Concentration-invariant odor representation in the olfactory system by presynaptic inhibition

Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System

In Drosophila, olfactory information received by olfactory receptor neurons (ORNs) is first processed by an incoherent feed forward neural circuit in the antennal lobe (AL) that consists of ORNs (input), inhibitory local neurons (LNs), and projection neurons (PNs). This “early” olfactory information processing has two important characteristics. First, response of a PN to its cognate ORN is normalized by the overall activity of other ORNs, a phenomenon termed “divisive normalization.” Second, PNs respond strongly to the onset of ORN activities, but they adapt to prolonged or continuously varying inputs. Despite the importance of these characteristics for learning and memory, their underlying mechanisms are not fully understood. Here, we develop a circuit model for describing the ORN-LN-PN dynamics by including key neuron-neuron interactions such as short-term plasticity (STP) and presynaptic inhibition (PI). By fitting our model to experimental data quantitatively, we show that a strong STP balanced between short-term facilitation (STF) and short-term depression (STD) is responsible for the observed nonlinear divisive normalization in Drosophila. Our circuit model suggests that either STP or PI alone can lead to adaptive response. However, by comparing our model results with experimental data, we find that both STP and PI work together to achieve a strong and robust adaptive response. Our model not only helps reveal the mechanisms underlying two main characteristics of the early olfactory process, it can also be used to predict PN responses to arbitrary time-dependent signals and to infer microscopic properties of the circuit (such as the strengths of STF and STD) from the measured input-output relation. Our circuit model may be useful for understanding the role of STP in other sensory systems.

Primacy coding facilitates effective odor discrimination when receptor sensitivities are tuned

The olfactory system faces the difficult task of identifying an enormous variety of odors independent of their intensity. Primacy coding, where the odor identity is encoded by the receptor types that respond earliest, might provide a compact and informative representation that can be interpreted efficiently by the brain. In this paper, we analyze the information transmitted by a simple model of primacy coding using numerical simulations and statistical descriptions. We show that the encoded information depends strongly on the number of receptor types included in the primacy representation, but only weakly on the size of the receptor repertoire. The representation is independent of the odor intensity and the transmitted information is useful to perform typical olfactory tasks with close to experimentally measured performance. Interestingly, we find situations in which a smaller receptor repertoire is advantageous for discriminating odors. The model also suggests that overly sensitive receptor types could dominate the entire response and make the whole array useless, which allows us to predict how receptor arrays need to adapt to stay useful during environmental changes. Taken together, we show that primacy coding is more useful than simple binary and normalized coding, essentially because the sparsity of the odor representations is independent of the odor statistics, in contrast to the alternatives. Primacy coding thus provides an efficient odor representation that is independent of the odor intensity and might thus help to identify odors in the olfactory cortex.

Humans can identify odors independent of their intensity. Experimental data suggest that this is accomplished by representing the odor identity by the earliest responding receptor types. Using theoretical modeling, we here show that such a primacy code outperforms alternative encodings and allows discriminating odors with close to experimentally measured performance. This performance depends strongly on the number of receptors considered in the primacy code, but the receptor repertoire size is less important. The model also suggests a strong evolutionary pressure on the receptor sensitivities, which could explain observed receptor copy number adaptations. By predicting psycho-physical experiments, the model will thus contribute to our understanding of the olfactory system.

Normalized Neural Representations of Complex Odors

The olfactory system removes correlations in natural odors using a network of inhibitory neurons in the olfactory bulb. It has been proposed that this network integrates the response from all olfactory receptors and inhibits them equally. However, how such global inhibition influences the neural representations of odors is unclear. Here, we study a simple statistical model of the processing in the olfactory bulb, which leads to concentration-invariant, sparse representations of the odor composition. We show that the inhibition strength can be tuned to obtain sparse representations that are still useful to discriminate odors that vary in relative concentration, size, and composition. The model reveals two generic consequences of global inhibition: (i) odors with many molecular species are more difficult to discriminate and (ii) receptor arrays with heterogeneous sensitivities perform badly. Comparing these predictions to experiments will help us to understand the role of global inhibition in shaping normalized odor representations in the olfactory bulb.

Specific volatile compounds from mango elicit oviposition in gravid Bactrocera dorsalis females

Selecting a suitable oviposition site is crucial to the fitness of female insects because it determines the successful development of their offspring. During the oviposition process, an insect must use cues from the external environment to make an appropriate choice of where to lay eggs. Generalist insects can detect and react to a plethora of cues, but are under selection pressure to adopt the most reliable ones to override noise and increase efficiency in finding hosts. The oriental fruit fly, Bactrocera dorsalis (Hendel), is a generalist that utilizes a multitude of fruits as oviposition sites. However, the identity and nature of oviposition stimulants for B. dorsalis is not well known. Recently, we identified a volatile compound γ-octalactone that elicits an innate oviposition response in B. dorsalis. We screened 21 EAD-active volatiles, identified from mango, for their oviposition stimulant activity. 1-Octen-3-ol, ethyl tiglate, and benzothiazole instigated oviposition in gravid B. dorsalis females. Flies deposited most of their eggs into pulp discs with oviposition-stimulants, and only a small fraction of eggs were laid into control discs. In a binary choice oviposition assay, 95.1, 93.7, and 65.6 % of eggs were laid in discs treated with 1-octen-3-ol, ethyl tiglate, and benzothiazole, respectively. Single plate two-choice assays proved that oviposition-stimulants were crucial in oviposition site selection by gravid female B. dorsalis. In simulated semi-natural assays, gravid B. dorsalis females accurately differentiated between fruits with and without 1-octen-3-ol, ethyl tiglate, and γ-octalactone by laying more eggs on the treated fruit. However, benzothiazole did not elicit an increase in oviposition when presented in this context. Our results suggest that the identified oviposition-stimulants are 'key' compounds, which the flies associate with suitable oviposition sites.