Sensitive and robust chemical detection using an olfactory brain-computer interface

When it comes to detecting volatile chemicals, biological olfactory systems far outperform all artificial chemical detection devices in their versatility, speed, and specificity. 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-computer interface that captures neuronal signals from an early stage of olfactory processing in awake mice combined with 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 that modifies the relative abundance of particular olfactory receptors in order to improve the sensitivity of our bio-electronic nose for specific chemical targets. Our recordings were stable over months, providing evidence for robust and stable decoding over time. The system also works in freely moving animals, allowing chemical detection to occur in real-world environments. Our bio-electronic nose outperforms current methods in terms of its stability, specificity, and versatility, setting a new standard for chemical detection.

Automated summary

Biological olfactory systems excel in detecting volatile chemicals, leading to a significant increase in using trained animals for chemical detection. A new alternative, a bio-electronic nose, has been proposed to directly read olfactory information from the brain, bypassing the need for behavioral communication with animals. By combining neuronal signals with machine learning techniques, this bio-electronic nose outperforms current methods in terms of stability, specificity, and versatility.