Static Motion Aftereffect Research Articles

Dissociating representations of affect and motion in visual cortices.

While a delicious dessert being presented to us may elicit strong feelings of happiness and excitement, the same treat falling slowly away can lead to sadness and disappointment. Our emotional response to the item depends on its visual motion direction. Despite this importance, it remains unclear whether (and how) cortical areas devoted to decoding motion direction represents or integrates emotion with perceived motion direction. Motion-selective visual area V5/MT+ sits, both functionally and anatomically, at the nexus of dorsal and ventral visual streams. These pathways, however, differ in how they are modulated by emotional cues. The current study was designed to disentangle how emotion and motion perception interact, as well as use emotion-dependent modulation of visual cortices to understand the relation of V5/MT+ to canonical processing streams. During functional magnetic resonance imaging (fMRI), approaching, receding, or static motion after-effects (MAEs) were induced on stationary positive, negative, and neutral stimuli. An independent localizer scan was conducted to identify the visual-motion area V5/MT+. Through univariate and multivariate analyses, we demonstrated that emotion representations in V5/MT+ share a more similar response profile to that observed in ventral visual than dorsal, visual structures. Specifically, V5/MT+ and ventral structures were sensitive to the emotional content of visual stimuli, whereas dorsal visual structures were not. Overall, this work highlights the critical role of V5/MT+ in the representation and processing of visually acquired emotional content. It further suggests a role for this region in utilizing affectively salient visual information to augment motion perception of biologically relevant stimuli.

Contribution of the slow motion mechanism to global motion revealed by an MAE technique

Two different motion mechanisms have been identified with motion aftereffect (MAE). (1) A slow motion mechanism, accessed by a static MAE, is sensitive to high-spatial and low-temporal frequency; (2) a fast motion mechanism, accessed by a flicker MAE, is sensitive to low-spatial and high-temporal frequency. We examined their respective responses to global motion after adapting to a global motion pattern constructed of multiple compound Gabor patches arranged circularly. Each compound Gabor patch contained two gratings at different spatial frequencies (0.53 and 2.13 cpd) drifting in opposite directions. The participants reported the direction and duration of the MAE for a variety of global motion patterns. We discovered that static MAE durations depended on the global motion patterns, e.g., longer MAE duration to patches arranged to see rotation than to random motion (Exp 1), and increase with global motion strength (patch number in Exp 2). In contrast, flicker MAEs durations are similar across different patterns and adaptation strength. Further, the global integration occurred at the adaptation stage, rather than at the test stage (Exp 3). These results suggest that slow motion mechanism, assessed by static MAE, integrate motion signals over space while fast motion mechanisms do not, at least under the conditions used.

Static motion aftereffects when the spatial frequency of the adaptation and test stimuli is same under continuous flash suppression

Static motion aftereffects when the spatial frequency of the adaptation and test stimuli is same under continuous flash suppression

Global-motion aftereffect does not depend on awareness of the adapting motion direction

It has been shown that humans cannot perceive more than three directions from a multidirectional motion stimulus. However, it remains unknown whether adapting to such imperceptible motion directions could generate motion aftereffects (MAEs). A series of psychophysical experiments were conducted to address this issue. Using a display consisting of randomly oriented Gabors, we replicated previous findings that observers were unable to perceive the global directions embedded in a five-direction motion pattern. However, adapting to this multidirectional pattern induced both static and dynamic MAEs, despite the fact that observers were unaware of any global motion directions during adaptation. Furthermore, by comparing the strengths of the dynamic MAEs induced at different levels of motion processing, we found that spatial integration of local illusory signals per se was sufficient to produce a significant global MAE. These psychophysical results show that the generation of a directional global MAE does not require conscious perception of the global motion during adaptation.

Motion aftereffect duration is not changed by perceptual learning: Evidence against the representation modification hypothesis

The representation modification hypothesis of perceptual learning attributes the practice-induced improvements in sensitivity and/or discriminability to changes in the early visual areas. We used motion aftereffects (MAE) to probe the representations of motion direction. In two experiments, four practice sessions on a fine direction-discrimination task caused large stimulus-specific improvements in d′ but no significant stimulus-specific changes in either static or dynamic MAE duration at posttest relative to a pretest. Power analysis indicated that the data were approximately 100 times more likely given the hypothesis of no MAE change than the hypothesis of a 10% relative change. In light of converging evidence in the MAE literature, this suggests that little or no change occurred in the cortical representations of visual motion up to and including area MT. The task specificity of the learning effect challenges the representation modification hypothesis and supports an alternative—selective reweighting.

