TY - JOUR T1 - Inferring Visuomotor Priors for Sensorimotor Learning A1 - Turnham, Edward J. A. A1 - Braun, Daniel A. A1 - Wolpert, Daniel M. Y1 - 2011/03/31 N2 - Author Summary When learning a new skill, such as riding a bicycle, we can adjust the commands we send to our muscles based on two sources of information. First, we can use sensory inputs to inform us how the bike is behaving. Second, we can use prior knowledge about the properties of bikes and how they behave in general. This prior knowledge is represented as a probability distribution over the properties of bikes. These two sources of information can then be combined by a process known as Bayes rule to identify optimally the properties of a particular bike. Here, we develop a novel technique to identify the probability distribution of a prior in a visuomotor learning task in which the visual location of the hand is transformed from the actual hand location, similar to when using a computer mouse. We show that subjects have a prior that tends to interpret ambiguous information about the task as arising from a visuomotor rotation but that experience of a particular set of visuomotor transformations can alter the prior. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 7 IS - 3 UR - https://doi.org/10.1371/journal.pcbi.1001112 SP - e1001112 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1001112 ER -