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Todorov and other scientists are finding that athletes’ brains calibrate forward models in a manner consistent with Bayesian decision theory, a statistical approach that combines a continual stream of new information with previous beliefs. Because there is a level of uncertainty associated with sensory input, the brain has to decide whether it is going to rely more on the new data (which could be misleading) or on more credible (albeit potentially outdated) priors. Elite athletes, who have acquired more priors through frequent competition and practice and who have less noise in their sensory input and motor output, will have the edge, Todorov suggests.
