A computational analysis of separating motion signals in transparent random dot kinematograms

When multiple motion directions are presented simultaneously within the same region of the visual field human observers see motion transparency. This perceptual phenomenon requires from the visual system to separate different motion signal distributions, which are characterised by distinct means that correspond to the different dot directions and variances that are determined by the signal and processing noise. Averaging of local motion signals can be employed to reduce noise components, but such pooling could at the same time lead to the averaging of different directional signal components, arising from spatially adjacent dots moving in different directions, which would reduce the visibility of transparent directions. To study the theoretical limitations of encoding transparent motion by a biologically plausible motion detector network, the distributions of motion directions signalled by a motion detector model (2DMD) were analysed here for Random Dot Kinematograms (RDKs). In sparse dot RDKs with two randomly interleaved motion directions, the angular separation that still allows us to separate two directions is limited by the internal noise in the system. Under the present conditions direction differences down to 30 deg could be separated. Correspondingly, in a transparent motion stimulus containing multiple motion directions, more than eight directions could be separated. When this computational analysis is compared to some published psychophysical data, it appears that the experimental results do not reach the predicted limits. Whereas the computer simulations demonstrate that even an unsophisticated motion detector network would be appropriate to represent a considerable number of motion directions simultaneously within the same region, human observers usually are restricted to seeing not more than two or three directions under comparable conditions. This raises the question why human observers do not make full use of information that could be easily extracted from the representation of motion signals at the early stages of the visual system.     

复合运动条纹刺激下的视动震颤（OKN）眼动反应

研究视动震颤眼动系统在同时包含两个二维运动的复合运动条纹刺激下的反应特性,并探讨两种子条纹运动方向的夹角和运动速度的影响。实验结果发现,在一定参数范围内,复合运动条纹引起了双重交替ＯＫＮ反应,即ＫＯＮ交替地跟踪合成运动和分别运动;在跟踪分别运动中,又是交替地跟踪两种子条纹的运动。     

Direct evidence for encoding of motion streaks in human visual cortex

Temporal integration in the visual system causes fast-moving objects to generate static, oriented traces (‘motion streaks’), which could be used to help judge direction of motion. While human psychophysics and single-unit studies in non-human primates are consistent with this hypothesis, direct neural evidence from the human cortex is still lacking. First, we provide psychophysical evidence that faster and slower motions are processed by distinct neural mechanisms: faster motion raised human perceptual thresholds for static orientations parallel to the direction of motion, whereas slower motion raised thresholds for orthogonal orientations. We then used functional magnetic resonance imaging to measure brain activity while human observers viewed either fast (‘streaky’) or slow random dot stimuli moving in different directions, or corresponding static-oriented stimuli. We found that local spatial patterns of brain activity in early retinotopic visual cortex reliably distinguished between static orientations. Critically, a multivariate pattern classifier trained on brain activity evoked by these static stimuli could then successfully distinguish the direction of fast (‘streaky’) but not slow motion. Thus, signals encoding static-oriented streak information are present in human early visual cortex when viewing fast motion. These experiments show that motion streaks are present in the human visual system for faster motion.     

Direction repulsion goes global

When viewing two superimposed, translating sets of dots moving in different directions, one overestimates direction difference. This phenomenon of direction repulsion is thought to be driven by inhibitory interactions between directionally tuned motion detectors. However, there is disagreement on where this occurs-at early stages of motion processing, when local motions are extracted; or at the later, global motion-processing stage following "pooling" of these local measures. These two stages of motion processing have been identified as occurring in area V1 and the human homolog of macaque MT/V5, respectively. We designed experiments in which local and global predictions of repulsion are pitted against one another. Our stimuli contained a target set of dots, moving at a uniform speed, superimposed on a "mixed-speed" distractor set. Because the perceived speed of a mixed-speed stimulus is equal to the dots' average speed, a global-processing account of direction repulsion predicts that repulsion magnitude induced by a mixed-speed distractor will be indistinguishable from that induced by a single-speed distractor moving at the same mean speed. This is exactly what we found. These results provide compelling evidence that global-motion interactions play a major role in driving direction repulsion.     

