Sensorimotor learning compensates for irreducible perceptual bias

Because of the uncertainties present in the any sensory inflows, we experienced perceptual biases that often contaminate sensorimotor transformations. How these biases can be prevented through perceptual learning or adaptation is an open question in inference theories of perception and motor control. We revisited this debate using a classic example of low-level perceptual bias, the aperture problem in motion perception and its consequences for smooth pursuit. In a visuomotor tracking paradigm, participants pursued left-, right-tilted, or upright Gabor patches moving horizontally. As expected, initial pursuit direction was biased toward the oblique directions. This initial pursuit error remained unchanged when participants repeatedly tracked a single tilted Gabor during training sessions conducted over several days. By contrast, post-training error correction became faster for the trained Gabor orientation, but not for its untrained, mirror-symmetric counterpart. This change in dynamics was explained by the emergence of a delayed compensatory pursuit response, best revealed after training with an upright Gabor, a stimulus that would normally elicit unbiased tracking. This corrective eye movement was selective for both shape and motion features. It lagged by [~]40 msec after pursuit onset suggesting that it was triggered by the biased motor command itself rather than by visual reafference. These results support a dissociation between low-level sensory computations, which cannot be modified over short timescales, and internal models of sensorimotor transformation, which can be rapidly updated to compensate for irreducible but predictable sensory-driven perceptual biases.