The measurement of visual motion

Interaction of retinal image and eye velocity in motion perception

When we move our eyes, why does the world look stable even as its image flows across our retinas, and why do afterimages, which are stationary on the retinas, appear to move? Current theories say this is because we perceive motion by summation: if an object slips across the retina at r degrees/s while the eye turns at e degrees/s, the object's perceived velocity in space should be r + e. We show that activity in MT+, the visual-motion complex in human cortex, does reflect a mix of r and e rather than r alone. But we show also that, for optimal perception, r and e should not summate; rather, the signals coding e interact multiplicatively with the spatial gradient of illumination.

The directional tuning of the barber-pole illusion

In order to study the integration of local motion signals in the human visual system, we measured directional tuning curves for the barber-pole illusion by varying two crucial aspects of the stimulus layout independently across a wide a range in the same experiment. These were the orientation of the grating presented behind the rectangular aperture and the aspect ratio of the aperture, which in combination determine the relative contributions of local motion signals perpendicular to the gratings and parallel to the aperture borders, respectively. The strength of the illusion, ie the tendency to perceive motion along the major axis of the aperture, obviously depends on the spatial layout of the aperture, but also on grating orientation. Subjects were asked which direction they perceived and how compelling their motion percept was, revealing different strategies of the visual system to deal with the barber-pole stimulus. Some individuals respond strongly to the unambiguous motion information at the boundaries, leading to multistable percepts and multimodal distributions of responses. Others tend to report intermediate directions, apparently being less influenced by the actual boundaries. The general pattern of deviations from the motion direction perpendicular to grating orientation--a decrease with aspect ratio approaching unity (ie square-shaped apertures) and with gratings approaching parallel orientation to the shorter aperture boundary--is discussed in the context of simple phenomenological models of motion integration. The best fit between model predictions and experimental data is found for an interaction between two stimulus parameters: (i) cycle ratio, which is the sine-wave gratings equivalent of the terminator ratio for line gratings, describing the effects from the aperture boundaries, and (ii) the grating orientation, responsible for perpendicular motion components, which describes the influence of motion signals from inside the aperture. This suggests that the most simple cycle (terminator) ratio explanation cannot fully account for the quantitative properties of the barber-pole illusion.

A one step motion detection circuitry

A model of motion and direction detection is presented as well as results from a computer simulation of the model. The model is based on cooperative computations which allows an extremely simple architecture. Furthermore, it involves only one logical step in its computations even though Hubel and others have argued that motion detection requires at least two. This is made possible by not including the initial detection of movement. The model simply updates prior detections which is a simpler problem. New movement can be captured by the system by means of spontaneous activity in the movement selective cells. The cost is that some iterations are required to capture new movement. On the other hand, the model handles noisy input very well. The reason for this is that movement is viewed as a stable phenomenon rather than change.

Cortical potentials reflecting motion processing in humans

Motion processing is a fundamental task of visual systems, and in the monkey cortical areas can be identified which appear to be functionally specialized for motion processing. The human visual system is expected to be organized in a similar way. A noninvasive method to study the functional organization of the visual cortex is the recording of scalp potentials generated by neural activity of the underlying cortical areas. In the present study, we recorded slow cortical potentials from normal subjects in order to investigate how motion stimuli are processed. Three classes of object motion were realized as random dot kinematograms, namely Fourier motion, drift-balanced motion, and theta motion, because they require mechanisms of increasing complexity in order to be extracted. Large-field motion and counterphase flicker were used as control stimuli. Three basic results were obtained: (1) The responses evoked by the three classes of object motion do not differ significantly in their course and distribution of activation. (2) The distributions of cortical activation evoked by object motion, and the control stimuli are different. During object motion the maximum activation occurs over the superior parietal cortex. Large-field motion activates occipital and parietal locations to the same extent, and during counterphase flicker the activity is maximum over the occipital lobe. Thus, the parietal slow potentials are interpreted to specifically reflect the cortical processing of object motion. (3) The time course of the activation reflects changes in the spatial position of the object: the amplitude of a transient negative component (TNC) which occurs 240 ms after motion onset decreases with increasing eccentricity of motion onset. The consecutive sustained negative component (SNC), which persists until the movement stops, decreases during centrifugal and increases during centripetal object motion. These results can be understood on the basis of physiological and anatomical knowledge about the mapping of the visual field on the cortex.