Attention Alters Feature Space in Motion Processing

Attending to a particular feature modulates the activity of neurons throughout the visual field with the result that relevant features are enhanced while irrelevant features are suppressed. Do these modulatory influences merely lead to a gating of relevant features, or does attention have a direct impact on the representation of feature space, leading to a different percept depending on the content of attention? We observed that direction estimates of the static motion aftereffect drastically change when human observers attend to a stimulus whose motion direction differs from the one of the adaptor. This observation suggests that feature-based attention might operate by local magnifications of feature space between relevant and irrelevant features.

Motion mechanisms with different spatiotemporal characteristics identified by an MAE techniquewith superimposed gratings

We investigated spatiotemporal characteristics of motion mechanisms using a new type of motion aftereffect (MAE) we found. Our stimulus comprised two superimposed sinusoidal gratings with different spatial frequencies. After exposure to the moving stimulus, observers perceived the MAE in the static test in the direction opposite to that of the high spatial frequency grating even when low spatial frequency motion was perceived during adaptation. In contrast, in the flicker test, the MAE was perceived in the direction opposite to that of the low spatial frequency grating. These MAEs indicate that two different motion systems contribute to motion perception and can be isolated by using different test stimuli. Using a psychophysical technique based on the MAE, we investigated the differences between the two motion mechanisms. The results showed that the static MAE is the aftereffect of the motion system with a high spatial and low temporal frequency tuning (slow motion detector) and the flicker MAE is the aftereffect of the motion system with a low spatial and high temporal frequency tuning (fast motion detector). We also revealed that the two motion detectors differ in orientation tuning, temporal frequency tuning, and sensitivity to relative motion.

'Zigzag motion' goes in unexpected directions

In a novel 'zigzag motion' display, random dots made alternate long and short jumps, 10 mm downward and 1 mm to the right. The zigs and zags were either at right angles (differing by 90 degrees) or in opposite directions (180 degrees). The perceived direction of motion varied with the viewing distance or spatial scale. During close-up [or distant] viewing the display appeared to move in the direction of the short [or long] jumps. When the motion was stopped after 30 s, a motion aftereffect (MAE) was seen, driven by the short jumps but not the long jumps. Therefore, the perceived direction of motion was dissociated from its aftereffect. A picture rotated alternately 5 degrees clockwise (CW) and 1 degrees counterclockwise (CCW) and appeared to rotate jerkily CW. When stopped, a clockwise MAE was seen, appropriate to the small 1 degrees jumps. If the test field contained blurred, dynamic visual noise, the MAE was now CCW, appropriate to the large 5 degrees jumps; the large jumps drove the perceived motion direction and dynamic MAE, but the small jumps drove the static MAE. Winner-take-all competition between pathways tuned to fast and slow movements. Their independent adaptation gave opposite static and dynamic MAEs.

Storage for free: a surprising property of a simple gain-control model of motion aftereffects

If a motion aftereffect (MAE) for given adaptation conditions has a duration T s, and the eyes are closed after adaptation during a waiting period t w = T s before testing, an unexpected MAE of a `residual' duration T r T s is experienced. This effect is called `storage' and it is often quantified by a storage factor σ = T r T / T , which can reach values up to about 0.7–0.8. The phenomenon and its name have invited explanations in terms of inhibition of recovery during darkness. We present a model based on the opposite idea, that an effective test stimulus quickens recovery relative to darkness or other ineffective test stimuli. The model is worked out in mathematical detail and proves to explain `storage' data from the literature, on the static MAE (sMAE: an MAE experienced for static test stimuli). We also present results of a psychophysical experiment with moving random pixel arrays, quantifying storage phenomena both for the sMAE and the dynamic MAE (dMAE: an MAE experienced for a random dynamic noise test stimulus). Storage factors for the dMAE are lower than for the sMAE. Our model also gives an excellent description of these new data on storage of the dMAE. The term `storage' might therefore be a misnomer. If an effective test stimulus influences all direction tuned motion sensors indiscriminately and thus speeds up equalization of gains, one gets the storage phenomenon for free.

