Mice are able to distinguish odors in a split second thanks to rapid interactions between neurons in the olfactory bulb, according to the NYU Langone website. Previously, it was believed that primary odor processing occurs in the cerebral cortex, which is associated with perception and consciousness, but new data point to an earlier and simpler mechanism.
Experiments have shown that the very first wave of signals from olfactory neurons plays a crucial role. When a mouse inhales, millions of sensory cells in the nose activate and transmit signals to the so-called glomeruli of the olfactory bulb, which are connected to the mitral and tufted cells. Within the first 50 milliseconds, a specific pattern of activity is formed that determines the odor the animal perceives.
Subsequent signals are largely ignored. Scientists describe this mechanism as temporal filtering. The idea is that the brain registers the first activated neural circuits and then suppresses later incoming information. This allows for the rapid isolation of a single odor, even in a complex environment with other background odors.
Remarkably, the same odor elicited the same early activity pattern regardless of its concentration.
This means that the recognition system relies not on signal strength, but on its temporal structure. This approach makes perception more stable and reliable.
The authors emphasize that the entire process occurs extremely quickly. In mice, a full inhalation cycle takes about a quarter of a second, but the decision about what they are feeling is made at the very beginning of this interval. In humans, inhalation takes longer, but the principle may be the same.
"Our results challenge the fundamental idea that such computations occur in the cerebral cortex. This study demonstrates for the first time how temporal filtering is used to distinguish odors," said study author Dmitry Rinberg.
The findings not only clarify the basic mechanisms of brain function but also have practical applications. Understanding how biological systems quickly distinguish meaningful signals from noise could help create more efficient algorithms for AI and sensor technologies.
The discovery may also lead to improved disease diagnosis. It has previously been shown that loss of smell can be an early sign of serious illness.
