Bifurcation enhances temporal information encoding in the olfactory periphery

TL;DR

This paper demonstrates that Drosophila olfactory receptor neurons utilize bifurcation dynamics to efficiently encode temporal odor information, with adaptation mechanisms maintaining proximity to bifurcation without extra feedback.

Contribution

It reveals how bifurcation proximity enhances odor signal encoding and shows that adaptation alone keeps neurons near this critical point, explaining observed adaptation behaviors.

Findings

Bifurcation proximity improves temporal encoding of odor signals.

Adaptation maintains neurons near bifurcation without additional feedback.

Biophysical model matches measured adaptation in Drosophila ORNs.

Abstract

Living systems continually respond to signals from the surrounding environment. Survival requires that their responses adapt quickly and robustly to the changes in the environment. One particularly challenging example is olfactory navigation in turbulent plumes, where animals experience highly intermittent odor signals while odor concentration varies over many length- and timescales. Here, we show theoretically that Drosophila olfactory receptor neurons (ORNs) can exploit proximity to a bifurcation point of their firing dynamics to reliably extract information about the timing and intensity of fluctuations in the odor signal, which have been shown to be critical for odor-guided navigation. Close to the bifurcation, the system is intrinsically invariant to signal variance, and information about the timing, duration, and intensity of odor fluctuations is transferred efficiently. Importantly, we find that proximity to the bifurcation is maintained by mean adaptation alone and therefore does not require any additional feedback mechanism or fine-tuning. Using a biophysical model with calcium-based feedback, we demonstrate that this mechanism can explain the measured adaptation characteristics of Drosophila ORNs.