Storage for free: a surprising property of a simple gain-control model of motion aftereffects

If a motion aftereffect (MAE) for given adaptation conditions has a duration T s, and the eyes are closed after adaptation during a waiting period t w= T s before testing, an unexpected MAE of a `residual' duration T r T s is experienced. This effect is called `storage' and it is often quantified by a storage factor σ= T r T / T, which can reach values up to about 0.7–0.8. The phenomenon and its name have invited explanations in terms of inhibition of recovery during darkness. We present a model based on the opposite idea, that an effective test stimulus quickens recovery relative to darkness or other ineffective test stimuli. The model is worked out in mathematical detail and proves to explain `storage' data from the literature, on the static MAE (sMAE: an MAE experienced for static test stimuli). We also present results of a psychophysical experiment with moving random pixel arrays, quantifying storage phenomena both for the sMAE and the dynamic MAE (dMAE: an MAE experienced for a random dynamic noise test stimulus). Storage factors for the dMAE are lower than for the sMAE. Our model also gives an excellent description of these new data on storage of the dMAE. The term `storage' might therefore be a misnomer. If an effective test stimulus influences all direction tuned motion sensors indiscriminately and thus speeds up equalization of gains, one gets the storage phenomenon for free.

Static motion aftereffect does not modulate positional representations in early visual areas

A stationary stimulus is perceived to drift in the opposite direction after adaptation to a moving stimulus (static motion aftereffect (MAE)). It is commonly assumed that positional effects from the static motion aftereffect are mediated by early visual areas. Here we psychophysically showed that these positional effects did not modulate illusory line-tilt aftereffect (TAE). Since illusory contours seem to be represented at relatively early stages of visual hierarchy, we suggest that the neural substrates underlying the perception of static motion aftereffect and illusory contours are different.

Bivectorial transparent stimuli simultaneously adapt mechanisms at different levels of the motion pathway

The motion aftereffect (MAE) to drifting bivectorial stimuli, such as plaids, is usually univectorial and in a direction opposite to the pattern direction of the plaid. This is true for plaids that are perceived as coherent, but also for other plaids which are seen as transparent for most or all of the adaptation period. The underlying mechanisms of this MAE are still not well understood. In order to assess these mechanisms further, we measured static and dynamic MAEs and their interocular transfer (IOT). Adaptation stimuli were plaids with small (coherent) and large (transparent) angles between the directions of the component gratings and a horizontal grating, which were adjusted in spatial frequency and drift velocity so that the pattern speed and vertical periodicity remained constant. Test stimuli were horizontal static or counterphasing gratings with the same periodicity as the adaptation stimuli. MAE duration was measured for monocular, binocular and IOT conditions. All static MAEs were smallest for the transparent plaid and largest for the grating, while all dynamic MAEs were constant across adaptation stimuli. IOT was twice as big for dynamic MAEs as for static MAEs, and did not vary with the adaptation stimuli. Other adaptation stimuli were plaids that differed in intersection luminance, contrast or spatial frequency, resulting in different amounts of perceived coherence. MAEs and IOT did not vary with perceived coherence. The results suggest that the MAE for bivectorial stimuli consists of low-level adaptation (dependent on local component properties, small IOT), as well as high-level adaptation (dependent on global integrated pattern properties, large IOT), which can be measured independently with static and dynamic test stimuli.

A hierarchical structure of motion system revealed by interocular transfer of flicker motion aftereffects

Interocular transfer of the motion aftereffect (MAE) has been extensively investigated for the purpose of analysing the binocularity of the underlying motion mechanism. Previous studies unanimously reported that the transfer of the classical static MAE is partial, but there is a controversy as to whether the transfer of the flicker MAE (MAE measured using counterphase gratings) is partial or perfect. To gain insight into the discrepancy between studies, we investigated whether the interocular transfer of the flicker MAE is influenced by the MAE measurement method, retinal eccentricity and attention. Our results showed that the transfer was perfect or nearly so when the MAE duration was measured in the central visual field with observers paying attention to the adaptation stimulus, but the transfer was partial when the MAE nulling strength was measured, when the MAE duration was measured in the peripheral visual field, or when the observers’ attention was distracted by a secondary task. These results not only resolve discrepancies between previous studies, but also suggest that the flicker MAE reflects adaptation at multiple stages in the hierarchical architecture of motion processing.

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.

What is the Transition Point between Static and Dynamic Motion Aftereffects?

