acm-header
Sign In

Communications of the ACM

ACM TechNews

Artificial Networks Learn to Smell Like the Brain


Artist's conception of an electronic nose.

When asked to classify odors, artificial neural networks adopt a structure that closely resembles that of the brains olfactory circuitry.

Credit: Mark Hooper

A team of researchers from the Massachusetts Institute of Technology (MIT) and Columbia University found a machine learning model can train itself to smell by building an artificial neural network that mimics the brain's odor-processing olfactory circuits.

The researchers used the fruit fly's olfactory system as a template, building an artificial network comprised of an input layer, a compression layer, and an expansion layer; links between neurons would be rewired as the model learned to classify smells.

The network self-organized in minutes into a structure closely resembling the fly brain's olfactory network.

MIT's Guangyu Robert Yang said, "By showing that we can match the architecture [of the biological system] very precisely, I think that gives more confidence that these neural networks can continue to be useful tools for modeling the brain."

From MIT News
View Full Article

 

Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


 

No entries found

Sign In for Full Access
» Forgot Password? » Create an ACM Web Account