We showed previously (Gorur-Shandilya et al 2017) that Drosophila olfactory receptor neurons (ORNs) expressing the co-receptor Orco scale their gain inversely with mean odor intensity according to Weber-Fechner's law. Here we show that this front-end adaptation promotes the reconstruction of odor identity from dynamic odor signals, even in the presence of confounding background odors and rapid intensity fluctuations. These enhancements are further aided by known downstream transformations in the antennal lobe and mushroom body. Our results, which are applicable to various odor classification and reconstruction schemes, stem from the fact that this adaptation mechanism is not intrinsic to the identity of the receptor involved. Instead, a feedback mechanism adjusts receptor sensitivity based on the activity of the receptor-Orco complex, according to Weber-Fechner's law. Thus, a common scaling of the gain across Orco-expressing ORNs may be a key feature of ORN adaptation that helps preserve combinatorial odor codes in naturalistic landscapes.
All data generated or analysed during this study are included in the manuscript and supporting files. All software codes are available via GitHub (https://github.com/emonetlab/ORN-WL-gain-control).
- Nirag Kadakia
- Thierry Emonet
- Nirag Kadakia
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Fred Rieke, University of Washington, United States
© 2019, Kadakia & Emonet
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.