How is sensory information processed?
Advances in statistical learning theory leave us with many possible designs of learning machines. But which of them are implemented by brains, metabolic and genetic networks, and other biological information processors? We analyze how abstract Bayesian learners would perform on different data and discuss possible experiments that can determine which learning–theoretic computation is performed by a particular organism.