A quick demo that will introduce you to the motion aftereffect – a visual illusion that has been known for centuries – and our paper that was the first to describe motion aftereffects on smooth pursuit eye movements. We used computational modeling to put the motion aftereffects we found with pursuit into the context of how the code for visual motion is read out from a population of neurons. Click anywhere on the gray screen above and use the <right arrow> and <left arrow> keys to navigate – or push the full screen button and use the buttons to navigate (keyboard navigation is prohibited by the Flash player in full screen mode).

Gardner, J. L. , Tokiyama, S., and Lisberger, S. G. (2004) A population decoding framework for motion aftereffects on smooth pursuit eye movements. Journal of Neuroscience 24:9035-9048 DOI Abstract

Both perceptual and motor systems must decode visual information from the distributed activity of large populations of cortical neurons. We have sought a common framework for understanding decoding strategies for visually guided movement and perception by asking whether the strong motion aftereffects seen in the perceptual domain lead to similar expressions in motor output. We found that motion adaptation indeed has strong sequelae in the direction and speed of smooth pursuit eye movements. After adaptation with a stimulus that moves in a given direction for 7 sec, the direction of pursuit is repelled from the direction of pursuit targets that move within 90 degrees of the adapting direction. The speed of pursuit decreases for targets that move at the direction and speed of the adapting stimulus and is repelled from the adapting speed in the sense that the decrease either becomes greater or smaller (eventually turning to an increase) when tracking targets move slower or faster than the adapting speed. The effects of adaptation are spatially specific and fixed to the retinal location of the adapting stimulus. The magnitude of adaptation of pursuit speed and direction is uncorrelated, suggesting that the two parameters are decoded independently. Computer simulation of motion adaptation in the middle temporal visual area (MT) shows that vector-averaging decoding of the population response in MT can account for the effects of adaptation on the direction of pursuit. Our results suggest a unified framework for thinking, in terms of population decoding, about motion adaptation for both perception and action. pdf