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Mysterious 'neural noise' actually primes brain for peak performance

from the world around us. But if we want to do something, such as jump over a stream, we need to extract data that is not inherently part of that information. We need to process all the variables we see, including how wide the stream appears, what the consequences of falling in might be, and how far we know we can jump. Each neuron responds to a particular variable and the brain will decide on a conclusion about the whole set of variables using Bayesian inference.

As you reach your decision, you'd have a lot of trouble articulating most of the variables your brain just processed for you. Similarly, intuition may be less a burst of insight than a rough consensus among your neurons.

Pouget and his team are now expanding their findings across the entire cortex, because every part of our highly developed cortex displays a similar underlying Bayes-optimal structure.

"If the structure is the same, that means there must be something fundamentally similar among vision, movement, reasoning, loving--anything that takes place in the human cortex," says Pouget. "The way you learn language must be essentially the same as the way a doctor reasons out a diagnosis, and right now our lab is pushing hard to find out exactly how that noise makes all these different aspects of being human possible."

Pouget's work still has its skeptics, but this, his fourth paper in Nature Neuroscience on the topic, is starting to win converts.

"If you ask me, this is the coming revolution," says Pouget. "It hit machine learning and cognitive science, and I think it's just hitting neuroscience. In 10 or 20 years, I think the way everybody thinks about the brain is going to be in these terms."

Not all of Pouget's neurons are in agreement, however. "…but I've been wrong before," he shrugs.
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Source:University of Rochester


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