Researchers at the University of Rochester may have answered one of neuroscience's most vexing questions--how can it be that our neurons, which are responsible for our crystal-clear thoughts, seem to fire in utterly random ways?
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.
Pouget's work for the first time connects two of the brain's biggest mysteries; why it's so noisy, and how it can perform such complex calculations. As counter-intuitive as it sounds, the noise seems integral to making those calculations possible.
In the last decade, Pouget and his colleagues in the University of Rochester's Department of Brain and Cognitive Sciences have blazed a new path to understanding our gray matter. The traditional approach has assumed the brain uses the same method computation in general had used up until the mid-80s: You see an image and you relate that image to one stored in your head. But the reality of the cranial world seems to be a confusing array of possibilities and probabilities, all of which are somehow, mysteriously, properly calculated.
The science of drawing answers from such a variety of probabilities is called Bayesian computing, after minister Thomas Bayes who founded the unusual branch of math 150 years ago. Pouget says that when we seem to be struck by an idea from out of the blue, our brain has actually just resolved many probabilities its been fervently calculating.
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Contact: Jonathan Sherwood
jonathan.sherwood@rochester.edu
585-273-4726
University of Rochester
10-Nov-2006