Context estimation for sensorimotor control

Human motor behavior is remarkably accurate and appropriate even though the properties of our own bodies as well as the objects we interact with vary over time. To adjust appropriately, the motor system has to estimate the co ntext, that is the properties of objects in the world and the prevailing en vironmental conditions. Here we show that to determine the current context the CNS uses information from both prior knowledge of how the context might evolve over time and from the comparison of predicted and actual sensory f eedback. We show that these two sources of information may be modeled withi n the CNS and combined to derive an accurate estimate of the context which adjusts motor command selection. This provides a novel probabilistic framew ork for sensorimotor control.