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

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.

The lateralized flash-lag illusion: A psychophysical and pupillometry study

The flash-lag illusion (FLI) is a visual phenomenon where a flashed object, either co-localized or in physical alignment with another continuously moving object, is perceived to lag behind the path of the moving object. In the present study, we reveal an anisotropy of the FLI between the lateral visual fields that was expressed psychophysically as different points of subjective equality, depending on the hemifield in which the stimuli appeared. Specifically, the study confirmed that, as seen in two previous studies, the FLI was significantly larger in the left visual field (LVF) than in the right (RVF). In addition, pupil dilations were larger in the RVF than in the LVF as well as returning to baseline levels more rapidly in the LVF. We interpret these findings as converging on revealing more efficient spatial and attentional processing and, in turn, extrapolation of motion in the LVF/right hemisphere than in the RVF/left hemisphere.

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.

Interocular Transfer: The Dichoptic Flash-Lag Effect in Controls and Amblyopes

Purpose

The mammalian brain can take into account the neural delays in visual information transmission from the retina to the cortex when accurately localizing the instantaneous position of moving objects by motion extrapolation. In this study, we wanted to investigate whether such extrapolation mechanism operates in a comparable fashion between the eyes in normally sighted and amblyopic observers.

Methods

To measure interocular extrapolation, we adapted a dichoptic version of the flash-lag effect (FLE) paradigm, in which a flashed bar is perceived to lag behind a moving bar when their two positions are physically aligned. Twelve adult subjects with amblyopia and 12 healthy controls participated in the experiment. We measured the FLE magnitude of the subjects under binocular, monocular, and dichoptic conditions.

Results

In controls, the FLE magnitude of binocular condition was significantly smaller than that of monocular conditions (P ≤ 0.023), but there was no difference between monocular and dichoptic conditions. Subject with amblyopia exhibited a smaller FLE magnitude in the dichoptic condition when the moving bar was presented to the amblyopic eye and the flash to the fellow eye (DA condition) compared to the opposite way around (DF condition), consistent with a delay in the processing of the amblyopic eye (P = 0.041).

Conclusions

Our observations confirm that trajectory extrapolation mechanisms transfer between the eyes of normal observers. However, such transfer may be impaired in amblyopia. The smaller FLE magnitude in DA compared to DF in patients with amblyopia could be due to an interocular delay in the amblyopic visual system. The observation that normal controls present a smaller FLE in binocular conditions raises the question whether a larger FLE is or is not an indicator of better motion processing and extrapolation.

Perception in real-time: predicting the present, reconstructing the past

We feel that we perceive events in the environment as they unfold in real-time. However, this intuitive view of perception is impossible to implement in the nervous system due to biological constraints such as neural transmission delays. I propose a new way of thinking about real-time perception: at any given moment, instead of representing a single timepoint, perceptual mechanisms represent an entire timeline. On this timeline, predictive mechanisms predict ahead to compensate for delays in incoming sensory input, and reconstruction mechanisms retroactively revise perception when those predictions do not come true. This proposal integrates and extends previous work to address a crucial gap in our understanding of a fundamental aspect of our everyday life: the experience of perceiving the present.

Delayed Correction for Extrapolation in Amblyopia

Purpose

It has been suggested that amblyopes present impaired motion extrapolation mechanisms. In this study, we used the flash grab effect (FGE), the illusory mislocalization of a briefly flashed stimulus in the direction of a reversing moving background, to investigate whether the amblyopic visual system can correct overextrapolation.

Methods

Thirteen amblyopes and 13 control subjects participated in the experiment. We measured the monocular FGE magnitude for each subject. Two spatial frequency (2 and 8 cycles), two texture configurations (square wave or sine wave), and two speed conditions (270 degrees/s and 67.5 degrees/s) were tested. In addition, control subjects were further tested in reduced luminance conditions.

Results

Compared with controls, amblyopes exhibited a larger FGE magnitude both in their fellow eye (FE) and amblyopic eye (AE). The FGE magnitude of their AE was significantly larger than that of the FE. In a control experiment, we observed that the FGE magnitude increases with the decreasing of the luminance. The FGE magnitude of amblyopes fall into the same range as that of controls under reduced luminance conditions.

Conclusions

We observed a lager FGE in patients with amblyopia, which indicates that the amblyopic visual system does not accurately correct the overextrapolation when a moving object abruptly reverses its direction. This spatiotemporal processing deficit could be ascribed to delayed visual processing in the amblyopic visual system.

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.

Expecting the unexpected: Temporal expectation increases the flash-grab effect

In the flash-grab effect, when a disk is flashed on a moving background at the moment it reverses direction, the perceived location of the disk is strongly displaced in the direction of the motion that follows the reversal. Here, we ask whether increased expectation of the reversal reduces its effect on the motion-induced shift, as suggested by predictive coding models with first order predictions. Across four experiments we find that when the reversal is expected, the illusion gets stronger, not weaker. We rule out accumulating motion adaptation as a contributing factor. The pattern of results cannot be accounted for by first-order predictions of location. Instead, it appears that second-order predictions of event timing play a role. Specifically, we conclude that temporal expectation causes a transient increase in temporal attention, boosting the strength of the motion signal and thereby increasing the strength of the illusion.

Predictions drive neural representations of visual events ahead of incoming sensory information

The transmission of sensory information through the visual system takes time. As a result of these delays, the visual information available to the brain always lags behind the timing of events in the present moment. Compensating for these delays is crucial for functioning within dynamic environments, since interacting with a moving object (e.g., catching a ball) requires real-time localization of the object. One way the brain might achieve this is via prediction of anticipated events. Using time-resolved decoding of electroencephalographic (EEG) data, we demonstrate that the visual system represents the anticipated future position of a moving object, showing that predictive mechanisms activate the same neural representations as afferent sensory input. Importantly, this activation is evident before sensory input corresponding to the stimulus position is able to arrive. Finally, we demonstrate that, when predicted events do not eventuate, sensory information arrives too late to prevent the visual system from representing what was expected but never presented. Taken together, we demonstrate how the visual system can implement predictive mechanisms to preactivate sensory representations, and argue that this might allow it to compensate for its own temporal constraints, allowing us to interact with dynamic visual environments in real time.

Introduction to special issue on "Prediction in Perception and Action"

The wide diversity of articles in this issue reveals an explosion of evidence for the mechanisms of prediction in the visual system. When thought of as visual priors, predictive mechanisms can be seen as tightly interwoven with incoming sensory data. Prediction is thus a fundamental and essential aspect not only of visual perception but of the actions that are guided by perception.

Ocular torsion is related to perceived motion-induced position shifts

Ocular torsion (i.e., rotations of the eye about the line of sight) can be induced by visual rotational motion. It remains unclear whether and how such visually induced torsion is related to perception. By using the flash-grab effect, an illusory position shift of a briefly flashed stationary target superimposed on a rotating pattern, we examined the relationship between torsion and perception. In two experiments, 25 observers reported the perceived location of a flash while their three-dimensional eye movements were recorded. In Experiment 1, the flash coincided with a direction reversal of a large, centrally displayed, rotating grating. The grating triggered visually induced torsion in the direction of stimulus rotation. The magnitude of torsional eye rotation correlated with the illusory perceptual position shift. To test whether torsion caused the illusion, in Experiment 2, the flash was superimposed on two peripheral gratings rotating in opposite directions. Even though torsion was eliminated, the illusory position shift persisted. Despite the lack of a causal relationship, the torsion-perception correlations indicate a close link between both systems, either through similar visual-input processing or a boost of visual rotational signal strength via oculomotor feedback.

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.