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Odor representations are structured by heterogeneous tuning and concentration-dependence of functionally distinct olfactory sensory neuron subpopulations.

Jason De Castro, Shawn D. BurtoniD, Joel Hallkaj, Matt WachowiakiD

Abstract

Olfactory stimuli (odorants) are represented by combinatorial patterns of olfactory sensory neuron (OSN) activation that are translated into spatially-organized glomerular maps at their input to the CNS. How glomerular maps relate to odorant features - including chemical structure and concentration - remains a key question in understanding the neural mechanisms of odor coding. Here, we compared glomerular response maps for the same 59 odorants across three concentration regimes, using GCaMP6 imaging from OSN axon terminals in the olfactory bulb (OB) of the anesthetized mouse. At the lowest regime, in which concentrations were chosen to distinguish the most sensitive glomeruli for each odorant, glomeruli were exceptionally narrowly tuned and responses across glomeruli were extremely sparse. We then compared responses at two higher-concentration regimes, 'low' and 'high', differing by 25-fold from each other and 2 - 5 log units higher than the 'most-sensitive' regime. Increasing concentration broadened tuning of OSN inputs; this broadening was heterogeneous across chemical space and was well-described by classifying glomeruli into several subpopulations with distinct consensus tuning profiles. Each subpopulation was selectively tuned to one or a few odorant chemical classes and spatially clustered in a manner consistent with the projection patterns of receptor-defined OSN classes. Glomerular subpopulations retained distinct tuning and spatial localization even at the highest concentrations. OSN subpopulations thus sample chemical space nonuniformly across a large concentration range. These results suggest a lower-dimensional structure in the representation of odorant information that largely reflects OSN subpopulations which, in turn, map to olfactory receptor subfamilies. This organization may enable distinct odor coding strategies for different OSN classes and for parts of chemical feature space with distinct ethological relevance.

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02 /Specification & Classification

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