Two-Dimensional Motion Perception in Flies

We study two-dimensional motion perception in flies using a semicircular visual stimulus. Measurements of both the H1-neuron and the optomotor response are consistent with a simple model supposing spatial integration of the outputs of correlation-type motion detectors. In both experiment and model, there is substantial H1 and horizontal (yaw) optomotor response to purely vertical motion of the stimulus. We conclude that the fly's optomotor response to a two-dimensional pattern, depending on its structure, may deviate considerably from the direction of pattern motion.

Conditions for the detection of coherent motion

Previous studies have suggested that human motion perception involves at least two different detection stages: an orientation selective or component motion stage and a combination stage where selectivity to the coherent motion of a pattern, e.g. a plaid is established. These studies are inconclusive as to the motion detection process per se. Here we provide evidence that the motion detectors involved are of the correlation type. We determined critical values for the temporal and spatial modulation of the stimulus structure where the motion of the stimulus is no longer visible. Our results indicate that the spatial parameters of plaid- and component-motion detectors are identical but that the critical temporal modulation period is shorter for plaid-motion detectors. The results are discussed with respect to recent neurophysiological and psychophysical evidence for the two-stage motion detection model.

Principles of visual motion detection

Motion information is required for the solution of many complex tasks of the visual system such as depth perception by motion parallax and figure/ground discrimination by relative motion. However, motion information is not explicitly encoded at the level of the retinal input. Instead, it has to be computed from the time-dependent brightness patterns of the retinal image as sensed by the two-dimensional array of photoreceptors. Different models have been proposed which describe the neural computations underlying motion detection in various ways. To what extent do biological motion detectors approximate any of these models? As will be argued here, there is increasing evidence from the different disciplines studying biological motion vision, that, throughout the animal kingdom ranging from invertebrates to vertebrates including man, the mechanisms underlying motion detection can be attributed to only a few, essentially equivalent computational principles. Motion detection may, therefore, be one of the first examples in computational neurosciences where common principles can be found not only at the cellular level (e.g., dendritic integration, spike propagation, synaptic transmission) but also at the level of computations performed by small neural networks.

The aperture problem--I. Perception of nonrigidity and motion direction in translating sinusoidal lines

To examine how local velocities from different regions of the visual field combine to form a coherent motion percept, we subjected a sinusoidal line stimulus to translational motion. Horizontal movement of a sinewave line along its axial direction is perceived as nonrigid if the angle at the zero crossing is smaller than a critical angle of about 15 deg. This angle is independent of spatial scale and the number of sinusoidal cycles. To extend the applicability of this concept of angle, we developed a mathematical model to predict an observer's sensitivity to small changes in motion direction based on two assumptions: (1) the computed velocity signal is obtained from the intersection of constraint lines defined by local velocity components, (2) local velocity components are contaminated by noise. Measurement of directional discrimination thresholds of moving targets confirmed our expectations. Thresholds varied as a function of the angle of the local contour independent of spatial scale and in quantitative accord with our assumptions.

Maximizing rigidity: the incremental recovery of 3-D structure from rigid and nonrigid motion

The human visual system can extract 3-D shape information of unfamiliar moving objects from their projected transformations. Computational studies of this capacity have established that 3-D shape can be extracted correctly from a brief presentation, provided the moving objects are rigid. The human visual system requires a longer temporal extension, but it can cope with considerable deviations from rigidity. It is shown how the 3-D structure of rigid as well as nonrigid objects can be recovered by maintaining an internal model of the viewed object and modifying it at each instant by the minimal nonrigid change that is sufficient to account for the observed transformation. The results of applying this incremental rigidity scheme to rigid and nonrigid objects in motion are described and compared with human perception.