Effect of exposure duration,contrast and base blur on coding and discrimination of edges

We extend a neural network model, developed to examine neural correlates for the dynamic synthesis of edges from luminance gradients (O?men, 1993), to account for the effects of exposure duration, base blur and contrast on the perceived sharpness of edges. This model of REtino-COrtical Dynamics (RECOD) predicts that (i) a decrease in exposure duration causes an increase in the perceived blur and the blur discrimination threshold for edges, (ii) this increase in perceived blur is more pronounced for sharper edges than for blurred edges, (iii) perceived blur is independent of contrast while the blur discrimination threshold decreases with contrast, (iv) perceived blur increases with increasing base blur while the blur discrimination threshold has a nonmonotonic U-shaped dependence on base blur, (v) the perceived location of an edge shifts progressively towards the low-luminance side of the edge with increasing contrast, and (vi) perceived contrast of suprathreshold stimuli is essentially independent of spatial frequency over a wide range of contrast values. These predictions are shown to be in quantitative agreement with existing psychophysical data from the literature and with data collected on three observers to quantify the effect of exposure duration on perceived blur.     

Implementation of the template model of vision

Adopting principles learnt from insect vision we have constructed model of a general-purpose front-end visual system for motion detection that is designed to operate in parallel along each photoreceptor axis with only local connections. The model is also designed to assist electrophysiological analysis of visual processing because it puts the response to a moving scene into sets of template responses similar to the distribution of activity among different neurons. An earlier template model divided the visual image into the fields of adjacent receptors, measured as intensity or receptor modulation at small increments of time. As soon as we used this model with natural scenes, however, we found that we had to look at changes in intensity, not intensity itself. Running the new model also generated new insights into the effects of very fast motion, of blurring the image, and the value of lateral inhibition. We also experimented with ways of measuring the angular velocity of the image moving across the eye. The camera eye is moved at a known speed and the range to objects is calculated from the angular velocity of contrasts moving across the receptor array. The original template model is modified so that contrast is saturated in a new representation of the original image data. This reduces the 8-bit grey-scale image to a log, 3 = 1.6-bit image, which becomes the input to a look-up table of templates. The output consists of groups of responding templates in specific ratios that define the input features, and these ratios lead into types of invariance at a higher level of further logic. At any stage, there can be persistent parallel inputs from all earlier stages. This design would enable groups of templates to be tuned to different expected situations, such as different velocities, different directions and different types of edges.     

二阶运动条件下闪现滞后现象的研究

闪现滞后现象(flash—lag effect)是指运动物体旁闪现的物体在知觉中物体落后于运动物体的现象。对这个现象,有一种解释认为视网膜上对运动刺激的外推机制对闪现滞后现象有相当的贡献．用视网膜外推机制不再有效的二阶运动刺激取代前人实验中的一阶运动刺激来研究闪现滞后现象,发现在视网膜推断机制失效的情况下,闪现滞后现象并没有减小,而是和一阶运动刺激条件下的量相当。结果表明,视网膜上的加工机制并不是闪现滞后现象的主要原因,并提示闪现滞后现象的机制可能位于一、二阶运动加工通道的汇合阶段以上。     

Static antennae act as locomotory guides that compensate for visual motion blur in a diurnal,keen-eyed predator

High visual acuity allows parallel processing of distant environmental features, but only when photons are abundant enough. Diurnal tiger beetles (Carabidae: Cicindelinae) have acute vision for insects and visually pursue prey in open, flat habitats. Their fast running speed causes motion blur that degrades visual contrast, forces stop-and-go pursuit and potentially impairs obstacle detection. We demonstrate here that vision is insufficient for obstacle detection during running, and show instead that antennal touch is both necessary and sufficient for obstacle detection. While running, tiger beetle vision appears to be photon-limited in a way reminiscent of animals in low-light habitats. Such animals often acquire wide-field spatial information through mechanosensation mediated by longer, more mobile appendages. We show that a nocturnal tiger beetle species waves its antennae in elliptical patterns typical of poorly sighted insects. While antennae of diurnal species are also used for mechanosensation, they are rigidly held forward with the tips close to the substrate. This enables timely detection of path obstructions followed by an increase in body pitch to avoid collision. Our results demonstrate adaptive mechanosensory augmentation of blurred visual information during fast locomotion, and suggest that future studies may reveal non-visual sensory compensation in other fast-moving animals.     

