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     

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.     

Induced motion at texture-defined motion boundaries

When a static textured background is covered and uncovered by a moving bar of the same mean luminance we can clearly see the motion of the bar. Texture-defined motion provides an example of a naturally occurring second-order motion. Second-order motion sequences defeat standard spatio-temporal energy models of motion perception. It has been proposed that second-order stimuli are analysed by separate systems, operating in parallel with luminance-defined motion processing, which incorporate identifiable pre-processing stages that make second-order patterns visible to standard techniques. However, the proposal of multiple paths to motion analysis remains controversial. Here we describe the behaviour of a model that recovers both luminance-defined and an important class of texture-defined motion. The model also accounts for the induced motion that is seen in some texture-defined motion sequences. We measured the perceived direction and speed of both the contrast envelope and induced motion in the case of a contrast modulation of static noise textures. Significantly, the model predicts the perceived speed of the induced motion seen at second-order texture boundaries. The induced motion investigated here appears distinct from classical induced effects resulting from motion contrast or the movement of a reference frame.     

Structure-from-motion based on information at surface boundaries

Existing computational models of structurefrom-motion — the appearance of three-dimensional motion generated by moving two-dimensional patterns — are all based on variations of optical flow or feature point correspondence within the interior of single objects. Three separate phenomena provide strong evidence that in human vision, structure-from-motion is significantly affected by surface boundary cues. In the first, a rotating cylinder is seen, though no variation in optical flow exists across the apparent cylinder. In the second, the shape of the bounding contour of a moving pattern dominates the actual differential motion within the pattern. In the third, the appearance of independently moving objects changes significantly when the boundary between them becomes indistinct. We describe a simple computational model sufficient to account for these effects. The model is based on qualitative constraints relating possible object motions to patterns of flow, together with an understanding of the patterns of flow that can be discriminated in practice.     

Processing Deficits of Motion of Contrast-Modulated Gratings in Anisometropic Amblyopia

Several studies have indicated substantial processing deficits for static second-order stimuli in amblyopia. However, less is known about the perception of second-order moving gratings. To investigate this issue, we measured the contrast sensitivity for second-order (contrast-modulated) moving gratings in seven anisometropic amblyopes and ten normal controls. The measurements were performed with non-equated carriers and a series of equated carriers. For comparison, the sensitivity for first-order motion and static second-order stimuli was also measured. Most of the amblyopic eyes (AEs) showed reduced sensitivity for second-order moving gratings relative to their non-amblyopic eyes (NAEs) and the dominant eyes (CEs) of normal control subjects, even when the detectability of the noise carriers was carefully controlled, suggesting substantial processing deficits of motion of contrast-modulated gratings in anisometropic amblyopia. In contrast, the non-amblyopic eyes of the anisometropic amblyopes were relatively spared. As a group, NAEs showed statistically comparable performance to CEs. We also found that contrast sensitivity for static second-order stimuli was strongly impaired in AEs and part of the NAEs of anisometropic amblyopes, consistent with previous studies. In addition, some amblyopes showed impaired performance in perception of static second-order stimuli but not in that of second-order moving gratings. These results may suggest a dissociation between the processing of static and moving second-order gratings in anisometropic amblyopia.     

A motion illusion reveals mechanisms of perceptual stabilization

Visual illusions are valuable tools for the scientific examination of the mechanisms underlying perception. In the peripheral drift illusion special drift patterns appear to move although they are static. During fixation small involuntary eye movements generate retinal image slips which need to be suppressed for stable perception. Here we show that the peripheral drift illusion reveals the mechanisms of perceptual stabilization associated with these micromovements. In a series of experiments we found that illusory motion was only observed in the peripheral visual field. The strength of illusory motion varied with the degree of micromovements. However, drift patterns presented in the central (but not the peripheral) visual field modulated the strength of illusory peripheral motion. Moreover, although central drift patterns were not perceived as moving, they elicited illusory motion of neutral peripheral patterns. Central drift patterns modulated illusory peripheral motion even when micromovements remained constant. Interestingly, perceptual stabilization was only affected by static drift patterns, but not by real motion signals. Our findings suggest that perceptual instabilities caused by fixational eye movements are corrected by a mechanism that relies on visual rather than extraretinal (proprioceptive or motor) signals, and that drift patterns systematically bias this compensatory mechanism. These mechanisms may be revealed by utilizing static visual patterns that give rise to the peripheral drift illusion, but remain undetected with other patterns. Accordingly, the peripheral drift illusion is of unique value for examining processes of perceptual stabilization.     

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.     

