Computations in Sensorimotor Learning

Computations underlying sensorimotor learning.

The study of sensorimotor learning has a long history. With the advent of innovative techniques for studying learning at the behavioral and computational levels new insights have been gained in recent years into how the sensorimotor system acquires, retains, represents, retrieves and forgets sensorimotor tasks. In this review we highlight recent advances in the field of sensorimotor learning fr...

Sensorimotor Learning

Perceptual learning in sensorimotor adaptation.

Motor learning often involves situations in which the somatosensory targets of movement are, at least initially, poorly defined, as for example, in learning to speak or learning the feel of a proper tennis serve. Under these conditions, motor skill acquisition presumably requires perceptual as well as motor learning. That is, it engages both the progressive shaping of sensory targets and associ...

Occam's Razor in sensorimotor learning.

A large number of recent studies suggest that the sensorimotor system uses probabilistic models to predict its environment and makes inferences about unobserved variables in line with Bayesian statistics. One of the important features of Bayesian statistics is Occam's Razor--an inbuilt preference for simpler models when comparing competing models that explain some observed data equally well. He...

Sensorimotor Learning Enhances Expectations 1 In press, Cerebral Cortex Sensorimotor learning enhances expectations during auditory perception

Sounds that have been produced with one’s own motor system tend to be remembered better than sounds that have only been perceived, suggesting a role of motor information in memory for auditory stimuli. To address potential contributions of the motor network to the recognition of previously produced sounds, we used event-related potential, electric current density, and behavioral measures to inv...