Motion extrapolation in the central fovea

Corrective mechanisms of motion extrapolation

Transmission and processing of sensory information in the visual system takes time. For motion perception, our brain can overcome this intrinsic neural delay through extrapolation mechanisms and accurately predict the current position of a continuously moving object. But how does the system behave when the motion abruptly changes and the prediction becomes wrong? Here we address this question by studying the perceived position of a moving object with various abrupt motion changes by human observers. We developed a task in which a bar is monotonously moving horizontally, and then motion suddenly stops, reverses, or disappears-then-reverses around two vertical stationary reference lines. Our results showed that participants overestimated the position of the stopping bar but did not perceive an overshoot in the motion reversal condition. When a temporal gap was added at the reverse point, the perceptual overshoot of the end point scaled with the gap durations. Our model suggests that the overestimation of the object position when it disappears is not linear as a function of its speeds but gradually fades out. These results can thus be reconciled in a single process where there is an interplay of the cortical motion prediction mechanisms and the late sensory transient visual inputs.

Exploring the extent to which shared mechanisms contribute to motion-position illusions

Motion-position illusions (MPIs) are visual motion illusions in which motion signals bias the perceived position of an object. Due to phenomenological similarities between these illusions, previous research has assumed that some are caused by common mechanisms. However, this assumption has yet to be directly tested. This study investigates this assumption by exploiting between-participant variations in illusion magnitude. During two sessions, 106 participants viewed the flash-lag effect, luminance flash-lag effect, Fröhlich effect, flash-drag effect, flash-grab effect, motion-induced position shift, twinkle-goes effect, and the flash-jump effect. For each effect, the magnitude of the illusion was reliable within participants, strongly correlating between sessions. When the pairwise correlations of averaged illusions magnitudes were explored, two clusters of statistically significant positively correlated illusions were identified. The first cluster comprised the flash-grab effect, motion-induced position shift, and twinkle-goes effect. The second cluster comprised the Fröhlich and flash-drag effect. The fact that within each of these two clusters, individual differences in illusion magnitude were correlated suggests that these clusters may reflect shared underlying mechanisms. An exploratory factor analysis provided additional evidence that these correlated clusters shared an underlying factor, with each cluster loading onto their own factor. Overall, our results reveal that, contrary to the prevailing perspective in the literature, while some motion-position illusions share processes, most of these illusions are unlikely to reflect any shared processes, instead implicating unique mechanisms.

A motion-induced position shift that depends on motion both before and after the test probe

Two versions of the flash grab illusion were used to examine the relative contributions of motion before and motion after the test flash to the illusory position shift. The stimulus in the first two experiments was a square pattern that expanded and contracted with an outline square flashed each time the motion reversed producing a dramatic difference in perceived size between the two reversals. Experiment 1 showed a strong illusion when motion was present before and after the flashed tests or just after the flashes, but no significant effect when only the pre-flash motion was present. In Experiment 2, motion always followed the flash, and the duration of the pre-flash motion was varied. The results showed a significant increase in illusion strength with the duration of pre-flash motion and the effect of the pre-flash motion was almost 50% that of the post-flash motion. Finally, Experiment 3 tested the position shifts when the linear motion of a disk before the flash was orthogonal to its motion after the flash. Here, the results again showed that the pre-flash motion made a significant contribution, about 32% that of the post-flash motion. Several models are considered and even though all fail to some degree, they do offer insights into the nature of the illusion. Finally, we show that the empirical measure of the relative contribution of motion before and after the flash can be used to distinguish the mechanisms underlying different illusions.

The nature of neural object representations during dynamic occlusion

Objects disappearing briefly from sight due to occlusion is an inevitable occurrence in everyday life. Yet we generally have a strong experience that occluded objects continue to exist, despite the fact that they objectively disappear. This indicates that neural object representations must be maintained during dynamic occlusion. However, it is unclear what the nature of such representation is and in particular whether it is perception-like or more abstract, for example, reflecting limited features such as position or movement direction only. In this study, we address this question by examining how different object features such as object shape, luminance, and position are represented in the brain when a moving object is dynamically occluded. We apply multivariate decoding methods to Magnetoencephalography (MEG) data to track how object representations unfold over time. Our methods allow us to contrast the representations of multiple object features during occlusion and enable us to compare the neural responses evoked by visible and occluded objects. The results show that object position information is represented during occlusion to a limited extent while object identity features are not maintained through the period of occlusion. Together, this suggests that the nature of object representations during dynamic occlusion is different from visual representations during perception.