Electron Density Sharpening as a General Technique in Crystallographic Studies

Sharpening is a powerful method to restore the details from blurred electron density in crystals with high overall temperature factors (B-factors). This valuable technique is currently not optimally used because of the uncertainty in the scope of its application and ambiguities in practice. We performed an analysis of ~ 2000 crystal data sets deposited in the Protein Data Bank and show that sharpening improves the electron density map in many cases across all resolution ranges, often with dramatic enhancement for mid- and low-resolution structures. It is effective when used with either experimental or model phases without introducing additional bias. Our tests also provide a practical guide for optimal sharpening. We further show that anisotropic diffraction correction improves electron density in many cases but should be used with caution. Our study demonstrates that a routine practice of electron density sharpening may have a broad impact on the outcomes of structural biology studies.     

Prediction of a moving target's position in fast goal-directed action

 Subjects made fast goal-directed arm movements towards moving targets. In some cases, the perceived direction of target motion was manipulated by moving the background. By comparing the trajectories towards moving targets with those towards static targets, we determined the position towards which subjects were aiming at movement onset. We showed that this position was an extrapolation in the target’s perceived direction from its position at that moment using its perceived direction of motion. If subjects were to continue to extrapolate in the perceived direction of target motion from the position at which they perceive the target at each instant, the error would decrease during the movements. By analysing the differences between subjects’ arm movements towards targets moving in different (apparent) directions with a linear second-order model, we show that the reduction in the error that this predicts is not enough to explain how subjects compensate for their initial misjudgements. Received: 10 February 1995/Accepted in revised form: 30 May 1995     

Cuttlefish camouflage: context-dependent body pattern use during motion

It is virtually impossible to camouflage a moving target against a non-uniform background, but strategies have been proposed to reduce detection and targeting of movement. Best known is the idea that high contrast markings produce ‘motion dazzle’, which impairs judgement of speed and trajectory. The ability of the cuttlefish Sepia officinalis to change its visual appearance allows us to compare the animal''s choice of patterns during movement to the predictions of models of motion camouflage. We compare cuttlefish body patterns used during movement with those expressed when static on two background types; one of which promotes low-contrast mottle patterns and the other promotes high-contrast disruptive patterns. We find that the body pattern used during motion is context-specific and that high-contrast body pattern components are significantly reduced during movement. Thus, in our experimental conditions, cuttlefish do not use high contrast motion dazzle. It may be that, in addition to being inherently conspicuous during movement, moving high-contrast patterns will attract attention because moving particles in coastal waters tend to be of small size and of low relative contrast.     

The evolution of patterning during movement in a large-scale citizen science game

The motion dazzle hypothesis posits that high contrast geometric patterns can cause difficulties in tracking a moving target and has been argued to explain the patterning of animals such as zebras. Research to date has only tested a small number of patterns, offering equivocal support for the hypothesis. Here, we take a genetic programming approach to allow patterns to evolve based on their fitness (time taken to capture) and thus find the optimal strategy for providing protection when moving. Our ‘Dazzle Bug’ citizen science game tested over 1.5 million targets in a touch screen game at a popular visitor attraction. Surprisingly, we found that targets lost pattern elements during evolution and became closely background matching. Modelling results suggested that targets with lower motion energy were harder to catch. Our results indicate that low contrast, featureless targets offer the greatest protection against capture when in motion, challenging the motion dazzle hypothesis.     

