Research data for paper History-dependent ephaptic interactions in paired olfactory receptor neurons

Research data for paper published in bioRxiv, 26 January 2026 (Pre-print).
Data contains spike counts from Single Sensillum Recordings taken from olfactory sensilla of female Drosophila melanogaster during odor stimulation and output from a spiking sensillum model. The model code is available at: https://github.com/tnowotny/drosophila-nsi/
Abstract
Olfactory sensing begins when airborne chemicals activate sensory neurons, converting odor molecules into electrical signals that the brain can interpret. In insect olfactory sensilla, olfactory receptor neurons (ORNs) share a confined space and can inhibit one another via rapid, non-synaptic ephaptic interactions, which have been proposed to help encode mixed odor information. We combined single-sensillum recordings in adult female Drosophila melanogaster with computational modeling to test how these interactions operate during brief, closely spaced dual-odor stimuli. In experiments, the strength of inhibition could not be predicted from instantaneous ORN firing rate alone and instead depended strongly on whether the inhibited ORN was adapted, with pronounced effects emerging only after adaptation. Our model reproduced these findings and suggested that this adaptation dependence arises from nonlinearities in ORN responses. Overall, we conclude that ephaptic interactions are unlikely to encode rapid temporal dynamics in odor mixtures, instead supporting slower peripheral functions such as novelty detection.
Contents
Excel file with multiple sheets, each related to a different dataset within the paper.
readme.txt file containing Description information