Systematic eye movements do not account for the perception of motion during attentive tracking.

It has been suggested that attention can disambiguate stimuli that have equal motion energy in opposite directions (e.g. a counterphasing grating), such that a clear motion direction is perceived. The direction of this movement is determined by the observer and can be changed at will. Assuming that the responses of front-end motion detectors are equal for the two opponent directions, it has been proposed that the unambiguous motion perceived with attentive tracking arises from an independent mechanism that monitors the shifts of attention directed to the moving feature of interest. However, while perceiving motion under attentive tracking conditions, observers often report a strong impression that they are making eye movements. In this study, we investigated whether systematic eye movements are present during attentive tracking and, as a result, could be responsible for the subjective experience of movement. We had observers track an object in smooth motion, apparent motion and ambiguous motion, either with eye movements or with attention. The results show that there are negligible eye movements during attentive tracking, which are neither systematic nor correlated with the stimulus. Given that neither eye movements nor retinal image motion can account for subjectively perceived motion, as well as the absence of any other plausible explanation, we find it tempting evidence for an earlier suggestion that the percept of movement must arise from a specialized mechanism.

Visual motion and the human brain: what has neuroimaging told us?

Recently, neuroimaging techniques have been applied to the study of human motion perception, complementing established techniques such as psychophysics, neurophysiology and neuropsychology. Because vision, particularly motion perception, has been studied relatively extensively, it provides an interesting case study to examine the contributions and limitations of neuroimaging to cognitive neuroscience. We suggest that in the domain of motion perception neuroimaging has: (1) revealed an extensive network of motion areas throughout the human brain, in addition to the well-studied motion complex (MT+); (2) verified and extended findings from other techniques; (3) suggested extensive top-down influences on motion perception; and (4) allowed experimenters to examine the neural correlates of awareness. We discuss these contributions, along with limitations and future directions for the neuroimaging of motion.

Slow and fast visual motion channels have independent binocular-rivalry stages.

We have previously reported a transparent motion after-effect indicating that the human visual system comprises separate slow and fast motion channels. Here, we report that the presentation of a fast motion in one eye and a slow motion in the other eye does not result in binocular rivalry but in a clear percept of transparent motion. We call this new visual phenomenon 'dichoptic motion transparency' (DMT). So far only the DMT phenomenon and the two motion after-effects (the 'classical' motion after-effect, seen after motion adaptation on a static test pattern, and the dynamic motion after-effect, seen on a dynamic-noise test pattern) appear to isolate the channels completely. The speed ranges of the slow and fast channels overlap strongly and are observer dependent. A model is presented that links after-effect durations of an observer to the probability of rivalry or DMT as a function of dichoptic velocity combinations. Model results support the assumption of two highly independent channels showing only within-channel rivalry, and no rivalry or after-effect interactions between the channels. The finding of two independent motion vision channels, each with a separate rivalry stage and a private line to conscious perception, might be helpful in visualizing or analysing pathways to consciousness.

Limits of attentive tracking reveal temporal properties of attention.

The maximum speed for attentive tracking of targets was measured in three types of (radial) motion displays: ambiguous motion where only attentive tracking produced an impression of direction, apparent motion, and continuous motion. The upper limit for tracking (about 50 deg s-1) was an order of magnitude lower than the maximum speed at which motion can be perceived for some of these stimuli. In all cases but one, the ultimate limit appeared to be one of temporal frequency, 4-8 Hz, not retinal speed or rotation rate. It was argued that this rate reflects the temporal resolution of attention, the maximum rate at which events can be individuated from those that precede or follow them. In one condition, evidence was also found for a speed limit to attentive tracking, a maximum rate at which attention could follow a path around the display.

Independent aftereffects of attention and motion.

In the motion aftereffect (MAE), a stationary pattern appears to move in the opposite direction to previously viewed motion. Here we report an MAE that is observed for a putatively high level of visual analysis-attentive tracking. These high-level MAEs, visible on dynamic (but not static) tests, suggest that attentive tracking does not simply enhance low-level motion signals but, rather, acts at a subsequent stage. MAEs from tracking (1) can overrule competing MAEs from adaptation to low-level motion, (2) can be established opposite to low-level MAEs seen on static tests at the same location, and (3), most striking, are specific to the overall direction of object motion, even at nonadapted locations. These distinctive properties suggest MAEs from attentive tracking can serve as valuable probes for understanding the mechanisms of high-level vision and attention.

Integration after adaptation to transparent motion: static and dynamic test patterns result in different aftereffect directions.