A linear model for symmetric receptive fields: implications for classification tests with flashed and moving images

The purpose of this study was to explore the effects of spatial and temporal properties on the expected responses of visual neurons that have linear receptive fields (RFs), particularly those having a mirror symmetric distribution of spatial subregions. Receptive fields that are symmetric in at least one spatial dimension occur in neurons of the retina, the lateral geniculate nucleus (LGN), and the visual cortex of mammals. Responses to flashing bars, moving bars, and moving edges were studied for different configurations of an analog RF model in which spatial and temporal aspects were varied independently. Responses of the model at intermediate stimulus speeds were found to agree with responses in the literature for X and Y units of the LGN and often for simple units of the visual cortex. In particular, having separated regions of response to light and dark edges, an identifying property of simple cells, was found to be a linear consequence of RF regions responding inversely to stimuli of opposite polarity. Model differences from responses of cortical complex units show that a linear model cannot mimic their responses, and imply that complex units employ major nonlinearities in coding image polarity (light vs dark), which signifies a nonlinearity in coding intensity. Because sudden flux changes inherent in flashing bars test mainly temporal RF properties, and slowly moving edges test mainly spatial properties, these two tests form a useful minimal set with which to describe and classify RFs. The usefulness of this set derives both from its sensitivity to spatial and temporal variables, and from the correlation between the linearity of a cell's processing of stimulus intensity and its RF classification.     

Insect detection of small targets moving in visual clutter

Detection of targets that move within visual clutter is a common task for animals searching for prey or conspecifics, a task made even more difficult when a moving pursuer needs to analyze targets against the motion of background texture (clutter). Despite the limited optical acuity of the compound eye of insects, this challenging task seems to have been solved by their tiny visual system. Here we describe neurons found in the male hoverfly,Eristalis tenax, that respond selectively to small moving targets. Although many of these target neurons are inhibited by the motion of a background pattern, others respond to target motion within the receptive field under a surprisingly large range of background motion stimuli. Some neurons respond whether or not there is a speed differential between target and background. Analysis of responses to very small targets (smaller than the size of the visual field of single photoreceptors) or those targets with reduced contrast shows that these neurons have extraordinarily high contrast sensitivity. Our data suggest that rejection of background motion may result from extreme selectivity for small targets contrasting against local patches of the background, combined with this high sensitivity, such that background patterns rarely contain features that satisfactorily drive the neuron.     

Contrast dependence of smooth pursuit eye movements following a saccade to superimposed targets

Dorsal stream areas provide motion information used by the oculomotor system to generate pursuit eye movements. Neurons in these areas saturate at low levels of luminance contrast. We therefore hypothesized that during the early phase of pursuit, eye velocity would exhibit an oculomotor gain function that saturates at low luminance contrast. To test this, we recorded eye movements in two macaques trained to saccade to an aperture in which a pattern of dots moved left or right. Shortly after the end of the saccade, the eyes followed the direction of motion with an oculomotor gain that increased with contrast before saturating. The addition of a second pattern of dots, moving in the opposite direction and superimposed on the first, resulted in a rightward shift of the contrast-dependent oculomotor gain function. The magnitude of this shift increased with the contrast of the second pattern of dots. Motion was nulled when the two patterns were equal in contrast. Next, we varied contrast over time. Contrast differences that disappeared before saccade onset biased post-saccadic eye movements at short latency. Changes in contrast occurring during or after saccade termination did not influence eye movements for approximately 150 ms. Earlier studies found that eye movements can be explained by a vector average computation when both targets are equal in contrast. We suggest that this averaging computation may reflect a special case of divisive normalization, yielding saturating contrast response functions that shift to the right with opposed motion, averaging motions when targets are equated in contrast.     

