History-dependent ephaptic interactions in paired olfactory receptor neurons
Olfactory sensing begins with the transduction of odors into receptor currents on the dendrites of olfactory receptor neurons (ORNs). In insects and many other arthropods, ORNs are grouped stereotypically in hair-like sensilla on the surface of olfactory organs, enabling mutual inhibition through non-synaptic 'ephaptic' interactions (NSIs). Given the electrical, and therefore virtually instantaneous, nature of NSIs, it has been hypothesized that they contribute to processing fast temporal elements of mixed odor plumes. Here, we present single sensillum recordings and computational modeling that characterize NSIs during short offset dual-odor stimulations in the olfactory sensilla of adult female Drosophila melanogaster. We find in the experiments that the magnitude of inhibition between co-housed ORNs cannot be predicted by their instantaneous activity (firing rate) alone. It is adaptation-dependent, with strong effects only occurring when the inhibited ORN is adapted. This limits the usefulness of NSIs for fast odor processing when ORNs lack time to adapt. We reproduced the observed phenomena in a computational model and use this model to explain how the adaptation-dependence of NSI-mediated inhibition arises from nonlinearities in neural responses. We conclude that NSIs are unlikely to support the encoding of fast temporal dynamics in mixed odor stimuli, instead contributing to slower peripheral processing, supporting roles such as novelty detection. More broadly, we demonstrate how the nonlinear interactions of fairly simple electrical components lead to non-intuitive results, offering insight into the longstanding debate around ephaptic interactions in other systems, such as the mammalian CNS. ### Competing Interest Statement The authors have declared no competing interest. Leverhulme Trust, https://ror.org/012mzw131, RPG-2019-232 Engineering and Physical Sciences Research Council, https://ror.org/0439y7842, EP/P006094/1, EP/S030964/1
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