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A model of the role of adaptation and disadaptation in olfactory receptor neurons: implications for the coding of temporal and intensity patterns in odor signals
Authors:Moore  Paul A
Abstract:Natural odors occur as turbulent plumes resulting in spatiallyand temporally variable odor signals at the chemoreceptor cells.Concentrations can fluctuate widely within discrete packetsof odor and individual packets are very intermittent and unpredictable.Chemoreceptor cells display the temporally dynamic propertiesof adaptation and disadaptation, which serve to alter theirresponses to these fluctuating odor patterns. A computationalmodel, modified from one previously published, was used to investigate,the effect of adaptation and recovery of adaptation (disadaptation)on the spike output of model olfectory receptor cells undernatural stimulus conditions. The response characteristics ofmodel cells were based upon empirically determined dose-response,adaptation, disadaptation and flicker fusion properties of peripheralolfactory cells. The physiological properties of the model cell(adaptation and disadaptation rate and the dose-response relationship)could be modified independently, allowing assessment of therole of each in shaping the responses of the model cell. Completeadaptation and disadaptation time courses ranged from 500 ms(rapid cells) to 10 s (slow cells). The stimuli for the modelcells were quantified odor plume recordings obtained under avariety of biologically relevant flow conditions. As expected,the rapidly adapting model cells displayed different responsecharacteristics than the slowly adapting model cells to identicaltemporal odor profiles. Responses of the model cells dependedupon their adaptation and disadaptation rates, and the frequencycharacteristics of the odor presentation. These results indicatethat adaptation and disadaptation determine the range of concentrationfluctuations over which a particular cell will respond. Thus,these properties function as an olfactory equivalent of a band-passfilter in electronics. This type of filtering has implicationsfor the extraction of information from odor signals, men isthe coding of temporal and intensity features.
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