Researchers at the Salk Institute and the University of California, San Diego have found the mechanism the fruit fly brain employs to identify olfactory similarities could inform the design of future search algorithms.
A study review found when fruit flies initially sense an odor, 50 neurons fire in a unique configuration, but instead of hashing that data to reduce the number of hashes associated with the smell, the flies expand the dimension to 2,000 neurons with the top activity as the "hash" for that smell.
In applying this process to three standard datasets used to test search algorithms, the team found the fly strategy enhanced performance.
"A dream shared by neurobiologists and computer scientists is to understand how the brain computes well enough that we can adapt its methods to improve machine computation," says Salk professor Charles Stevens. "Our [research] provides a proof of principle that this dream may become reality."
From Salk Institute for Biological Studies
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