Harvard University researchers have developed a machine-learning algorithm to train a computer to recognize the neural patterns associated with various scents, and to identify whether specific odors are present in a mix of smells.
The algorithm works like other pattern-recognition systems, only the patterns are the neural activation patterns of mice reacting to particular odors.
"Essentially, one odor causes a particular neural activation pattern, and another odor causes a different pattern," says Harvard professor Venkatesh Murthy.
The researchers trained the algorithm to recognize those patterns by gathering data on the neural activation patterns associated with various odors by imaging the brains of mice. They used 80% of the data to train the system to recognize patterns of activation for particular odors.
The system examines the patterns and randomly selects pixels, and if those pixels reach a certain level, the system concludes the target odor is present.
Over thousands of trials, the algorithm eventually became as successful as mice at identifying whether a specific odor was present in a mix of scents.
The researchers say their study suggests computer-learning algorithms could be potentially powerful tools to examine the sense of smell, and a way to design and conduct experiments in a virtual space before performing them in the real world.
From Harvard Gazette
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