One of the many interesting questions in motion aftereffect (MAE) research is concerned with the location(s) along the pathway of visual processing at which certain perceptual manifestations of this illusory motion originate. One such manifestation is the unidirectionality of the MAE after adaptation to moving plaids or transparent motion. This unidirectionality has led to the suggestion that the origin of this MAE might be a single source (gain control) located at, or beyond areas that are believed to be responsible for the integration of motion signals. In this report we present evidence against this suggestion using a simple experiment. For the same adaptation pattern, which consisted of two orthogonally moving transparent patterns with different speeds, we show that the direction of the resulting unidirectional MAE depends on the nature of the test stimulus. We used two kinds of test patterns: static and dynamic. For exactly the same adaptation conditions, the difference in MAE direction between testing with static and dynamic patterns can be as large as 50 degrees. This finding suggests that this MAE is not just a perceptual manifestation of a passive recovery of adapted motion sensors but an active integrative process using the output of different gain controls. A process which takes place after adaptation. These findings are in line with the idea that there are several sites of adaptation along the pathway of visual motion processing and that the nature of the test pattern determines the fate of our perceptual experience of the MAE.

Motion aftereffect of combined first-order and second-order motion.

When, after prolonged viewing of a moving stimulus, a stationary (test) pattern is presented to an observer, this results in an illusory movement in the direction opposite to the adapting motion. Typically, this motion aftereffect (MAE) does not occur after adaptation to a second-order motion stimulus (i.e. an equiluminous stimulus where the movement is defined by a contrast or texture border, not by a luminance border). However, a MAE of second-order motion is perceived when, instead of a static test pattern, a dynamic test pattern is used. Here, we investigate whether a second-order motion stimulus does affect the MAE on a static test pattern (sMAE), when second-order motion is presented in combination with first-order motion during adaptation. The results show that this is indeed the case. Although the second-order motion stimulus is too weak to produce a convincing sMAE on its own, its influence on the sMAE is of equal strength to that of the first-order motion component, when they are adapted to simultaneously. The results suggest that the perceptual appearance of the sMAE originates from the site where first-order and second-order motion are integrated.

Aftereffect of high-speed motion.

A visual illusion known as the motion aftereffect is considered to be the perceptual manifestation of motion sensors that are recovering from adaptation. This aftereffect can be obtained for a specific range of adaptation speeds with its magnitude generally peaking for speeds around 3 deg s-1. The classic motion aftereffect is usually measured with a static test pattern. Here, we measured the magnitude of the motion aftereffect for a large range of velocities covering also higher speeds, using both static and dynamic test patterns. The results suggest that at least two (sub)populations of motion-sensitive neurons underlie these motion aftereffects. One population shows itself under static test conditions and is dominant for low adaptation speeds, and the other is prevalent under dynamic test conditions after adaptation to high speeds. The dynamic motion aftereffect can be perceived for adaptation speeds up to three times as fast as the static motion aftereffect. We tested predictions that follow from the hypothesised division in neuronal substrates. We found that for exactly the same adaptation conditions (oppositely directed transparent motion with different speeds), the aftereffect direction differs by 180 degrees depending on the test pattern. The motion aftereffect is opposite to the pattern moving at low speed when the test pattern is static, and opposite to the high-speed pattern for a dynamic test pattern. The determining factor is the combination of adaptation speed and type of test pattern.

The motion aftereffect.

The motion aftereffect is a powerful illusion of motion in the visual image caused by prior exposure to motion in the opposite direction. For example, when one looks at the rocks beside a waterfall they may appear to drift upwards after one has viewed the flowing water for a short period-perhaps 60 seconds. The illusion almost certainly originates in the visual cortex, and arises from selective adaptation in cells tuned to respond to movement direction. Cells responding to the movement of the water suffer a reduction in responsiveness, so that during competitive interactions between detector outputs, false motion signals arise. The result is the appearance of motion in the opposite direction when one later gazes at the rocks. The adaptation is not confined to just one population of cells, but probably occurs at several cortical sites, reflecting the multiple levels of processing involved in visual motion analysis. The effect is unlikely to be caused by neural fatigue; more likely, the MAE and similar adaptation effects provide a form of error-correction or coding optimization, or both.

Linking lower and higher stages of motion processing?

The spatial frequency selectivity of motion detection mechanisms can be measured by comparing the magnitude of motion aftereffects (MAEs) as a function of the spatial frequency of the adapting and test gratings. For static test gratings, narrow spatial frequency tuning has been reported in a number of studies. However, for dynamic test patterns, reports have been conflicting. Ashida & Osaka [(1994). Perception, 23, 1313-1320] found no tuning whereas Bex et al. [(1996) Vision Research, 36, 2721-2727] reported a narrow tuning. The main difference between the two studies was the temporal frequency of the test pattern. In this study we measured the spatial frequency tuning of the MAE using test patterns for a range of temporal frequencies. The results confirmed that there was narrow spatial frequency tuning when the test pattern was counterphasing at a low temporal frequency. However, the spatial frequency selectivity broadened as the temporal frequency of the test pattern was increased.