A dynamic noise background reveals perceptual motion extrapolation: The twinkle-goes illusion

We find that on a dynamic noise background, the perceived disappearance location of a moving object is shifted in the direction of motion. This “twinkle-goes” illusion does not require luminance- or chromaticity-based confusability of the object with the background, or on the amount of background motion energy in the same direction as the object motion. This suggests that the illusion is enabled by the dynamic noise masking the offset transients that otherwise accompany an object's disappearance. While these results are consistent with an anticipatory process that pre-activates positions ahead of the object's current position, additional findings suggest an alternative account: a continuation of attentional tracking after the object disappears. First, the shift increased with speed until over 1.2 revolutions per second (rps), nearing the attentional tracking limit. Second, the shift was greatly reduced when attention was divided between two moving objects. Finally, the illusion was associated with a delay in simple reaction time to the disappearance of the object. We propose that in the absence of offset transients, attentional tracking keeps moving for several tens of milliseconds after the target disappearance, and this causes one to hallucinate a moving object at the position of attention.

Resolving visual motion through perceptual gaps

Perceptual gaps can be caused by objects in the foreground temporarily occluding objects in the background or by eyeblinks, which briefly but frequently interrupt visual information. Resolving visual motion across perceptual gaps is particularly challenging, as object position changes during the gap. We examine how visual motion is maintained and updated through externally driven (occlusion) and internally driven (eyeblinks) perceptual gaps. Focusing on both phenomenology and potential mechanisms such as suppression, extrapolation, and integration, we present a framework for how perceptual gaps are resolved over space and time. We finish by highlighting critical questions and directions for future work.

Motion Extrapolation in Visual Processing: Lessons from 25 Years of Flash-Lag Debate

Because of the delays inherent in neural transmission, the brain needs time to process incoming visual information. If these delays were not somehow compensated, we would consistently mislocalize moving objects behind their physical positions. Twenty-five years ago, Nijhawan used a perceptual illusion he called the flash-lag effect (FLE) to argue that the brain's visual system solves this computational challenge by extrapolating the position of moving objects (Nijhawan, 1994). Although motion extrapolation had been proposed a decade earlier (e.g., Finke et al., 1986), the proposal that it caused the FLE and functioned to compensate for computational delays was hotly debated in the years that followed, with several alternative interpretations put forth to explain the effect. Here, I argue, 25 years later, that evidence from behavioral, computational, and particularly recent functional neuroimaging studies converges to support the existence of motion extrapolation mechanisms in the visual system, as well as their causal involvement in the FLE. First, findings that were initially argued to challenge the motion extrapolation model of the FLE have since been explained, and those explanations have been tested and corroborated by more recent findings. Second, motion extrapolation explains the spatial shifts observed in several FLE conditions that cannot be explained by alternative (temporal) models of the FLE. Finally, neural mechanisms that actually perform motion extrapolation have been identified at multiple levels of the visual system, in multiple species, and with multiple different methods. I outline key questions that remain, and discuss possible directions for future research.

Motion extrapolation in the High-Phi illusion: Analogous but dissociable effects on perceived position and perceived motion

A range of visual illusions, including the much-studied flash-lag effect, demonstrate that neural signals coding for motion and position interact in the visual system. One interpretation of these illusions is that they are the consequence of motion extrapolation mechanisms in the early visual system. Here, we study the recently reported High-Phi illusion to investigate whether it might be caused by the same underlying mechanisms. In the High-Phi illusion, a rotating texture is abruptly replaced by a new, uncorrelated texture. This leads to the percept of a large illusory jump, which can be forward or backward depending on the duration of the initial motion sequence (the inducer). To investigate whether this motion illusion also leads to illusions of perceived position, in three experiments we asked observers to localize briefly flashed targets presented concurrently with the new texture. Our results replicate the original finding of perceived forward and backward jumps, and reveal an illusion of perceived position. Like the observed effects on illusory motion, these position shifts could be forward or backward, depending on the duration of the inducer: brief inducers caused forward mislocalization, and longer inducers caused backward mislocalization. Additionally, we found that both jumps and mislocalizations scaled in magnitude with the speed of the inducer. Interestingly, forward position shifts were observed at shorter inducer durations than forward jumps. We interpret our results as an interaction of extrapolation and correction-for-extrapolation, and discuss possible mechanisms in the early visual system that might carry out these computations.

