Jean-Luc points me to Mysterious ‘Neural Noise’ Actually Primes Brain for Peak Performance:
In the November issue of Nature Neuroscience, the Rochester study shows that the brain’s cortex uses seemingly chaotic, or “noisy,” signals to represent the ambiguities of the real world—and that this noise dramatically enhances the brain’s processing, enabling us to make decisions in an uncertain world.
“You’d think this is crazy because engineers are always fighting to reduce the noise in their circuits, and yet here’s the best computing machine in the universe—and it looks utterly random,” says Alex Pouget, associate professor of brain and cognitive sciences at the University of Rochester. [...]
“We’ve known for several years that at the behavioral level, we’re ‘Bayes optimal,’ meaning we are excellent at taking various bits of probability information, weighing their relative worth, and coming to a good conclusion quickly,” says Pouget. “But we’ve always been at a loss to explain how our brains are able to conduct such complex Bayesian computations so easily.” [...]
“The cortex appears wired at its foundation to run Bayesian computations as efficiently as can be possible,” says Pouget. His paper says the uncertainty of the real world is represented by this noise, and the noise itself is in a format that reduces the resources needed to compute it. Anyone familiar with log tables and slide rules knows that while multiplying large numbers is difficult, adding them with log tables is relatively undemanding.
E. T. Jaynes inferred that evolution would drive brain circuitry to implement Bayesian probability calculations in his posthumous textbook. Given the Cox theorems, I'd be more surprised if neural circuitry weren't hooked up to do Bayesian probability when dealing with uncertainty.