Responses of complex cells in cat area 17 to apparent motion of random pixel arrays.

The characteristics of directionally selective cells in area 17 of the cat are studied using moving random pixel arrays (RPAs) with 50% white and 50% black pixels. The apparent motion stimulus is similar to that used in human psychophysics [Fredericksen et al. (1993). Vision Research, 33, pp. 1193-1205]. We compare motion sensitivity measured with single-step pixel lifetimes and unlimited pixel lifetimes. A motion stimulus with a single-step pixel lifetime contains directional motion energy primarily at one combination of spatial displacement and temporal delay. We recorded the responses of complex cells to different combinations of displacement and delay to describe their spatio-temporal correlation characteristics. The response to motion of RPAs with unlimited lifetime is strongest along the preferred speed line in a delay vs displacement size diagram. When using an RPA with a single-step pixel lifetime, the cells are responsive to a much smaller range of spatial displacements and temporal delays of the stimulus. The maximum displacement that still gives a directionally selective response is larger when the preferred speed of the cell is higher. It is on average about three times smaller than the receptive field size.

How big is a Gabor patch, and why should we care?

We propose a two-parameter model for the perceived size (spatial extent) of a Gaussian-windowed, drifting sinusoidal luminance pattern (a Gabor patch) based on the simple assumption that perceived size is determined by detection threshold for the sinusoidal carrier. Psychophysical measures of perceived size vary with peak contrast, Gaussian standard deviation, and carrier spatial frequency in a manner predicted by the model. At suprathreshold peak contrasts Gabor perceived size is relatively unaffected by systemic noise but varies in a manner that is consistent with the influence of local contrast gain control. However, at and near threshold, systemic noise plays a major role in determining perceived size. The data and the model indicate that measures of contrast threshold using Gaussian-windowed stimuli (or any other nonflat contrast window) are determined not just by contrast response of the neurons activated by the stimulus but also by integration of that activation over a noisy, contrast-dependent extent of the stimulus in space and time. Thus, when we wish to measure precisely the influence of spatial and temporal integration on threshold, we cannot do so by combining contrast threshold measures with Gaussian-windowed stimuli.

Pitfalls in estimating motion detector receptive field geometry.

A number of psychophysical investigations have used spatial-summation methods to estimate the receptive field (RF) geometry of motion detectors by exploring how psychophysical thresholds change with stimulus height and/or width. This approach is based on the idea that an observer's ability to detect motion direction is strongly determined by the relationship between the stimulus geometry (height and width) and the RF of the activated motion detectors. Our results show that previous estimates of RF geometry can depend significantly on stimulus position in the visual field as well as on the stimulus height-to-width ratio. The data further show that RF estimates depend on the stimulus in a manner that is inconsistent with basic predictions derived from current motion detector models. Hence previous estimates of height, width, and height-to-width ratios of motion detector RFs are inaccurate and unreliable. This inaccuracy/unreliability is attributed to a number of sources. These include incorrect fixed-parameter values in model fits, as well as the confounding of physiological spatial summation area through combined use of contrast thresholds and Gaussian-windowed stimuli. A third source of error is an asymmetric variation of spatiotemporal correlation in the stimulus as either its height or width is varied (and the other dimension held constant). Most importantly, a fourth source of unreliability is attributed to the existence of a nonlinear, nonmonotonic distribution of motion detectors in the visual field that has been previously described and is a natural result of visual anatomy.

Temporal and spatial frequency tuning of the flicker motion aftereffect.

The motion aftereffect (MAE) was used to study the temporal and spatial frequency selectivity of the visual system at supra-threshold contrasts. Observers adapted to drifting sine-wave gratings of a range of spatial and temporal frequencies. The magnitude of the MAE induced by the adaptation was measured with counterphasing test gratings of a variety of spatial and temporal frequencies. Independently of the spatial or temporal frequency of the adapting grating, the largest MAE was found with slowly counterphasing test gratings (at approximately 0.125-0.25 Hz). The largest MAEs were also found when the test grating was of similar spatial frequency to that of the adapting grating, even at very low spatial frequencies (0.125 c/deg). These data suggest that MAEs are dominated by a single, low-pass temporal frequency mechanism and by a series of band-pass spatial frequency mechanisms. The band-pass spatial frequency tuning even at low spatial frequencies suggests that the "lowest adaptable channel" concept [Cameron et al. (1992). Vision Research, 32, 561-568] may be an artifact of disadvantaged low spatial frequencies using static test patterns.

