Direction-of-motion discrimination is facilitated by visible motion smear

Motion direction is represented as a bimodal probability distribution in the human visual cortex

Humans infer motion direction from noisy sensory signals. We hypothesize that to make these inferences more precise, the visual system computes motion direction not only from velocity but also spatial orientation signals - a 'streak' created by moving objects. We implement this hypothesis in a Bayesian model, which quantifies knowledge with probability distributions, and test its predictions using psychophysics and fMRI. Using a probabilistic pattern-based analysis, we decode probability distributions of motion direction from trial-by-trial activity in the human visual cortex. Corroborating the predictions, the decoded distributions have a bimodal shape, with peaks that predict the direction and magnitude of behavioral errors. Interestingly, we observe similar bimodality in the distribution of the observers' behavioral responses across trials. Together, these results suggest that observers use spatial orientation signals when estimating motion direction. More broadly, our findings indicate that the cortical representation of low-level visual features, such as motion direction, can reflect a combination of several qualitatively distinct signals.

But Still It Moves: Static Image Statistics Underlie How We See Motion

Seeing movement promotes survival. It results from an uncertain interplay between evolution and experience, making it hard to isolate the drivers of computational architectures found in brains. Here we seek insight into motion perception using a neural network (MotionNet) trained on moving images to classify velocity. The network recapitulates key properties of motion direction and speed processing in biological brains, and we use it to derive, and test, understanding of motion (mis)perception at the computational, neural, and perceptual levels. We show that diverse motion characteristics are largely explained by the statistical structure of natural images, rather than motion per se. First, we show how neural and perceptual biases for particular motion directions can result from the orientation structure of natural images. Second, we demonstrate an interrelation between speed and direction preferences in (macaque) MT neurons that can be explained by image autocorrelation. Third, we show that natural image statistics mean that speed and image contrast are related quantities. Finally, using behavioral tests (humans, both sexes), we show that it is knowledge of the speed-contrast association that accounts for motion illusions, rather than the distribution of movements in the environment (the “slow world” prior) as premised by Bayesian accounts. Together, this provides an exposition of motion speed and direction estimation, and produces concrete predictions for future neurophysiological experiments. More broadly, we demonstrate the conceptual value of marrying artificial systems with biological characterization, moving beyond “black box” reproduction of an architecture to advance understanding of complex systems, such as the brain.

SIGNIFICANCE STATEMENT Using an artificial systems approach, we show that physiological properties of motion can result from natural image structure. In particular, we show that the anisotropic distribution of orientations in natural statistics is sufficient to explain the cardinal bias for motion direction. We show that inherent autocorrelation in natural images means that speed and direction are related quantities, which could shape the relationship between speed and direction tuning of MT neurons. Finally, we show that movement speed and image contrast are related in moving natural images, and that motion misperception can be explained by this speed-contrast association not a “slow world” prior.

Shape representation modulating the effect of motion on visual search performance

The effect of motion on visual search has been extensively investigated, but that of uniform linear motion of display on search performance for tasks with different target-distractor shape representations has been rarely explored. The present study conducted three visual search experiments. In Experiments 1 and 2, participants finished two search tasks that differed in target-distractor shape representations under static and dynamic conditions. Two tasks with clear and blurred stimuli were performed in Experiment 3. The experiments revealed that target-distractor shape representation modulated the effect of motion on visual search performance. For tasks with low target-distractor shape similarity, motion negatively affected search performance, which was consistent with previous studies. However, for tasks with high target-distractor shape similarity, if the target differed from distractors in that a gap with a linear contour was added to the target, and the corresponding part of distractors had a curved contour, motion positively influenced search performance. Motion blur contributed to the performance enhancement under dynamic conditions. The findings are useful for understanding the influence of target-distractor shape representation on dynamic visual search performance when display had uniform linear motion.

Motion deblurring during pursuit tracking improves spatial-interval acuity

The extent of perceived blur produced by a moving retinal image is less when the image motion occurs during pursuit eye movements compared to fixation. This study examined the effect of this reduced perception of motion blur during pursuit on spatial-interval acuity. Observers judged during pursuit at 4 or 8 deg/s whether the horizontal separation between two stationary lines was larger or smaller than a standard. Three different line separations were tested for each pursuit velocity. Each observer performed these judgments also during fixation, for spatial-interval stimuli that moved with the same mean and standard deviation of speeds as the distribution of eye velocities during pursuit. Spatial-interval acuity was better during pursuit than fixation for small or intermediate line separations. The results indicate that a reduction of perceived motion blur during pursuit eye movements can lead to improved visual performance.

The perception of motion smear during eye and head movements

Because the visual system integrates information across time, an image that moves on the retina would be expected to be perceived as smeared. In this article, we summarize the previous evidence that human observers perceive a smaller extent of smear when retinal image motion results from an eye or head movement, compared to when a physically moving target generates comparable image motion while the eyes and head are still. This evidence indicates that the reduction of perceived motion smear is asymmetrical, occurring only for targets that move against the direction of an eye or head movement. In addition, we present new data to show that no reduction of perceived motion smear occurs for targets that move in either direction during a visually-induced perception of self motion. We propose that low-level extra-retinal eye- and head-movement signals are responsible for the reduction of perceived motion smear, by decreasing the duration of the temporal impulse response. Although retinal as well as extra-retinal mechanisms can reduce the extent of perceived motion smear, available evidence suggests that improved visual functioning may occur only when an extra-retinal mechanism reduces the perception of smear.

Integration across Time Determines Path Deviation Discrimination for Moving Objects

BACKGROUND

Human vision is vital in determining our interaction with the outside world. In this study we characterize our ability to judge changes in the direction of motion of objects-a common task which can allow us either to intercept moving objects, or else avoid them if they pose a threat.

METHODOLOGY/PRINCIPAL FINDINGS

Observers were presented with objects which moved across a computer monitor on a linear path until the midline, at which point they changed their direction of motion, and observers were required to judge the direction of change. In keeping with the variety of objects we encounter in the real world, we varied characteristics of the moving stimuli such as velocity, extent of motion path and the object size. Furthermore, we compared performance for moving objects with the ability of observers to detect a deviation in a line which formed the static trace of the motion path, since it has been suggested that a form of static memory trace may form the basis for these types of judgment. The static line judgments were well described by a 'scale invariant' model in which any two stimuli which possess the same two-dimensional geometry (length/width) result in the same level of performance. Performance for the moving objects was entirely different. Irrespective of the path length, object size or velocity of motion, path deviation thresholds depended simply upon the duration of the motion path in seconds.

CONCLUSIONS/SIGNIFICANCE

Human vision has long been known to integrate information across space in order to solve spatial tasks such as judgment of orientation or position. Here we demonstrate an intriguing mechanism which integrates direction information across time in order to optimize the judgment of path deviation for moving objects.

The attenuation of perceived motion smear during combined eye and head movements

The extent of perceived motion smear was compared for targets that underwent similar velocities of retinal image motion during the vestibulo-ocular reflex (VOR) in the dark, the visually enhanced VOR (VVOR), VOR suppression, and fixation. Compared to the extent of perceived motion smear during fixation, observers reported significantly less smear when the target moved either in the same direction or against the direction of the head movement during the VVOR and VOR. We also confirmed a previous finding that perceived smear is attenuated asymmetrically during VOR suppression, with attenuation occurring primarily for targets that move against the direction of the observer's head motion. The results support the hypothesis that the visual system employs extra-retinal signals that accompany eye and head movements to reduce the perception of motion smear for targets that move physically in the opposite direction of eye and/or head movements.