The motion aftereffect (MAE) measured with a dynamic test pattern (eg a counterphase-flickering grating) is distinguishable by a number of properties from the classical MAE obtained with a static test pattern. For a dynamic MAE, however, it is not sufficient simply to introduce dynamic properties into the test pattern. In two experiments we attempted to determine the transition point in the temporal-frequency domain at which a dynamic MAE becomes distinguishable from the static MAE. First, we examined the interocular transfer (IOT) of the MAE with conventional first-order (luminance) gratings. The amount of IOT increased with temporal frequency, and was almost complete at 1 Hz and above. In addition, the IOT of a dynamic MAE shows a drastic reduction in the peripheral visual field, possibly reflecting difficulties in feature tracking or the loss of involuntary attention. Second, we examined the MAE with second-order motion as the adaptation stimulus (contrast modulation of two-dimensional static noise). Under these conditions, similar results were obtained for first-order and second-order test gratings: MAE was not observed at low temporal frequencies and a substantial MAE was observed only at 1 Hz and above. The results agree with recent findings which showed a gradual loss of spatial-frequency selectivity with increasing temporal frequency of the test pattern (Mareschal et al, 1997 Vision Research37 1755 – 1759). The present results support the idea that two mechanisms underlie the different kinds of MAE: a low-level mechanism responsible for the MAE observed at low temporal frequencies, and a high-level mechanism operating predominantly at high temporal frequencies with a transition point at about 1 Hz.

Contrast dependencies of two types of motion aftereffect.

We examined the effects of adaptation and test contrasts on the duration of two types of motion aftereffect (MAE) that presumably reveal different levels of motion processing: MAE with a static test stimulus (static MAE), and that with a counterphasing test stimulus (flicker MAE). MAE duration increased with increasing adaptation contrast. When the test contrast was low, it increased rapidly, and saturated at a low adaptation contrast. When the test contrast was high, however, it gradually increased over a wide range of adaptation contrasts. These complex effects of stimulus contrasts could be well described by a dependency on adaptation contrast normalized by test contrast on a logarithmic axis. Little difference was found between the results for two types of MAE. The interaction between adaptation and test contrasts leads us to reject the idea that the shape of adaptation contrast dependency of MAE duration reflects that of the sensitivity function of motion detecting mechanisms. The results also suggest a functional similarity between the processes underlying static and flicker MAEs with regard to their responses to contrasts.

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.

Motion aftereffect with flickering test patterns reveals higher stages of motion processing

A series of experiments was conducted to clarify the distinction between motion aftereffects (MAEs) with static and counterphasing test patterns (static and flicker MAEs). It was found that while the motion of higher-order structure, such as areas defined by texture, flicker, or stereoscopic depth, induces little static MAE, such motion reliably generates flicker MAE. It was also found that static and flicker MAEs were induced in opposite directions for stimuli in which first- and second-order structures moved in opposite directions (compound graftings of 2 f + 3 f or 2 f + 3 f + 4 f, shifting a half cycle of 2 f). When the test was static, MAE was induced in the direction opposite to the first-order motion; but when the test was counterphasing, MAE was induced in the direction opposite to the second-order motion. This means that static MAE is predominantly induced by first-order motion, but that flicker MAE is affected strongly by second-order motion, along with first-order motion. The present results suggest that static MAE primarily reflects adaptation of a low-level motion mechanism, where first-order motion is processed, while flicker MAE reveals a high-level motion processing, where both first- and second-order motion signals are available.

Difference of spatial frequency selectivity between static and flicker motion aftereffects.

The strength of motion aftereffect (MAE) was measured with the use of sinusoidal gratings of several spatial frequencies, to examine the spatial frequency selectivity of two types of MAE. With ordinary static grating as a test stimulus, to measure 'static MAE', the maximum aftereffect for each adapting spatial frequency was obtained at the testing stimuli of the same spatial frequency, showing spatial frequency selectivity. However, in the case when the sinusoidally flickering grating was used as a test stimulus, to measure 'flicker MAE', no spatial frequency selectivity was observed. The two types of MAE were considered to be based on different mechanisms. Static MAE is thought to depend on the spatiotemporal channel mechanism in the early processing stages, whereas flicker MAE might reflect higher-level processes which might occur at the extrastriate regions.

Another perspective on the visual motion aftereffect.

Prolonged adaptation to motion in a given direction produces distinctly different visual motion aftereffects (MAEs) when viewing static vs. dynamic test displays. The dynamic MAE can be exactly simulated by real motion, whereas the static MAE cannot. In addition, the magnitude of the dynamic MAE depends on the bandwidth of motion directions experienced during adaptation, whereas the static MAE does not. Evidently a stationary pattern does not directly activate the neural mechanisms affected during motion adaptation, whereas a dynamic visual display does. These results imply that the traditional explanation of the MAE needs modification.