Motion repulsion arises from stimulus statistics when analyzed with a clustering algorithm

Motion repulsion is the perceived enlargement of the angle between the directions of motion of two transparently moving patterns. An explanation of this illusion has long been sought for in the neural circuitry of the brain. We show that motion repulsion already arises from the statistical properties of the motion transparency problem when analyzed with a clustering algorithm.     

Human visual system integrates color signals along a motion trajectory

Whether fundamental visual attributes, such as color, motion, and shape, are analyzed separately in specialized pathways has been one of the central questions of visual neuroscience. Although recent studies have revealed various forms of cross-attribute interactions, including significant contributions of color signals to motion processing, it is still widely believed that color perception is relatively independent of motion processing. Here, we report a new color illusion, motion-induced color mixing, in which moving bars, the color of each of which alternates between two colors (e.g., red and green), are perceived as the mixed color (e.g., yellow) even though the two colors are never superimposed on the retina. The magnitude of color mixture is significantly stronger than that expected from direction-insensitive spatial integration of color signals. This illusion cannot be ascribed to optical image blurs, including those induced by chromatic aberration, or to involuntary eye movements of the observer. Our findings indicate that color signals are integrated not only at the same retinal location, but also along a motion trajectory. It is possible that this neural mechanism helps us to see veridical colors for moving objects by reducing motion blur, as in the case of luminance-based pattern perception.     

Motion Noise Changes Directional Interaction between Transparently Moving Stimuli from Repulsion to Attraction

To interpret visual scenes, visual systems need to segment or integrate multiple moving features into distinct objects or surfaces. Previous studies have found that the perceived direction separation between two transparently moving random-dot stimuli is wider than the actual direction separation. This perceptual “direction repulsion” is useful for segmenting overlapping motion vectors. Here we investigate the effects of motion noise on the directional interaction between overlapping moving stimuli. Human subjects viewed two overlapping random-dot patches moving in different directions and judged the direction separation between the two motion vectors. We found that the perceived direction separation progressively changed from wide to narrow as the level of motion noise in the stimuli was increased, showing a switch from direction repulsion to attraction (i.e. smaller than the veridical direction separation). We also found that direction attraction occurred at a wider range of direction separations than direction repulsion. The normalized effects of both direction repulsion and attraction were the strongest near the direction separation of ∼25° and declined as the direction separation further increased. These results support the idea that motion noise prompts motion integration to overcome stimulus ambiguity. Our findings provide new constraints on neural models of motion transparency and segmentation.     

Neural population representation hypothesis of visual flow and its illusory after effect in the brain: psychophysics,neurophysiology and computational approaches

The neural representation of motion aftereffects induced by various visual flows (translational, rotational, motion-in-depth, and translational transparent flows) was studied under the hypothesis that the imbalances in discharge activities would occur in favor in the direction opposite to the adapting stimulation in the monkey MST cells (cells in the medial superior temporal area) which can discriminate the mode (i.e., translational, rotational, or motion-in-depth) of the given flow. In single-unit recording experiments conducted on anaesthetized monkeys, we found that the rate of spontaneous discharge and the sensitivity to a test stimulus moving in the preferred direction decreased after receiving an adapting stimulation moving in the preferred direction, whereas they increased after receiving an adapting stimulation moving in the null direction. To consistently explain the bidirectional perception of a transparent visual flow and its unidirectional motion aftereffect by the same hypothesis, we need to assume the existence of two subtypes of MST D cells which show directionally selective responses to a translational flow: component cells and integration cells. Our physiological investigation revealed that the MST D cells could be divided into two types: one responded to a transparent flow by two peaks at the instances when the direction of one of the component flow matched the preferred direction of the cell, and the other responded by a single peak at the instance when the direction of the integrated motion matched the preferred direction. In psychophysical experiments on human subjects, we found evidence for the existence of component and integration representations in the human brain. To explain the different motion perceptions, i.e., two transparent flows during presentation of the flows and a single flow in the opposite direction to the integrated flows after stopping the flow stimuli, we suggest that the pattern-discrimination system can select the motion representation that is consistent with the perception of the pattern from two motion representations. We discuss the computational aspects related to the integration of component motion fields.     

