Abstract
When it comes to simultaneous versatility, speed, and specificity in detecting volatile chemicals, biological olfactory systems far outperform all artificial chemical detection devices. Consequently, the use of trained animals for chemical detection in security, defense, healthcare, agriculture, and other applications has grown astronomically. However, the use of animals in this capacity requires extensive training and behavior-based communication. Here we propose an alternative strategy, a bio-electronic nose, that capitalizes on the superior capability of the mammalian olfactory system, but bypasses behavioral output by reading olfactory information directly from the brain. We engineered a brain-machine interface that captures neuronal signals from an early stage of olfactory processing in awake mice, and used machine learning techniques to form a sensitive and selective chemical detector. We chronically implanted a grid electrode array on the surface of the mouse olfactory bulb and systematically recorded responses to a large battery of odorants and odorant mixtures across a wide range of concentrations. The bio-electronic nose has a comparable sensitivity to the trained animal and can detect odors on a variable background. We also introduce a novel genetic engineering approach designed to improve the sensitivity of our bio-electronic nose for specific chemical targets. Our bio-electronic nose outperforms current detection methods and unlocks a wide spectrum of civil, medical and environmental applications.
Competing Interest Statement
The authors have declared no competing interest.
