Bayesian integration in sensorimotor learning

@article{Krding2004BayesianII,
  title={Bayesian integration in sensorimotor learning},
  author={Konrad P. K{\"o}rding and Daniel M. Wolpert},
  journal={Nature},
  year={2004},
  volume={427},
  pages={244-247}
}
When we learn a new motor skill, such as playing an approaching tennis ball, both our sensors and the task possess variability. Our sensors provide imperfect information about the ball's velocity, so we can only estimate it. Combining information from multiple modalities can reduce the error in this estimate. On a longer time scale, not all velocities are a priori equally probable, and over the course of a match there will be a probability distribution of velocities. According to bayesian… CONTINUE READING
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