A model of motion adaptation and motion after-effects based upon principal component regression

A computational model to help explain effects of adaptation to moving signals is compared with established energy (linear regression) models of motion detection. The proposed model assumes that processed image signals are subject to error in both dimensions of space and time. This assumption constrains models of motion perception to be based upon principal component regression rather than linear regression. It is shown that response suppression of model complex cell neurons that input into the model may account for (1) increases in perceived speed after adaptation to static patterns and testing with slowly moving patterns, (2) significant increases in perceived speed after adaptation to patterns moving at a medium speed and testing at high speed, and (3) decreases in perceived speed in the opponent direction to a quickly moving adapting signal. Neither of predictions (2) or (3) are general features of established accounts of motion detection by visual processes based upon linear regression. Comparisons of the proposed model's speed transfer function with existing psychophysical data suggests that the visual system processes motion signals with the tacit assumption that image measurements are subject to error in both space and time. Received: 24 January 2000 / Accepted in revised form: 8 May 2000     

Motion camouflage induced by zebra stripes

The functional significance of the zebra coat stripe pattern is one of the oldest questions in evolutionary biology, having troubled scientists ever since Charles Darwin and Alfred Russel Wallace first disagreed on the subject. While different theories have been put forward to address this question, the idea that the stripes act to confuse or ‘dazzle’ observers remains one of the most plausible. However, the specific mechanisms by which this may operate have not been investigated in detail. In this paper, we investigate how motion of the zebra's high contrast stripes creates visual effects that may act as a form of motion camouflage. We simulated a biologically motivated motion detection algorithm to analyse motion signals generated by different areas on a zebra's body during displacements of their retinal images. Our simulations demonstrate that the motion signals that these coat patterns generate could be a highly misleading source of information. We suggest that the observer's visual system is flooded with erroneous motion signals that correspond to two well-known visual illusions: (i) the wagon-wheel effect (perceived motion inversion due to spatiotemporal aliasing); and (ii) the barber-pole illusion (misperceived direction of motion due to the aperture effect), and predict that these two illusory effects act together to confuse biting insects approaching from the air, or possibly mammalian predators during the hunt, particularly when two or more zebras are observed moving together as a herd.     

Characteristics of Motor Resonance Predict the Pattern of Flash-Lag Effects for Biological Motion

Background

When a moving stimulus and a briefly flashed static stimulus are physically aligned in space the static stimulus is perceived as lagging behind the moving stimulus. This vastly replicated phenomenon is known as the Flash-Lag Effect (FLE). For the first time we employed biological motion as the moving stimulus, which is important for two reasons. Firstly, biological motion is processed by visual as well as somatosensory brain areas, which makes it a prime candidate for elucidating the interplay between the two systems with respect to the FLE. Secondly, discussions about the mechanisms of the FLE tend to recur to evolutionary arguments, while most studies employ highly artificial stimuli with constant velocities.

Methodology/Principal Finding

Since biological motion is ecologically valid it follows complex patterns with changing velocity. We therefore compared biological to symbolic motion with the same acceleration profile. Our results with 16 observers revealed a qualitatively different pattern for biological compared to symbolic motion and this pattern was predicted by the characteristics of motor resonance: The amount of anticipatory processing of perceived actions based on the induced perspective and agency modulated the FLE.

Conclusions/Significance

Our study provides first evidence for an FLE with non-linear motion in general and with biological motion in particular. Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. Our findings are compatible with visual prediction (Nijhawan, 2008) which assumes that extrapolated motion representations within the visual system generate the FLE. These representations are modulated by sudden visual input (e.g. offset signals) or by input from other systems (e.g. sensorimotor) that can boost or attenuate overshooting representations in accordance with biased neural competition (Desimone & Duncan, 1995).     

