Adaptation of olfactory receptor abundances for efficient coding

ELife
Tiberiu TesileanuVijay Balasubramanian

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.

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Citations

Sep 25, 2019·Proceedings of the National Academy of Sciences of the United States of America·Shanshan QinYuhai Tu
Jan 10, 2021·Communications Biology·Sidney R LehkyAnne B Sereno
Jun 14, 2020·Neuron·Florentina SotoDaniel Kerschensteiner
Oct 12, 2021·PLoS Computational Biology·Gaia TavoniVijay Balasubramanian

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BETA
RNAseq

Software Mentioned

Matlab

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