What’s That Smell? Analyzing How Different Smells are Detected

DCF 1.0

Evolutionarily speaking, smell was the first sense to develop, and yet we still know so little about it. We measure light intensity in watts and sound in decibels, but measuring smell is more arduous because odor environments are exceedingly complex and difficult to characterize as a result.

In order to understand how olfactory receptor neurons (ORNs) can detect distinct odors in a complicated environment, Yale scientists led by Nirag Kadakia have developed a theoretical computer model of fruit fly ORNs. Organisms identify scents through a process called combinatorial coding; for example, instead of having one receptor for the smell of an apple, the odor will activate a unique pattern of different odor receptors. The brain interprets this pattern as the scent of an apple. While fruit flies have around fifty to sixty of these receptors, humans have several hundred, allowing for the detection of subtle differences in odor. As ORNs acclimate to the smells in a particular environment, it becomes much easier to identify new or intensifying ones.

The ability to identify how scent environments are distinguished through computer algorithms and modeling is a large step in smell-related technology. “It could have some implications for how we can develop technologies to harness smell, to replicate smell, to enhance smell… for situations in which people cannot perceive odors as well,” Kadakia said. The next step in their research is to compare their theoretical findings to behavioral responses of fruit flies to evaluate the accuracy of their model in predicting real-world phenomena.