Detecting binocular 3D motion in static 3D noise: no effect of viewing distance

Relative binocular disparity cannot tell us the absolute 3D shape of an object, nor the 3D trajectory of its motion, unless the visual system has independent access to how far away the object is at any moment. Indeed, as the viewing distance is changed, the same disparate retinal motions will correspond to very different real 3D trajectories. In this paper we were interested in whether binocular 3D motion detection is affected by viewing distance. A visual search task was used, in which the observer is asked to detect a target dot, moving in 3D, amidst 3D stationary distractor dots. We found that distance does not affect detection performance. Motion-in-depth is consistently harder to detect than the equivalent lateral motion, for all viewing distances. For a constant retinal motion with both lateral and motion-in-depth components, detection performance is constant despite variations in viewing distance that produce large changes in the direction of the 3D trajectory. We conclude that binocular 3D motion detection relies on retinal, not absolute, visual signals.     

Attention to surfaces modulates motion processing in extrastriate area MT

In the visual system, early atomized representations are grouped into higher-level entities through processes of perceptual organization. Here we present neurophysiological evidence that a representation of a simple object, a surface defined by color and motion, can be the unit of attentional selection at an early stage of visual processing. Monkeys were cued by the color of a fixation spot to attend to one of two transparent random-dot surfaces, one red and one green, which occupied the same region of space. Motion of the attended surface drove neurons in the middle temporal (MT) visual area more strongly than physically identical motion of the non-attended surface, even though both occurred within the spotlight of attention. Surface-based effects of attention persisted even without differential surface coloring, but attentional modulation was stronger with color. These results show that attention can select surface representations to modulate visual processing as early as cortical area MT.     

A Network Model of Motion Processing in Area MT of Primates

A simple and biologically plausible model is proposed to simulatethe visual motion processing taking place in the middle temporal (MT) areaof the visual cortex in the primate brain. The model is ahierarchical neural network composed of multiple competitive learninglayers. The input layer of the network simulates the neurons in the primaryvisual cortex (V1), which are sensitive to the orientation and motionvelocity of the visual stimuli, and the middle and output layers of thenetwork simulate the component MT and pattern MT neurons, which areselectively responsive to local and global motions, respectively. Thenetwork model was tested with various simulated motion patterns (random dotsof different direction correlations, transparent motion, grating and plaidpatterns, and so on). The response properties of the model closely resemblemany of the known features of the MT neurons found neurophysiologically.These results show that the sophisticated response behaviors of the MTneurons can emerge naturally from some very simple models, such as acompetitive learning network.     

Long-range interactions in the spatial integration of motion signals.

When a sinewave grating is moving within a cross-shaped aperture, a strongly multi-stable phenomenon is perceived. The percept switches between the coherence of an extended surface moving in a single direction and the segregation of two patterned strips sliding across each other in directions parallel to the branches of the cross. We studied how the balance between these two percepts is affected by the length of the arms and by the shape of their ends. We report here that human observers report the segregation into two surfaces more often when the branches of the cross are extended, and when the small sides of the arms are oriented parallel to the grating. Two kinds of early motion signals interact in the crossed barber-pole stimulus: (a) the signals extracted in the middle of the bars are ambiguous with regard to their direction, and usually would be interpreted as motion normal to the grating orientation; (b) the signals from regions where the grating is intersected by the borders of the aperture convey motion signals in direction of the border. Our results show that the global appearance of our display can be dramatically influenced by the reliability of motion signals located in small regions that may be separated by large distances. To explain this long-range effect, we tentatively propose the existence of a representation level situated between the extraction of low-level local signals and the final global percept. The postulated processing level is concerned with the segmenting of the entire image into surfaces that are likely to belong to the same object, even if they are not contiguous in space. This hypothetical mechanism involves the construction of coarse-scale 'patches' from the local motion signal distributions, each carrying a single velocity associated with a certain degree of reliability. Our experiments indicate that the probability of grouping together similar patches depends on their respective reliabilities.     

