Another perspective on the visual motion aftereffect.

Abstract

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.Following inspection of motion in a given direction for a period of time, a stationary object appears temporarily to drift in the opposite direction (1); this is the well-known motion aftereffect (MAE). The MAE is a widely used inferential tool for studying the response properties of motionanalyzing mechanisms in human vision (2-4), and neurophysiologists have sought to uncover the neural concomitants of this compelling illusion (5-8). The MAE cannot be caused by transients or by retinal slip associated with eye movements, for it is observed even when the image of the test pattern is stabilized on the retina (9). Instead, the MAE is typically attributed to a temporary depression in activity within those neurons responsive to motion in the direction experienced during adaptation. When a stationary pattern is then viewed, this selective adaptation yields a shift in the balance of activity favoring neural mechanisms signaling motion in the opposite direction (10, 11). Based on two findings utilizing dynamic as well as static MAE displays, we find this explanation deficient. (i) A dynamic MAE can be simulated by real motion whereas a static MAE cannot and (ii) the magnitude of a dynamic MAE depends on the bandwidth of motion directions experienced during adaptation whereas a static MAE does not. We propose that a stationary pattern does not directly activate neural mechanisms affected during motion adaptation, whereas a dynamic visual display does. This proposal leads to a significant modification of the traditional explanation of the MAE.Can the MAE Be Simulated by Real Motion?Imagine viewing a cluster of black dots moving against a white background, with the directions of dot motions entirely random. Termed random dynamic visual noise (RDVN), this display has no net direction flow; the individual dots appear to be jittering about randomly (12). But now suppose this RDVN test display is viewed following prolonged inspection of dots all moving in the same direction, say upward. Following adaptation to upward motion, RDVN now appears temporarily to have a general downward direction of drift, even though statistically all directions are equally represented. This dynamic MAE is readily explained by the distribution-shift model (10, 11). Now, the unadapted DVN stimulus can be rendered perceptually identical to the dynamic MAE experienced during postadaptation viewing of RDVN simpl...

Another means for measuring the motion aftereffect

“…It is also possible to alter the statistical distribution of directions of motion, creating animation sequences in which the range of possible directions is restricted to something ~360 deg. This bandwidth manipulation, like signal strength, affects the perception of global motion flow, These "directional bandwidth" stimuli can be used either as adaptation or test stimuli in the study of the DMAE; indeed we have found that the DMAE varies in strength with the bandwidth of motion directions present during adaptation (Hiris & Blake, 1992). Finally, this procedure involving the nullification of a DMAE with signal motion works equally effectively with rotational motion or with expansion/contraction.…”

“…While simple in principle, this task turns out to be challenging: observers can never exactly match the MAE using real motion, for the object undergoing illusory motion never goes anywhere. In fact, we have found that observers never confuse real motion with the illusory motion associated with the MAE (Hiris & Blake, 1992). So in a matching procedure, the match is at best an approximation.…”

Visual motion aftereffect from understanding motion language

“…The net difference in the firing rate of neurons selective for the direction of the adapting stimulus relative to those selective for the opposite direction of motion produces a motion illusion. For example, after adapting to upward motion, people are more likely to see a stationary stimulus or a field of randomly moving dots as moving downward, and vice versa (14,15). To quantify the size of the aftereffect, one can parametrically vary the degree of motion coherence in the test display of moving dots (14,15).…”

“…For example, after adapting to upward motion, people are more likely to see a stationary stimulus or a field of randomly moving dots as moving downward, and vice versa (14,15). To quantify the size of the aftereffect, one can parametrically vary the degree of motion coherence in the test display of moving dots (14,15). The amount of coherence necessary to null the MAE (i.e., to make people equally likely to report the motion as upward or downward) provides a nice measure of the size of the aftereffect produced by the adapting stimulus.…”

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

“…However, more recently it has been found that there are other MAEs, that can be best perceived if the test stimulus consists of global flicker (Green, Chilcoat, & Stromeyer, 1983) or local flicker, such as dynamic noise (e.g. Blake & Hiris, 1993;Hiris & Blake, 1992), or counterphase-flickering gratings (e.g. Ashida & Osaka, 1995a, 1995bvon Gr€ unau, 1986;Ledgeway, 1994;McCarthy, 1993;Nishida & Sato, 1995).…”