A model for the detection of moving targets in visual clutter inspired by insect physiology

We present a computational model for target discrimination based on intracellular recordings from neurons in the fly visual system. Determining how insects detect and track small moving features, often against cluttered moving backgrounds, is an intriguing challenge, both from a physiological and a computational perspective. Previous research has characterized higher-order neurons within the fly brain, known as 'small target motion detectors' (STMD), that respond robustly to moving features, even when the velocity of the target is matched to the background (i.e. with no relative motion cues). We recorded from intermediate-order neurons in the fly visual system that are well suited as a component along the target detection pathway. This full-wave rectifying, transient cell (RTC) reveals independent adaptation to luminance changes of opposite signs (suggesting separate ON and OFF channels) and fast adaptive temporal mechanisms, similar to other cell types previously described. From this physiological data we have created a numerical model for target discrimination. This model includes nonlinear filtering based on the fly optics, the photoreceptors, the 1(st) order interneurons (Large Monopolar Cells), and the newly derived parameters for the RTC. We show that our RTC-based target detection model is well matched to properties described for the STMDs, such as contrast sensitivity, height tuning and velocity tuning. The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear 'matched filter' to successfully detect most targets from the background. Importantly, this model can explain this type of feature discrimination without the need for relative motion cues.     

Lower visual field advantage for motion segmentation during high competition for selection

A series of visual enumeration tasks were conducted investigating the role of the dorsal visual stream in motion segmentation. Cortical areas representing the lower visual field have greater connections with the parietal cortex and should therefore show an advantage for processes driven by the dorsal stream (Previc, 1990). We looked for differences in processing displays in the upper versus lower visual field when targets required segmentation from distractors in an enumeration task. In a baseline condition, random configurations of moving and static items were presented briefly (200 ms) to the upper or lower visual field. Fast and efficient enumeration took place both for moving targets and for static targets presented alone; there was no effect of visual field. In contrast, for moving targets, a lower visual field advantage was found when the inclusion of static distractors demanded segmentation by motion. This disappeared at the smaller display sizes when the targets were presented in canonical patterns. The results are consistent with segmentation of moving targets from static distractors being mediated by dorsal regions of the visual cortex, particularly under conditions of high load (non-canonical patterns). These regions show greater sensitivity to the lower visual field and to magnocellular-based input.     

From 1D to 2D via 3D: dynamics of surface motion segmentation for ocular tracking in primates.

In primates, tracking eye movements help vision by stabilising onto the retinas the images of a moving object of interest. This sensorimotor transformation involves several stages of motion processing, from the local measurement of one-dimensional luminance changes up to the integration of first and higher-order local motion cues into a global two-dimensional motion immune to antagonistic motions arising from the surrounding. The dynamics of this surface motion segmentation is reflected into the various components of the tracking responses and its underlying neural mechanisms can be correlated with behaviour at both single-cell and population levels. I review a series of behavioural studies which demonstrate that the neural representation driving eye movements evolves over time from a fast vector average of the outputs of linear and non-linear spatio-temporal filtering to a progressive and slower accurate solution for global motion. Because of the sensitivity of earliest ocular following to binocular disparity, antagonistic visual motion from surfaces located at different depths are filtered out. Thus, global motion integration is restricted within the depth plane of the object to be tracked. Similar dynamics were found at the level of monkey extra-striate areas MT and MST and I suggest that several parallel pathways along the motion stream are involved albeit with different latencies to build-up this accurate surface motion representation. After 200-300 ms, most of the computational problems of early motion processing (aperture problem, motion integration, motion segmentation) are solved and the eye velocity matches the global object velocity to maintain a clear and steady retinal image.     

Synchronized firing among retinal ganglion cells signals motion reversal

We show that when a moving object suddenly reverses direction, there is a brief, synchronous burst of firing within a population of retinal ganglion cells. This burst can be driven by either the leading or trailing edge of the object. The latency is constant for movement at different speeds, objects of different size, and bright versus dark contrasts. The same ganglion cells that signal a motion reversal also respond to smooth motion. We show that the brain can build a pure reversal detector using only a linear filter that reads out synchrony from a group of ganglion cells. These results indicate that not only can the retina anticipate the location of a smoothly moving object, but that it can also signal violations in its own prediction. We show that the reversal response cannot be explained by models of the classical receptive field and suggest that nonlinear receptive field subunits may be responsible.     

