Parameter Mapping Sonification of Human Olfactory Thresholds

SIMPLE SUMMARY: It is challenging to deduce the bioactivity of volatile compounds from their chemical characteristics. We therefore previously used parameter mapping sonification to study volatiles secreted by some insects that repel predators. Chemical parameters from single volatiles were linked to sound parameters. The peak sound pressure values from the gathered audio clips contain information about the repellent effect of the compounds. Here, human olfactory thresholds were investigated. The volatiles were subjected to parameter mapping, and the results show that these thresholds are correlated with the peak sound pressures. More generally, the results illustrate that the sonification of volatiles helps to better understand their bioactivity. ABSTRACT: An objective of chemical ecology is to understand the chemical diversity across and within species, as well as the bioactivity of chemical compounds. We previously studied defensive volatiles from phytophagous insects that were subjected to parameter mapping sonification. The created sounds contained information about the repellent bioactivity of the volatiles, such as the repellence from the volatiles themselves when tested against live predators. Here, we applied a similar sonification process to data about human olfactory thresholds. Randomized mapping conditions were used and a peak sound pressure, Lpeak, was calculated from each audio file. The results indicate that Lpeak values were significantly correlated with the olfactory threshold values (e.g., r(S) = 0.72, t = 10.19, p < 0.001, Spearman rank-order correlation; standardized olfactory thresholds of 100 volatiles). Furthermore, multiple linear regressions used the olfactory threshold as a dependent variable. The regressions revealed that the molecular weight, the number of carbon and oxygen atoms, as well as the functional groups aldehyde, acid, and (remaining) double bond were significant determinants of the bioactivity, while the functional groups ester, ketone, and alcohol were not. We conclude that the presented sonification methodology that converts chemicals into sound data allows for the study of their bioactivities by integrating compound characteristics that are easily accessible.