Perceiving Locations of Moving Objects Across Eyeblinks

Eyeblinks cause disruption of visual input that generally goes unnoticed. It is thought that the brain uses active suppression to prevent awareness of the gaps, but it is unclear how suppression would affect the perception of dynamic events when visual input changes across the blink. Here, we addressed this question by studying the perception of moving objects around eyeblinks. In Experiment 1 (N = 16), we observed that when motion terminates during a blink, the last perceived position is shifted forward from its actual last position. In Experiment 2 (N = 8), we found that motion trajectories were perceived as more continuous when the object jumped backward during the blink, canceling a fraction of the space that it traveled. This suggests subjective underestimation of blink duration. These results reveal the strategies used by the visual system to compensate for disruptions and maintain perceptual continuity: Time elapsed during eyeblinks is perceptually compressed and filled with extrapolated information.

The perceived present: What is it, and what is it there for?

It is proposed that the perceived present is not a moment in time, but an information structure comprising an integrated set of products of perceptual processing. All information in the perceived present carries an informational time marker identifying it as "present". This marker is exclusive to information in the perceived present. There are other kinds of time markers, such as ordinality ("this stimulus occurred before that one") and duration ("this stimulus lasted for 50 ms"). These are different from the "present" time marker and may be attached to information regardless of whether it is in the perceived present or not. It is proposed that the perceived present is a very short-term and very high-capacity holding area for perceptual information. The maximum holding time for any given piece of information is ~100 ms: This is affected by the need to balance the value of informational persistence for further processing against the problem of obsolescence of the information. The main function of the perceived present is to facilitate access by other specialized, automatic processes.

When predictions fail: Correction for extrapolation in the flash-grab effect

Motion-induced position shifts constitute a broad class of visual illusions in which motion and position signals interact in the human visual pathway. In such illusions, the presence of visual motion distorts the perceived positions of objects in nearby space. Predictive mechanisms, which could contribute to compensating for processing delays due to neural transmission, have been given as an explanation. However, such mechanisms have struggled to explain why we do not usually perceive objects extrapolated beyond the end of their trajectory. Advocates of this interpretation have proposed a "correction-for-extrapolation" mechanism to explain this: When the object motion ends abruptly, this mechanism corrects the overextrapolation by shifting the perceived object location backwards to its actual location. However, such a mechanism has so far not been empirically demonstrated. Here, we use a novel version of the flash-grab illusion to demonstrate this mechanism. In the flash-grab effect, a target is flashed on a moving background that abruptly changes direction, leading to the mislocalization of the target. Here, we manipulate the angle of the direction change to dissociate the contributions of the background motion before and after the flash. Consistent with previous reports, we observe that perceptual mislocalization in the flash-grab illusion is mainly driven by motion after the flash. Importantly, however, we reveal a small but consistent mislocalization component in the direction opposite to the direction of the first motion sequence. This provides empirical support for the proposed correction-for-extrapolation mechanism, and therefore corroborates the interpretation that motion-induced position shifts might result from predictive interactions between motion and position signals.

Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis

Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical levels are connected by backward connections carrying predictions, as well as forward connections carrying prediction errors. To date, however, predictive coding models have largely neglected to take into account that neural transmission itself takes time. For a time-varying stimulus, such as a moving object, this means that backward predictions become misaligned with new sensory input. We present an extended model implementing both forward and backward extrapolation mechanisms that realigns backward predictions to minimize prediction error. This realignment has the consequence that neural representations across all hierarchical levels become aligned in real time. Using visual motion as an example, we show that the model is neurally plausible, that it is consistent with evidence of extrapolation mechanisms throughout the visual hierarchy, that it predicts several known motion-position illusions in human observers, and that it provides a solution to the temporal binding problem.