Responses of complex cells in area 17 of the cat to bi-vectorial transparent motion.

We examined the responses to transparent motion of complex cells in cat area 17 which show directional selectivity to moving random pixel arrays (RPAs). The response to an RPA moving in the cell's preferred direction is inhibited when a second RPA is transparently moving in another direction. The inhibition by the second pattern is quantified as a function of its direction. The response to a pattern moving in the preferred direction is never completely suppressed, not even when a second pattern is moving transparently in the opposite direction. To the extent that supra-spontaneous firing rates signal the presence of the optimal velocity vector, these cells therefore still signal the presence of this line-label stimulus despite additional opposing, or otherwise directed, motion components. The results confirm previous suggestions that, for the computation of motion energy in cat area 17 complex cells, a full opponent stage is not plausible. Furthermore, we show that the response to a combination of two motion vectors can be predicted by the average of the responses to the individual components.

Directional motion sensitivity under transparent motion conditions.

We measured directional sensitivity to a foreground pattern while an orthogonally directed background pattern was present under transparent motion conditions. For both foreground and background pattern, the speed was varied between 0.5 and 28 deg sec-1. A multi-step paradigm was employed which results in a better estimation of the suppressive or facilitatory effects than previously applied single-step methods (e.g. measuring Dmax or Dmin). Moreover, our method gives insight into the interactions for a wide range of speed and not just the extreme motion thresholds (the D-values). We found that high background speeds have an inhibitory effect on the detection of a range of high foreground speeds and low background speeds have an inhibitory effect on a range of low foreground speeds. Intermediate background pattern speeds inhibit the detection of both low and high foreground pattern speeds and do so in a systemic manner.

Monocular mechanisms determine plaid motion coherence.

Although the neural location of the plaid motion coherence process is not precisely known, the middle temporal (MT) cortical area has been proposed as a likely candidate. This claim rests largely on the neurophysiological findings showing that in response to plaid stimuli, a subgroup of cells in area MT responds to the pattern direction, whereas cells in area V1 respond only to the directions of the component gratings. In Experiment 1, we report that the coherent motion of a plaid pattern can be completely abolished following adaptation to a grating which moves in the plaid direction and has the same spatial period as the plaid features (the so-called "blobs"). Interestingly, we find this phenomenon is monocular: monocular adaptation destroys plaid coherence in the exposed eye but leaves it unaffected in the other eye. Experiment 2 demonstrates that adaptation to a purely binocular (dichoptic) grating does not affect perceived plaid coherence. These data suggest several conclusions: (1) that the mechanism determining plaid coherence responds to the motion of plaid features, (2) that the coherence mechanism is monocular, and thus (3), that it is probably located at a relatively low level in the visual system and peripherally to the binocular mechanisms commonly presumed to underlie two-dimensional (2-D) motion perception. Experiment 3 examines the spatial tuning of the monocular coherence mechanism and our results suggest it is broadly tuned with a preference for lower spatial frequencies. In Experiment 4, we examine whether perceived plaid direction is determined by the motion of the grating components or the features. Our data strongly support a feature-based model.

Recovery from adaptation for dynamic and static motion aftereffects: evidence for two mechanisms.

The motion aftereffect (MAE) is an illusory drift of a physically stationary pattern induced by prolonged viewing of a moving pattern. Depending on the nature of the test pattern the MAE can be phenomenally different. This difference in appearance has led to the suggestion that different underlying mechanisms may be responsible and several reports show that this might be the case. Here, we tested whether differences in MAE duration obtained with stationary test patterns and dynamic test patterns can be explained by a single underlying mechanism. We find the results support the existence of (at least) two mechanisms. The two mechanisms show different characteristics: the static MAE (i.e. the MAE tested with a static test pattern) is almost completely stored when the static test is preceded by a dynamic test; in contradistinction, the dynamic MAE is not stored when dynamic testing is preceded by a static test pattern.

On the ancient history of the direction of the motion aftereffect.

Scientists agree that Aristotle in his Parva Naturalia was the first to report a visual illusion known as the motion aftereffect (MAE). But there is less consensus as to who was the first to report the direction of the MAE. According to some, Aristotle only described the phenomenon without saying anything about its direction. Others have defended the position that Aristotle did report a direction, but the wrong one. Therefore, it has been suggested that Lucretius in his poem De Rerum Natura was the first to report the correct direction of the MAE. In this paper it is shown why and how it can be inferred that Aristotle did not write about the direction of the MAE, only about its occurrence. It is also argued that it is indeed likely that Lucretius was the first person to report the direction of the MAE. However, this is not as obvious as it might appear at first sight.