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

Abstract

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.

The Flash-lag Effect in Amblyopia

“…The flash-lag effect (FLE), a well-established illusion in which a flashed object is perceived to lag behind a moving object when their two positions are physically aligned, has been widely used to study the spatiotemporal interactions in visual processing. This effect has mostly been attributed to latency differences in processing: the processing latency of the flashed object would be longer than the latency of the moving one, 22 – 25 extrapolation mechanisms, 17 , 26 – 28 or other mechanisms. 29 Transcranial magnetic stimulation (TMS) applied to area MT+, which is involved in visual motion processing and temporal integration, has been shown to significantly reduce the FLE over a long period of time (100 ms before flash to 200 ms after flash).…”

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

“…This includes motion extrapolation mechanisms in the retinae of mice, salamanders, and rabbits ( Berry et al, 1999 ; Schwartz et al, 2007 ), cat LGN ( Sillito, Jones, Gerstein, & West, 1994 ) and both cat ( Jancke, Erlhagen, Schöner, & Dinse, 2004 ) and macaque V1 ( Subramaniyan et al, 2018 ). Comparable mechanisms have been reported in humans on the basis of EEG ( Blom, Feuerriegel, Johnson, Bode, & Hogendoorn, 2020 ; Hogendoorn & Burkitt, 2018 ; Johnson, Blom, Feuerriegel, Bode, & Hogendoorn, 2019 ) and fMRI evidence ( Ekman, Kok, & de Lange, 2017 ; Schellekens, van Wezel, Petridou, Ramsey, & Raemaekers, 2016 ; see Hogendoorn, 2020 for a review). The current findings are consistent with these neural mechanisms and provide further insight into the perceptual consequences of those mechanisms.…”

“…In contrast, the flash-lag effect has been the subject of intense investigation and debate since it was first interpreted by Nijhawan as evidence for visual motion extrapolation ( Nijhawan, 1994 ). Although several other explanations have been proposed (see Hubbard, 2014 ; Maus, Khurana, & Nijhawan, 2010 for reviews), convergent behavioral, computational, and neuroimaging evidence continues to support the existence of motion extrapolation mechanisms in the visual system, and their role in the flash-lag and related illusions ( Hogendoorn, 2020 ; Nijhawan, 1994 ; Nijhawan, 2008 ). In this interpretation, motion signals interact with position signals to shift the perceived position of moving objects in the direction of motion ( Eagleman & Sejnowski, 2007 ), proportional to the speed of motion ( Nijhawan, 1994 ), potentially serving to counteract neural processing delays.…”

No Evidence for a Single Oscillator Underlying Discrete Visual Percepts

“…This is distinct from discrete sampling (or the related post diction account of the flash-lag) in that the motion percept is not reconstructed after the fact, but is instead based on a prediction about where the stimulus will be. Motion extrapolation mechanisms have been observed as early as the retina (in some species) and could therefore begin very early after motion onset to produce a percept of the motion stimulus that is advanced with respect to a stationary flash (Hogendoorn, 2020). Regarding the Fröhlich effect, it has been argued that metacontrast masking plays a crucial role (Kerzel, 2010).…”