  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.
