Adaptation of olfactory receptor abundances for efficient coding
- Flatiron Institute, United States
- École Normale Supérieure, France
- University of Pennsylvania, United States
Abstract
Olfactory receptor usage is highly heterogeneous, with some receptor types being orders of magnitude more abundant than others. We propose an explanation for this striking fact: the receptor distribution is tuned to maximally represent information about the olfactory environment in a regime of efficient coding that is sensitive to the global context of correlated sensor responses. This model predicts that in mammals, where olfactory sensory neurons are replaced regularly, receptor abundances should continuously adapt to odor statistics. Experimentally, increased exposure to odorants leads variously, but reproducibly, to increased, decreased, or unchanged abundances of different activated receptors. We demonstrate that this diversity of effects is required for efficient coding when sensors are broadly correlated, and provide an algorithm for predicting which olfactory receptors should increase or decrease in abundance following specific environmental changes. Finally, we give simple dynamical rules for neural birth and death processes that might underlie this adaptation.
Data availability
All the code necessary to reproduce our results and the figures from the paper is available on GitHub, at https://github.com/ttesileanu/OlfactoryReceptorDistribution. The olfactory receptor affinity data were originally published in Hallem et al. (2006) and Saito et al. (2009), and the olfactory receptor expression levels in mouse were originally published in Ibarra-Soria et al. (2017).
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Coding of odors by a receptor repertoiredoi:10.1016/j.cell.2006.01.050.
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Odor Coding by a Mammalian Receptor Repertoiredoi:10.1126/scisignal.2000016.
Article and author information
Author details
Vijay Balasubramanian
Funding
Simons Foundation (400425)
- Vijay Balasubramanian
Aspen Center for Physics (PHY-160761)
- Vijay Balasubramanian
Swartz Foundation
- Tiberiu Tesileanu
National Science Foundation (PHY-1734030)
- Tiberiu Tesileanu
- Vijay Balasubramanian
US-Israel Binational Science Foundation (2011058)
- Vijay Balasubramanian
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Tesileanu et al.
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.
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Adaptation of olfactory receptor abundances for efficient coding
eLife 8:e39279.
https://doi.org/10.7554/eLife.39279
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