Motion-based mechanisms of illusory contour synthesis

Neurophysiological studies and computational models of illusory contour formation have focused on contour orientation as the underlying determinant of illusory contour shape in both static and moving displays. Here, we report a class of motion-induced illusory contours that demonstrate the existence of novel mechanisms of illusory contour synthesis. In a series of experiments, we show that the velocity of contour terminations and the direction of motion of a partially occluded figure regulate the perceived shape and apparent movement of illusory contours formed from moving image sequences. These results demonstrate the existence of neural mechanisms that reconstruct occlusion relationships from both real and inferred image velocities, in contrast to the static geometric mechanisms that have been the focus of studies to date.     

Pre-Exposure to Moving Form Enhances Static Form Sensitivity

Background

Motion-defined form can seem to persist briefly after motion ceases, before seeming to gradually disappear into the background. Here we investigate if this subjective persistence reflects a signal capable of improving objective measures of sensitivity to static form.

Methodology/Principal Findings

We presented a sinusoidal modulation of luminance, masked by a background noise pattern. The sinusoidal luminance modulation was usually subjectively invisible when static, but visible when moving. We found that drifting then stopping the waveform resulted in a transient subjective persistence of the waveform in the static display. Observers'' objective sensitivity to the position of the static waveform was also improved after viewing moving waveforms, compared to viewing static waveforms for a matched duration. This facilitation did not occur simply because movement provided more perspectives of the waveform, since performance following pre-exposure to scrambled animations did not match that following pre-exposure to smooth motion. Observers did not simply remember waveform positions at motion offset, since removing the waveform before testing reduced performance.

Conclusions/Significance

Motion processing therefore interacts with subsequent static visual inputs in a way that can improve performance in objective sensitivity measures. We suggest that the brief subjective persistence of motion-defined forms that can occur after motion offsets is a consequence of the decay of a static form signal that has been transiently enhanced by motion processing.     

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).     

Incidental processing of biological motion

The successful detection of biological motion can have important consequences for survival. Previous studies have demonstrated the ease and speed with which observers can extract a wide range of information from impoverished dynamic displays in which only an actor's joints are visible. Although it has often been suggested that such biological motion processing can be accomplished relatively automatically, few studies have directly tested this assumption by using behavioral methods. Here we used a flanker paradigm to assess how peripheral "to-be-ignored" walkers affect the processing of a central target walker. Our results suggest that task-irrelevant dynamic figures cannot be ignored and are processed to a level where they influence behavior. These findings provide the first direct evidence that complex dynamic patterns can be processed incidentally, a finding that may have important implications for cognitive, neurophysiological, and computational models of biological motion processing.     

Speed of Human Biological Form and Motion Processing

Recent work suggests that biological motion processing can begin within ~110 ms of stimulus onset, as indexed by the P1 component of the event-related potential (ERP). Here, we investigated whether modulation of the P1 component reflects configural processing alone, rather than the processing of both configuration and motion cues. A three-stimulus oddball task was employed to evaluate bottom-up processing of biological motion. Intact point-light walkers (PLWs) or scrambled PLWs served as distractor stimuli, whereas point-light displays of tool motion served as standard and target stimuli. In a second experiment, the same design was used, but the dynamic stimuli were replaced with static point-light displays. The first experiment revealed that dynamic PLWs elicited a larger P1 as compared to scrambled PLWs. A similar P1 increase was also observed for static PLWs in the second experiment, indicating that these stimuli were more salient than static, scrambled PLWs. These findings suggest that the visual system can rapidly extract global form information from static PLWs and that the observed P1 effect for dynamic PLWs is not dependent on the presence of motion cues. Finally, we found that the N1 component was sensitive to dynamic, but not static, PLWs, suggesting that this component reflects the processing of both form and motion information. The sensitivity of P1 to static PLWs has implications for dynamic form models of biological motion processing that posit temporal integration of configural cues present in individual frames of PLW animations.     

A multi-differential neuromorphic approach to motion detection

This paper presents a multi-differential neuromorphic approach to motion detection. The model is based evidence for a differential operators interpretation of the properties of the cortical motion pathway. We discuss how this strategy, which provides a robust measure of speed for a range of types of image motion using a single computational mechanism, forms a useful framework in which to develop future neuromorphic motion systems. We also discuss both our approaches to developing computational motion models, and constraints in the design strategy for transferring motion models to other domains of early visual processing.     

Influence of Visual Motion,Suggestion, and Illusory Motion on Self-Motion Perception in the Horizontal Plane

