A team from the US taught a neural network how to map and describe popular smells, with the hopes of digitizing them someday.
are activated. We know that odorant receptors react when chemicals attach to them, but scientists don’t know exactly what information these receptors transmit to the brain, or how the brain interprets these signals. It’s important to make predictive models while keeping biology in mind, he wrote.
Additionally, to really see how general the model could go, Ray points out that the team should have tested their neural network on more datasets separate from the training data. But until they do that, we can’t say how widely useful this model is, he adds. What’s more, the neural network doesn’t take into account how our perceptions of a smell can change with varying concentrations of odorants. “A really great example of this is a component of cat urine called MMB; it’s what makes cat pee stink” says Datta.” But at very low concentrations, it smells quite appealing and even delicious—it’s found in some coffees and wines. It’ll be interesting to see if future models can take this into account, Datta adds.
Overall, it’s important to note that this principal odor map “doesn’t explain the magic of how our nose sifts through a universe of chemicals and our brain alights on a descriptor,” says Datta. “That remains a profound mystery.” But it could facilitate experiments that help us interrogate how the brain perceives smells. Witschko and his collaborators are aware of other limitations of their map. “With this neural network, we’re making predictions on one molecule at a time.
Eventually, Wiltschko envisions a world where smell, like sound and vision, is fully digitizable. In the future he hopes machines will be able to detect smells and describe them, like speech to text capabilities on smartphones. Or similar to how we can demand a specific song from a smart speaker, they would be able to exude specific smells on demand. But there’s more to be done before that vision becomes reality. On the mission to digitize smell, Wiltschko says, “this is just the first step.
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