. Our results show that certain odd symmetric patterns are discriminable in the periphery, while others are not. Furthermore, certain even symmetric patterns are not peripherally discriminable. These data are consistent with three limitations on peripheral pattern discrimination: (1) Patterns that produce different maximum neural responses will be peripherally discriminable. (2) Positional uncertainty and undersampling degrade discrimination of high spatial frequency patterns in the periphery. (3) Patterns generating substantial neural activity within a constrained region are processed as textures in peripheral vision so that pattern details within that region are no longer available for discrimination. A neural model incorporating inhibition of simple cells by complex cells implements a transition between contour analysis and texture analysis in peripheral vision and explains the experimental data.     

Visual discrimination of simple geometrical patterns: I. Measurements for multiple element stimuli

We describe a method for the measurement of visual discrimination between simple patterns. The target to be discriminated is embedded in a background consisting of multiple, randomly positioned but identical elements, and is distinguished by a single parameter such as magnification or relative rotation. The positions of the target and background elements are varied randomly between presentations and discrimination for different values of the target parameter is measured in terms of the time taken for detection of the target. Using this method, we have studied discrimination of rotation and of magnification for simple pattern elements such as lines, triangles and squares. The results for rotation discrimination are interpreted as evidence for the activity of two discrimination mechanisms, one sensitive to the orientation of the lines from which the pattern elements are constructed and the other to the orientation of the pattern element relative to the visual field.     

Object detection by honeybees: Why do they land on edges?

Behavioural experiments using a variety of experimental situations (Figs. 1, 3, 6, 7, 9) were conducted to investigate the visual cues which bees use in the task of object-ground discrimination. The bees' flight and landing behaviour was video-filmed throughout the experiments. The evaluation of the video data shows that bees trained to find a randomly textured figure raised above a similarly textured ground land mainly on the boundaries of the figure, facing its inner surface (Fig. 2a, b). Bees can also be trained to find a hole, i.e. a low texture viewed through a window cut in a raised texture, but these bees are not attracted to the edges of the hole (Fig. 5a, b). Bees trained to a single edge between a low and a raised random texture land at the edge mainly facing the raised side (Table 1). Bees approaching the edge from the high side cross the edge in most cases without landing on it (Table 1). Bees trained to an edge between 2 striped patterns, one raised above the other, again land on the edge facing the raised pattern, regardless of whether the stripes on the 2 patterns run parallel or perpendicular to each other or to the edge (Fig. 8). In this case, the bees acquire range information by flying in oblique directions with respect to the orientation of the stripes (Fig. 10). All of the results suggest that the edge elicits landings when the bee perceives a local increase in the speed of image motion, signalling an abrupt decrease in range. This is corroborated by the results of further experiments in which artificial motion was used to simulate range differences between the two sides of an edge (Table 2). We conclude that image speed is a powerful cue in range discrimination as well as object detection. Dedicated to G. Adrian Horridge on the occasion of his retirement     

蝇视系统的图形—背景分辨和初级模式分辨

本文通过行为实验及计算机模拟进一步证明,蝇视系统的自发模式辨别可以看作是图形—背景分辨的特殊情况.关键在于蝇的模式分辨是由运动检测器实现的.运动检测器不仅对模式速度反应,也对模式的结构特性反应.本文提出,人视系统的模式分辨也可能部分地由运动检测器来实现.     

Population coding of stimulus orientation by striate cortical cells

I have examined the performance of a population coding model of visual orientation discrimination, similar to the population coding models proposed for the coding of limb movements. The orientation of the stimulus is not represented by a single unit but by an ensemble of broadly tuned units in a distributed way. Each unit is represented by a vector whose magnitude and direction correspond to the response magnitude and preferred orientation of the unit, respectively. The orientation of the population vector, i.e. the vector sum of the ensemble of units, is the signalled orientation on a particular trial. The accuracy of this population vector orientation coding was determined as a function of a number of parameters by computer simulation. I have shown that even with broadly orientation tuned units possessing considerable response variance, the accuracy of the orientation of the population vector can be as good as behaviorally measured just noticeable differences in orientation. The accuracy of the population code is shown to depend upon the number of units, the average response strength, the orientation bandwidth, response variability and the response covariance. The results of these simulations were also compared to predictions derived from psychophysical studies of orientation discrimination.