Ikuya Murakami

Latency difference, not spatial extrapolation

The inevitable neural delays involved in processing visual information should cause the perceived location of a moving stimulus to lag significantly behind its actual location. However, Nijhawan has proposed that the visual system corrects the perceived location of the moving stimulus by extrapolating it along the trajectory of motion, so that the stimulus is perceived at its expected actual location. We provide new evidence to the contrary, demonstrating that the visual system does not compensate for neural delays but simply shows a reduced delay for moving stimuli.

Illusory spatial offset of a flash relative to a moving stimulus is caused by differential latencies for moving and flashed stimuli

A flash that is presented adjacent to a continuously moving bar is perceived to lag behind the bar. One explanation for this phenomenon is that there is a difference in the persistence of the flash and the bar. Another explanation is that the visual system compensates for the neural delays of processing visual motion information, such as the moving bar, by spatially extrapolating the bars perceived location forward in space along its expected trajectory. Two experiments demonstrate that neither of these models is tenable. The first experiment masked the flash one video frame after its presentation. The flash was still perceived to lag behind the bar, suggesting that a difference in the persistence of the flash and bar, does not cause the apparent offset. The second experiment employed unpredictable changes in the velocity of the bar including an abrupt reversal, disappearance, acceleration, and deceleration. If the extrapolation model held, the bar would continue to be extrapolated in accordance with its initial velocity until the moment of an abrupt velocity change. The results were inconsistent with this prediction, suggesting that there is little or no spatial compensation for the neural delays of processing moving objects. The results support a new model of temporal facilitation for moving objects whereby the apparent flash lag is due to a latency advantage for moving over flashed stimuli.

Perceived duration of visual motion increases with speed.

Despite wide recognition that a moving object is perceived to last longer, scientists do not yet agree as to how this illusion occurs. In the present study, we conducted two experiments using two experimental methods, namely duration matching and reproduction, and systematically manipulated the temporal frequency, spatial frequency, and speed of the stimulus, to identify the determinant factor of the illusion. Our results indicated that the speed of the stimulus, rather than temporal frequency or spatial frequency per se, best described the perceived duration of a moving stimulus, with the apparent duration proportionally increasing with log speed (Experiments 1 and 2). However, in an additional experiment, we found little or no change in onset and offset reaction times for moving stimuli (Experiment 3). Arguing that speed information is made explicit in higher stages of visual information processing in the brain, we suggest that this illusion is primarily mediated by higher level motion processing stages in the dorsal pathway.

Large-Field Visual Motion Directly Induces an Involuntary Rapid Manual Following Response

Recent neuroscience studies have been concerned with how aimed movements are generated on the basis of target localization. However, visual information from the surroundings as well as from the target can influence arm motor control, in a manner similar to known effects in postural and ocular motor control. Here, we show an ultra-fast manual motor response directly induced by a large-field visual motion. This rapid response aided reaction when the subject moved his hand in the direction of visual motion, suggesting assistive visually evoked manual control during postural movement. The latency of muscle activity generating this response was as short as that of the ocular following responses to the visual motion. Abrupt visual motion entrained arm movement without affecting perceptual target localization, and the degrees of motion coherence and speed of the visual stimulus modulated this arm response. This visuomotor behavior was still observed when the visual motion was confined to the “follow-through” phase of a hitting movement, in which no target existed. An analysis of the arm movements suggests that the hitting follow through made by the subject is not a part of a reaching movement. Moreover, the arm response was systematically modulated by hand bias forces, suggesting that it results from a reflexive control mechanism. We therefore propose that its mechanism is radically distinct from motor control for aimed movements to a target. Rather, in an analogy with reflexive eye movement stabilizing a retinal image, we consider that this mechanism regulates arm movements in parallel with voluntary motor control.

A jitter after-effect reveals motion-based stabilization of vision

A shaky hand holding a video camera invariably turns a treasured moment into an annoying, jittery momento. More recent consumer cameras thoughtfully offer stabilization mechanisms to compensate for our unsteady grip. Our eyes face a similar challenge in that they are constantly making small movements even when we try to maintain a fixed gaze. What should be substantial, distracting jitter passes completely unseen. Position changes from large eye movements (saccades) seem to be corrected on the basis of extraretinal signals such as the motor commands sent to the eye muscle, and the resulting motion responses seem to be simply switched off,. But this approach is impracticable for incessant, small displacements, and here we describe a novel visual illusion that reveals a compensation mechanism based on visual motion signals. Observers were adapted to a patch of dynamic random noise and then viewed a larger pattern of static random noise. The static noise in the unadapted regions then appeared to ‘jitter’ coherently in random directions. Several observations indicate that this visual jitter directly reflects fixational eye movements. We propose a model that accounts for this illusion as well as the stability of the visual world during small and/or slow eye movements such as fixational drift, smooth pursuit and low-amplitude mechanical vibrations of the eyes.