Ramp edges,Mach bands,and the functional significance of the simple cell assembly

The responses of “complex” simple cells to sharp and blurred ramp edges were studied. These responses are quite similar to those in the case of lines, which implies that phase information cannot be used to discriminate between ramp edges and lines. Furthermore, if the maximum of the modulus is used as a position estimate, a systematic bias toward the ramp side results, and this bias increases with edge blur. In contrast, a local extremum in the real part of the cell responses provides a precise position estimate, even for strongly blurred edges. Possible multiscale detection strategies are discussed in the context of a syntactical visual reconstruction. This is illustrated by an explanation of Mach bands as perceived at trapezoidal edges, including Ratliff’s Mach-band cancellation stimulus, and criteria for local probability summation in the prediction of Mach-band detection thresholds are presented. Received: 10 December 1992/Accepted in revised form: 6 August 1993     

Are non-directional simple cells constructed from directional subunits?

Experiments by Schiller et al. have suggested that non-directional edge-specific simple cells are constructed from two directionally selective subunits with opposite preferred direction. This hierarchical notion was based on the fact that the responses of such units to edges moving in opposite directions are spatially displaced with respect to each other.An alternative explanation of the observed response separation is the delay between the responses of the center and surround mechanisms at the retinal level. Measurements of the response separation as a function of stimulus speed support this explanation and argues against the hierarchical notion of Schiller et al.     

Spatio-temporal brain mapping of motion-onset VEPs combined with fMRI and retinotopic maps

Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR).     

Stereoscopic and contrast-defined motion in human vision.

There is considerable evidence for the existence of a specialized mechanism in human vision for detecting moving contrast modulations and some evidence for a mechanism for detecting moving stereoscopic depth modulations. It is unclear whether a single second-order motion mechanism detects both types of stimulus or whether they are detected separately. We show that sensitivity to stereo-defined motion resembles that to contrast-defined motion in two important ways. First, when a missing-fundamental disparity waveform is moved in steps of 0.25 cycles, its perceived direction tends to reverse. This is a property of both luminance-defined and contrast-defined motion and is consistent with independent detection of motion at different spatial scales. Second, thresholds for detecting the direction of a smoothly drifting sinusoidal disparity modulation are much higher than those for detecting its orientation. This is a property of contrast-modulated gratings but not luminance-modulated gratings, for which the two thresholds are normally identical. The results suggest that stereo-defined and contrast-defined motion stimuli are detected either by a common mechanism or by separate mechanisms sharing a common principle of operation.     

蜻蜒运动检测神经元的光谱反应

蜻蜒腹神经束上存在着自运动检测神经元和目标运动检测神经元.我们采用了两种视觉刺激条件来测试自运动检测神经元的光谱反应.当采用控制强度和波长的闪光进行测试时、它们的光谱反应曲线与绿色光感受器的光谱灵敏度曲线极其相似,峰值位于500nm处.然而采用运动的条纹进行测试时,它们的峰值却位于560nm处.当用一种颜色的运动图案作为目标放置在另一种颜色背景的前方测试时,发现存在某个目标的照明强度值能使反应下降到自发放电的水平,这表明自运动检测器无法检测这二种颜色的差别,即它们是色盲的、它主要接受来自绿色光感受器的信号.目标运动检测神经元的光谱反应特性与自运动检测神经元的不同,目标运动检测神经元在以380nm至580nm的范围中有着平坦的光谱反应曲线,有时在紫外频段出现峰有(?)前景与背景颜色不同且固定背景光的颜色与强度而改变前景的光强时,神经元的反应不会下降到自发放电水平,当背景为绿色而目标为另一个颜色.特别是兰色时,神经元反应强烈,但当背景为兰色而目标为绿色时,它们的反应相对较弱.这些结果表明目标运动检测神经元是对颜色敏感的.