Predictability, efference copies, and non-retinotopic motion
Perception is usually non-retinotopic. For example, visual perception is stable even though the retinal image is constantly changing due to eye and body movements. Likewise, a reflector on the wheel of a bicycle is perceived to rotate on a circular orbit, while its “true” motion (in retinotopic or exogenous coordinates) is cycloidal. In the first example, the brain uses efference copies to predict and compensate for eye movements. But how does the brain compensate for motion without efference copies? To investigate non-retinotopic motion perception, we used the Ternus-Pikler display. Two disks are flashed on a computer screen. A dot moves linearly up-down in the left disk and left-right in the right disk (retinotopic percept). If a third disk is added alternatingly to the left and right, the three disks form a group moving back and forth horizontally. The dot in the central disk now appears to move on a circular orbit (non-retinotopic percept), because the brain subtracts the horizontal group motion from the combination of the up-down and left-right motion. Here, we asked whether predictability is necessary to compute non-retinotopic motion. In experiment 1, the three disks moved randomly in any direction, rather than horizontally back and forth. Still, a strong non-retinotopic dot rotation was perceived. In experiment 2, we additionally varied the shape and contrast polarity of the stimuli from frame to frame. Still, a strong non-retinotopic dot rotation was perceived. Hence, the visual system can flexibly solve the non-retinotopic motion correspondence problem, even when the retinotopic reference motion is unpredictable. It seems that, in the case of non-retinotopic motion, the brain computes the reference-frame in real-time and does not need efference copy-like signals based on the predictability of the stimulus.
This work was supported by grant 153001, “Basics of visual processing: From retinotopic encoding to non-retinotopic representations”, of the Swiss National Science Foundation (SNSF).
Record created on 2015-09-17, modified on 2016-08-09