Non-Conscious Processing of Motion Coherence Can Boost Conscious Access

Research on the scope and limits of non-conscious vision can advance our understanding of the functional and neural underpinnings of visual awareness. Here we investigated whether distributed local features can be bound, outside of awareness, into coherent patterns. We used continuous flash suppression (CFS) to create interocular suppression, and thus lack of awareness, for a moving dot stimulus that varied in terms of coherence with an overall pattern (radial flow). Our results demonstrate that for radial motion, coherence favors the detection of patterns of moving dots even under interocular suppression. Coherence caused dots to break through the masks more often: this indicates that the visual system was able to integrate low-level motion signals into a coherent pattern outside of visual awareness. In contrast, in an experiment using meaningful or scrambled biological motion we did not observe any increase in the sensitivity of detection for meaningful patterns. Overall, our results are in agreement with previous studies on face processing and with the hypothesis that certain features are spatiotemporally bound into coherent patterns even outside of attention or awareness.     

基于空间ICA和时间相关方法的人脑视觉皮层V5区的功能连通性研究

利用功能磁共振成像技术,将空间ICA和时间相关方法相结合来研究不同活动状态下人脑视觉皮层V5区的功能连通性。首先利用空间ICA处理组块视觉运动刺激的数据,定位V5区;然后分别计算静息和连续视觉运动刺激两种稳态下V5区与其它脑区低频振荡的时间相关,检测出该区的功能连通网络。实验结果表明,静息时V5区的功能连通网络更广泛,且与已知的解剖连通一致;当被试接受连续视觉运动刺激时,与V5区连通的脑区网络局限在视觉皮层,此时的网络特定于处理视觉运动这一任务。     

A Color Hierarchy for Automatic Target Selection

Visual processing of color starts at the cones in the retina and continues through ventral stream visual areas, called the parvocellular pathway. Motion processing also starts in the retina but continues through dorsal stream visual areas, called the magnocellular system. Color and motion processing are functionally and anatomically discrete. Previously, motion processing areas MT and MST have been shown to have no color selectivity to a moving stimulus; the neurons were colorblind whenever color was presented along with motion. This occurs when the stimuli are luminance-defined versus the background and is considered achromatic motion processing. Is motion processing independent of color processing? We find that motion processing is intrinsically modulated by color. Color modulated smooth pursuit eye movements produced upon saccading to an aperture containing a surface of coherently moving dots upon a black background. Furthermore, when two surfaces that differed in color were present, one surface was automatically selected based upon a color hierarchy. The strength of that selection depended upon the distance between the two colors in color space. A quantifiable color hierarchy for automatic target selection has wide-ranging implications from sports to advertising to human-computer interfaces.     

Analytic determination of the depth effect in stereokinetic phenomena without a rigidity assumption

When a circular disk with an eccentric dot is set in slow rotary motion a compelling impression of a three-dimensional cone is observed. Similarly a line segment of constant length, a bar, rotating on the frontal plane appears slanted in depth. The two stereokinetic phenomena cannot be explained on the basis of Ullman's method of extracting depth from 2-D moving stimuli i.e. the rigidity assumption. A new analytic model is here presented based on the hypothesis that the visual system minimizes the relative velocity differences among all the points of the moving pattern. Two different methods of calculating the depth displacement are described: the velocity field method and the trajectories method. Both lead to the same results. A comparison of the theoretical results with the experimental ones supports the validity of the model.     

Moving from spatially segregated to transparent motion: A modelling approach

Motion transparency, in which patterns of moving elements group together to give the impression of lacy overlapping surfaces, provides an important challenge to models of motion perception. It has been suggested that we perceive transparent motion when the shape of the velocity histogram of the stimulus is bimodal. To investigate this further, random-dot kinematogram motion sequences were created to simulate segregated (perceptually spatially separated) and transparent (perceptually overlapping) motion. The motion sequences were analysed using the multi-channel gradient model (McGM) to obtain the speed and direction at every pixel of each frame of the motion sequences. The velocity histograms obtained were found to be quantitatively similar and all were bimodal. However, the spatial and temporal properties of the velocity field differed between segregated and transparent stimuli. Transparent stimuli produced patches of rightward and leftward motion that varied in location over time. This demonstrates that we can successfully differentiate between these two types of motion on the basis of the time varying local velocity field. However, the percept of motion transparency cannot be based simply on the presence of a bimodal velocity histogram.