Adaptive temporal processing of odor stimuli

Abstract

The olfactory system translates chemical signals into neuronal signals that inform behavioral decisions of the animal. Odors are cues for source identity, but if monitored long enough, they can also be used to localize the source. Odor representations should therefore be robust to changing conditions and flexible in order to drive an appropriate behavior. In this review, we aim at discussing the main computations that allow robust and flexible encoding of odor information in the olfactory neural pathway.

Keywords: Olfactory system; Sensory adaptation; Stimulus dynamics.

Fig. 1

Temporal aspects of the odor response within a single neuron. ORNs (blue) extend their dendrites in hair-like structures called sensilla. Single sensillum recordings (a) are carried out in vivo from the intact antenna and allow the quantification of the LFP (b) and the spiking activity of the neuron (c) (Clyne et al. 1997). In a sliced antenna preparation, it is possible to access the cell body for patch clamp (d) (Cao et al. 2016). This technique allows the quantification of somatic and dendritic currents (up to a certain distance from the recording site) (e). ORNs expressing the same OR send their axons to a single glomerulus in the antennal lobe, where they make synaptic connections with local neurons (LNs, green) and uniglomerular projection neurons (PNs, red). 2-photon calcium imaging allows the quantification of the presynaptic activity (f) reported by the calcium indicator GCaMP genetically expressed in specific ORNs (Riemensperger et al. 2012). All the curves are schematic representations of the neuron response to a 1s odor puff reported by the specified technique. See main text for more detail

Fig. 2

Comparing the effect of background stimulus intensity on the response of light- and odor-sensitive neurons. (a) Response of photoreceptors to light stimuli of different intensity in dark-adapted conditions (black) spans three-log units of light intensity. In the presence of an adapting background light (intensity indicated by the arrows), photoreceptor sensitivity shifts up to more than three-log units (from black to purple). Adaptation to the background stimulus increases the basal potential (first data point of each curve) and pushes response saturation to higher light intensities, keeping the response dynamic range centered around the mean stimulus. Data are from Laughlin and Hardie (1978) reproduced with permission of S. Laughlin. (b) Response of Drosophila ORN ab3A to two odorants at different concentrations. Odor puffs are presented isolated (black) or on a background of the same odorant at concentrations indicated by the arrow. Data are same as in Fig. 4 of Martelli et al. (2013), but plotted as a function of the total stimulus concentration (C_back + C_test) for comparison with the data of the photoreceptors. Adaptation to the background only slightly increases the basal firing rate (first data point of each curve). The response reaches saturation at lower firing rates and at the same concentration as in no-background conditions. (c) Response of frog ORNs: receptor current (top) and firing rate (bottom) from (Reisert and Matthews 1999), reproduced with permission of J. Reisert. Adaptation to the background decrease receptor current and firing rate. The ORN dynamic range does not simply shift to the right, and, for the highest background, the neuron stops firing spikes

Fig. 3

Adaptation changes the combinatorial representation. a Response of two ORNs to stimuli of increasing intensities. Red and blue arrows indicate the response of two ORNs to a given stimulus intensity (dotted line). b In the presence of a background the odor representation in the two ORNs (red and blue arrows) differs from the non-adapted response (a). c, d A background stimulus, indicated by the black arrow, changes the response function of ORN1. ORN2 is not sensitive to the background stimulus and its response function is unaffected by the background stimulus