A positive correlation between fixation instability and the strength of illusory motion in a static display

A stationary pattern with asymmetrical luminance gradients can appear to move. We hypothesized that the source signal of this illusion originates in retinal image motions due to fixational eye movements. We investigated the inter-subject correlation between fixation instability and illusion strength. First, we demonstrated that the strength of the illusion can be quantified by the nulling technique. Second, we concurrently measured cancellation velocity and fixation instability for each subject, and found a positive correlation between them. The same relationship was also found within a single observer when the visual stimulus was artificially moved in the simulation of fixation instability. Third, we confirmed the same correlation with eye movements for a wider variety of illusory displays. These results suggest that fixational eye movements indeed play a relevant role in generating this motion illusion.

A flash-lag effect in random motion.

The flash-lag effect refers to the phenomenon in which a flash adjacent to a continuously moving object is perceived to lag behind it. To test three previously proposed hypotheses (motion extrapolation, positional averaging, and differential latency), a new stimulus configuration, to which the three hypotheses give different predictions, was introduced. Instead of continuous motion, a randomly jumping bar was used as the moving stimulus, relative to which the position of the flash was judged. The results were visualized as a spatiotemporal correlogram, in which the response to a flash was plotted at the space-time relative to the position and onset of the jumping bar. The actual human performance was not consistent with any of the original hypotheses. However, all the results were explained well if the differential latency was assumed to fluctuate considerably, its probability density function being approximated by Gaussian. Also, the model fit well with previously published data on the flash-lag effect.

THE THEORY OF THE CURVATURE-CONSTRAINT LINE FOR AMODAL COMPLETION

Amodal completion of partly occluded figures is analyzed as natural computation. Here amodal completion is shown to consist of four subproblems: representation, parsing, correspondence, and interpolation. Second, each problem is shown to be basically solvable on the basis of the generic-viewpoint assumption. It is also argued that the interpolation problem might be the key problem because of mutual interdependence among the subproblems. Third, a theory is described for the interpolation problem, in which the generic-viewpoint assumption and the curvature-consistency assumption are presumed. The generic-viewpoint assumption entails that the orientation and the curvature should not change at the point of occlusion. The curvature-consistency assumption entails that the hidden contour should have the minimum number of inflections to maintain continuity in orientation and curvature. The shape of the interpolated contour represented qualitatively in terms of the number of inflections can uniquely be determined when the location of the terminators and local orientation and curvature of the visible contours at the terminators are given. Fourth, it is shown in an instant psychophysics that the theory is highly consistent with human performance.

Surface representation in the visual system

Perception of surface accompanies the impression that a certain area of the visual field is occupied by some quality, such as color, brightness and transparency. This does not mean, however, that information about surface quality must be obtained throughout the area. It has been shown in many situations that our visual system has ability to interpolate information obtained at the border of the surface and to perceive homogeneous surfaces. The most dramatic demonstration of this is the perceptual filling-in at the blind spot. In order to understand the neural representation of surface in the visual system, we conducted a series of experiments using macaque monkeys. First, we examined if neurons in the primary visual cortex (V1) respond when a homogeneous surface is presented on the receptive field. Neurons representing the parafoveal visual field were tested and it was found that about one third of neurons showed significant responses when the cells receptive field was contained in a homogeneous surface. Then we examined neuron activities in the retinotopic representation of the blind spot in V1. Although there is no retinal input in the blind spot, a homogeneous surface is perceived within the blind spot as a result of filling-in. We tested whether neurons in this region were activated when a homogeneous surface was perceived in the blind spot as a result of filling-in. We found some neurons in V1 were activated by stimuli which lead to the filling-in. These results indicate that when a surface area is perceived, neurons are activated throughout the region in V1 topographically corresponding to the perceived surface and not restricted to the region representing the border of the surface.

Correlations between fixation stability and visual motion sensitivity

To assess influences of fixational drift eye movements on motion detection, lower thresholds for motion and drift amplitudes were measured in normal subjects. The threshold was higher without visible surrounds than with a surround, and had a positive correlation with drift amplitude. The same effect, but more pronounced, was found when the surround was visible but flickered synchronously. In contrast, the correlation disappeared in the threshold with a static surround. These results suggest that, while spurious image motions by eye drift can have a detrimental effect, a mechanism tuned for differential motions normally counteracts it.