Odorant mixtures elicit less variable and faster responses than pure odorants

HO KA CHAN; FABIAN HERSPERGER; MARACHLIAN EMILIANO; SMITH BRIAN; FERNANDO LOCATELLI; SZYSZKA PAUL; THOMAS NOWOTNY

PLOS COMPUTATIONAL BIOLOGY

PUBLIC LIBRARY SCIENCE

Lugar: San Francisco; Año: 2018 p. 1 - 27

1553-734X

In natural environments, odors are typically mixtures of several different chemical compounds. However, theimplications of mixtures for odor processing have not been fully investigated. We have extended a standardolfactory receptor model to mixtures and found through its mathematical analysis that odorant-evoked activitypatterns are more stable across concentrations and first-spike latencies of receptor neurons are shorter formixtures than for pure odorants. Shorter first-spike latencies arise from the nonlinear dependence of binding rateon odorant concentration, commonly described by the Hill coefficient, while the more stable activity patternsresult from the competition between different ligands for receptor sites. These results are consistent withobservations from numerical simulations and physiological recordings in the olfactory system of insects. Ourresults suggest that mixtures allow faster and more reliable olfactory coding, which could be one of the reasonswhy animals often use mixtures in chemical signaling.