Olfactory receptor usage is highly non-uniform, with some receptor types being orders of magnitude more abundant than others. Intriguingly, in mammalsthe receptors are replaced regularly  and the receptor distribution changes in response to olfactory experience.  We propose a theoretical model that explains these experimental observations. Our model suggests that the receptor distribution is tuned to maximize the amount of information about the olfactory environment , in accordance with the efficient coding hypothesis. The optimal receptor distribution depends on natural odor statistics, implying that a change in environment should lead to changes in receptor abundances. The effect is more pronounced when olfactory receptors respond strongly to a smaller number of odors. Our model also predicts that, between closely-related species, those with more neurons in the olfactory epithelium should express more receptor types . We show that simple dynamical rules for neural birth and death processes converge to the predicted optimum .
Olfactory receptor usage is highly non-uniform, with some receptor types being orders of magnitude more abundant than others. In mammals, the receptor neurons are replaced regularly , and the receptor distribution changes in response to olfactory experience. The observed changes are mysteriously context-dependent, with increased exposure to odorants leading variously to increased, decreased or unchanged abundance of activated receptors. We propose a theoretical model that explains these observations: the receptor distribution is tuned to efficiently encode information about the olfactory environment . This adaptation occurs before olfactory signals are decorrelated, leading to a new regime of efficient coding in which the optimal receptor distribution is sensitive to the global context of the correlated responses of all receptor types in the population. We demonstrate how this effect reproduces the context-dependence seen in experiments. We also show that the optimal receptor distribution can be achieved by following simple dynamical rules for neural birth and death processes .
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, in accordance with the efficient coding hypothesis. The
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depends on natural odor statistics, implying that a change in environment should lead to changes in receptor abundances. The effect is more pronounced when olfactory receptors respond strongly to a smaller number of odors. Our model also predicts that, between closely-related species, those with more neurons in the olfactory epithelium should express more receptor types . We show that
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converge to the predicted optimum