A moving visual field can induce the feeling of self-motion or vection. Illusory motion from static repeated asymmetric patterns creates a compelling visual motion stimulus, but it is unclear if such illusory motion can induce a feeling of self-motion or alter self-motion perception. In these experiments, human subjects reported the perceived direction of self-motion for sway translation and yaw rotation at the end of a period of viewing set visual stimuli coordinated with varying inertial stimuli. This tested the hypothesis that illusory visual motion would influence self-motion perception in the horizontal plane. Trials were arranged into 5 blocks based on stimulus type: moving star field with yaw rotation, moving star field with sway translation, illusory motion with yaw, illusory motion with sway, and static arrows with sway. Static arrows were used to evaluate the effect of cognitive suggestion on self-motion perception. Each trial had a control condition; the illusory motion controls were altered versions of the experimental image, which removed the illusory motion effect. For the moving visual stimulus, controls were carried out in a dark room. With the arrow visual stimulus, controls were a gray screen. In blocks containing a visual stimulus there was an 8s viewing interval with the inertial stimulus occurring over the final 1s. This allowed measurement of the visual illusion perception using objective methods. When no visual stimulus was present, only the 1s motion stimulus was presented. Eight women and five men (mean age 37) participated. To assess for a shift in self-motion perception, the effect of each visual stimulus on the self-motion stimulus (cm/s) at which subjects were equally likely to report motion in either direction was measured. Significant effects were seen for moving star fields for both translation (p = 0.001) and rotation (p<0.001), and arrows (p = 0.02). For the visual motion stimuli, inertial motion perception was shifted in the direction consistent with the visual stimulus. Arrows had a small effect on self-motion perception driven by a minority of subjects. There was no significant effect of illusory motion on self-motion perception for either translation or rotation (p>0.1 for both). Thus, although a true moving visual field can induce self-motion, results of this study show that illusory motion does not.     

Parallel visual motion processing streams for manipulable objects and human movements

We tested the hypothesis that different regions of lateral temporal cortex are specialized for processing different types of visual motion by studying the cortical responses to moving gratings and to humans and manipulable objects (tools and utensils) that were either stationary or moving with natural or artificially generated motions. Segregated responses to human and tool stimuli were observed in both ventral and lateral regions of posterior temporal cortex. Relative to ventral cortex, lateral temporal cortex showed a larger response for moving compared with static humans and tools. Superior temporal cortex preferred human motion, and middle temporal gyrus preferred tool motion. A greater response was observed in STS to articulated compared with unarticulated human motion. Specificity for different types of complex motion (in combination with visual form) may be an organizing principle in lateral temporal cortex.     

Bayesian inference in populations of cortical neurons: a model of motion integration and segmentation in area MT

A major issue in cortical physiology and computational neuroscience is understanding the interaction between extrinsic signals from feedforward connections and intracortical signals from lateral connections. We propose here a computational model for motion perception based on the assumption that the local cortical circuits in the medio-temporal area (area MT) implement a Bayesian inference principle. This approach establishes a functional balance between feedforward and lateral, excitatory and inhibitory, inputs. The model reproduces most of the known properties of the neurons in area MT in response to moving stimuli. It accounts for important motion perception phenomena including motion transparency, spatial and temporal integration/segmentation. While integrating several properties of previously proposed models, it makes specific testable predictions concerning, in particular, temporal properties of neurons and the architecture of lateral connections in area MT. In addition, the proposed mechanism is consistent with the known properties of local cortical circuits in area V1. This suggests that Bayesian inference may be a general feature of information processing in cortical neuron populations. Received: 3 December 1997 / Accepted in revised form: 21 July 1998     

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.     

The visual processing of motion-defined transparency

Our understanding of how the visual system processes motion transparency, the phenomenon by which multiple directions of motion are perceived to coexist in the same spatial region, has grown considerably in the past decade. There is compelling evidence that the process is driven by global-motion mechanisms. Consequently, although transparently moving surfaces are readily segmented over an extended space, the visual system cannot separate two motion signals that coexist in the same local region. A related issue is whether the visual system can detect transparently moving surfaces simultaneously or whether the component signals encounter a serial 'bottleneck' during their processing. Our initial results show that, at sufficiently short stimulus durations, observers cannot accurately detect two superimposed directions; yet they have no difficulty in detecting one pattern direction in noise, supporting the serial-bottleneck scenario. However, in a second experiment, the difference in performance between the two tasks disappears when the component patterns are segregated. This discrepancy between the processing of transparent and non-overlapping patterns may be a consequence of suppressed activity of global-motion mechanisms when the transparent surfaces are presented in the same depth plane. To test this explanation, we repeated our initial experiment while separating the motion components in depth. The marked improvement in performance leads us to conclude that transparent motion signals are represented simultaneously.     

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.     

采用Reichardt运动检测器和Boltzmann Machine神经网络的运动计算

建立了一个探讨灵长类视皮层从Ｖ１区到ＭＴ区的运动信息加工原理的计算模型,这个过程的突出特征是视觉运动信息经过了从局部检测进步到整体感知。模型的第一层由用于抽提运动模式的局部速度以及结构性质的Ｒｅｉｃｈａｒｄｔ运动检测器组成,进一步的加工是通过Ｂｏｌｔｚｍａｎｎ Ｍａｃｈｉｎｅ神经网络来实现的。这种网络的学习算法具有局部更新的显著性质,在学习阶段,网络不断地修改联结权重以形成对于记录在网络的显单元上