How machine learning is helping neuroscientists understand the brain

"Just because machine learning and evolution appear to use a similar principle doesn’t mean algorithms performed by brain tissue and algorithms performed by computers will resemble each other. But it turns out they do: the architecture that works best for computer vision algorithms is modeled after the visual part of the primate brain. More remarkably, the precise computational outputs learned by trial-and-error – not designed from on high – allow us to predict how real neurons will respond when a monkey looks at images. For all our intelligence, the best hand-crafted visual models, built upon the principles of signal processing theory, have predicted most of these real responses poorly. Even the early, successful models of more basic neural computations are falling quickly to machine learning models that explain the same data better."


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