Investigating the properties of adaptation in a computational model of the olfactory sensory neuron

We developed a detailed computational model of an olfactory sensory neuron to investigate the functional properties of the sensory adaptation in the peripheral olfactory system. The model consists of a system of first-order differential equations that describes the time course of the different components considered, including the biochemical pathways in the cilia and the electrical compartments that represent the cilia, the dendrite, dendritic knob, the cell body and the initial segment of the axon. We used different protocols of stimulation to investigate the response of the model to constant or transient stimuli. In this way, it was possible to explore the occurrence of two types of adaptation mediated by distinct processes in the same cell. The results of the model suggest that different respiratory frequencies during sniffing behavior could be used by animals as a mechanism to avoid adaptation to odorants at the receptor cell level.