Researchers from the Southern Federal University Center for Neurotechnology Research and Development have developed a pioneering mouse AI biohybrid system designed to detect airborne substances. The accuracy of this system has improved from 60 percent to a perfect 100 percent, a milestone shared with the public through the Priority-2030 program of the Ministry of Science and Higher Education of the Russian Federation.
Traditional approaches to artificial olfaction faced limits because scientists had not fully mapped all odorant components or how they interact with the brain’s olfactory bulbs. This gap led researchers to merge an electronic nose with a biological sensing element, creating a hybrid solution that leverages the animal nose alongside artificial analysis.
In this biohybrid setup, the mouse functions as the primary sensor thanks to its exceptional sense of smell. Artificial intelligence then interprets brain activity related to smell and translates it into actionable results.
To implement the system, microelectrodes are implanted in the mouse’s olfactory bulb. The animal is then briefly anesthetized and placed in a chamber equipped with a biological signal amplifier. A computer program records activity in the brain region responsible for odor processing, and neural networks analyze the signals to identify the presented substance. This process enables rapid, accurate recognition of specific airborne compounds.
Researchers have also explored how the duration of anesthesia influences the central nervous system. In particular, studies examined a two hour anesthesia window and traced how olfactory system activity evolves over that period, culminating in a mathematical description of the dynamics observed.
As anesthesia progresses, the olfactory brain shows heightened efficiency compared to wakeful or sleep states. The data indicate that neuronal responses rise and reach peak activity during the second hour of anesthesia, marking a deep anesthesia stage as a critical moment for detection performance.
Potential applications for this technology span multiple fields. It could be employed to identify dangerous airborne substances such as explosives or opioids, as well as substances tied to oncological diseases. The system has the potential to enhance public safety and health by enabling real time detection in various environments.
Looking ahead, researchers plan to advance the technology toward continuous real time operation, enabling ongoing monitoring and rapid interpretation of airborne chemical signatures across diverse settings.