Perireceptor and receptor events in olfaction. Comparison of concentration and flux detectors: a modeling study

Gain control in olfactory receptor neurons and the detection of temporal fluctuations in odor concentration

The ability of the cockroach to locate an odor source in still air suggests that the temporal dynamic of odor concentration in the slowly expanding stationary plume alone is used to infer odor source distance and location. This contradicts with the well-established view that insects use the wind direction as the principle directional cue. This contribution highlights the evidence for, and likely functional relevance of, the capacity of the cockroach's olfactory receptor neurons to detect and process-from one moment to the next-not only a succession of odor concentrations but also the rates at which concentration changes. This presents a challenge for the olfactory system because it must detect and encode the temporal concentration dynamic in a manner that simultaneously allows invariant odor recognition. The challenge is met by a parallel representation of odor identity and concentration changes in a dual pathway that starts from olfactory receptor neurons located in two morphologically distinct types of olfactory sensilla. Parallel processing uses two types of gain control that simultaneously allocate different weight to the instantaneous odor concentration and its rate of change. Robust gain control provides a stable sensitivity for the instantaneous concentration by filtering the information on fluctuations in the rate of change. Variable gain control, in turn, enhances sensitivity for the concentration rate according to variations in the duration of the fluctuation period. This efficiently represents the fluctuation of concentration changes in the environmental context in which such changes occur.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

Comparative analysis of the boundary layer filtering of odor signals in the amblypygid (whip spider) species Paraphrynus laevifrons and Phrynus marginemaculatus

Amblypygids use a pair of modified walking legs (antenniform) as chemosensory and mechanosensory appendages. At the tip of these legs are covered in chemosensory sensilla, which the animals use to sample odor stimuli in their environment by moving the antenniform leg through the air. We designed a set of experiments to measure the filtering effect that aerodynamic boundary layers have on the temporal and spatial structure of chemical stimuli. In addition, two different species of amblypygids (Paraphrynus laevifrons and Phrynus marginemaculatus) that live in two distinct habitats were used for a comparative analysis. Pulses of a tracer molecule were quantified at different distances and flow velocities using an electrochemical detection system. Temporal attributes of the chemical pulses were extracted and were statistically compared across velocities, distances from the appendage, and the two species. Overall, the boundary layer significantly decreased the concentration and increased the duration of pulses for both species. This filtering effect was more pronounced for P. marginemaculatus than P. laevifrons, as the chemical signal was lower in concentration and longer in duration at any distance from the antenniform leg. It is speculated that the difference in boundary layer filtering, as a function of appendage morphology, is tuned to the different types of odor plumes in these animals' native habitats.

Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth

In order to understand how olfactory stimuli are encoded and processed in the brain, it is important to build a computational model for olfactory receptor neurons (ORNs). Here, we present a simple and reliable mathematical model of a moth ORN generating spikes. The model incorporates a simplified description of the chemical kinetics leading to olfactory receptor activation and action potential generation. We show that an adaptive spike threshold regulated by prior spike history is an effective mechanism for reproducing the typical phasic-tonic time course of ORN responses. Our model reproduces the response dynamics of individual neurons to a fluctuating stimulus that approximates odorant fluctuations in nature. The parameters of the spike threshold are essential for reproducing the response heterogeneity in ORNs. The model provides a valuable tool for efficient simulations of olfactory circuits.

Encoding of Slowly Fluctuating Concentration Changes by Cockroach Olfactory Receptor Neurons Is Invariant to Air Flow Velocity

The ON and OFF olfactory receptor neurons (ORNs) on the cockroach antenna display a high sensitivity for the rate at which odorant concentration changes. That rate of change acts as a gain control signal that improves the sensitivity of both ORNs for fluctuating concentration changes. By means of extracellular recording techniques, we find in both types of ORNs an increased gain for the rate of concentration change when the duration of the oscillation period increases. During long-period oscillations with slow concentration changes, the high gain for the rate of concentration change improves the ORNs ability to detect low rates of concentration changes when the fluctuations are weak. To be useful in plume tracking, gain control must be invariant to the air flow velocity. We describe that raising the level of the flow rate has no effect on the ON-ORN responses to concentration changes down to rates of 2%/s, but exerts a slight increase on the OFF-ORN response during these extremely low rates. At 4%/s, however, the OFF-ORN response is also unaffected by the flow rate level. The asymmetry corresponds with a generally higher sensitivity of the OFF-ORN to concentration changes. Nevertheless, the gain of both ORNs for the concentration rate change is robust against the air flow velocity. This makes possible an instantaneous analysis of the rate of concentration change for both directions of change by one or the other ORN. Therefore, the ON and OFF ORNs are optimized to encode concentration increments and decrements in a turbulent odorant plume.

Monte Carlo Analysis of Molecule Absorption Probabilities in Diffusion-Based Nanoscale Communication Systems with Multiple Receivers

For biomedical applications of nanonetworks, employing molecular communication for information transport is advantageous over nano-electromagnetic communication: molecular communication is potentially biocompatible and inherently energy-efficient. Recently, several studies have modeled receivers in diffusion-based molecular communication systems as "perfectly monitoring" or "perfectly absorbing" spheres based on idealized descriptions of chemoreception. In this paper, we focus on perfectly absorbing receivers and present methods to improve the accuracy of simulation procedures that are used to analyze these receivers. We employ schemes available from the chemical physics and biophysics literature and outline a Monte Carlo simulation algorithm that accounts for the possibility of molecule absorption during discrete time steps, leading to a more accurate analysis of absorption probabilities. Unlike most existing studies that consider a single receiver, this paper analyzes absorption probabilities for multiple receivers deterministically or randomly deployed in a region. For random deployments, the ultimate absorption probabilities as a function of transmitter-receiver distance are shown to fit well to power laws; the exponents derived become more negative as the number of receivers increases up to a limit beyond which no additional receivers can be "packed" in the deployment region. This paper is expected to impact the design of molecular nanonetworks with multiple absorbing receivers.

A Novel Electrical Model for Advection-Diffusion-Based Molecular Communication in Nanonetworks

In this paper, we propose an end-to-end electrical model to characterize the communication between two nanomachines via advection-diffusion motion along the conventional pipe medium. For this modeling, we consider three modules consisting of transmitter, advection-diffusion propagation and receiver. The modulation scheme and releasing molecules through the conventional pipe medium from the transmitter nanomachine is represented in the transmitter module. The advection-diffusion propagation of molecules along the flow-induced path is shown in advection-diffusion propagation module, and the demodulation scheme of bounded particles at the receiver nanomachine is characterized in the receiver module. Our objective is to find an electrical model of each module under the zero initial condition which enables us to represent the electrical circuit related to each module. The transmitter and the signal propagation models are built on the basis of the molecular advection-diffusion physics, whereas the receiver model is interpreted by stemming from the theory of the ligand-receptor binding chemical process. In addition, we employ the transfer function of modules to derive the normalized gain and the delay of each module. Supported by numerical results, we analyze the effect of physical parameters of the pipe medium on the total normalized gain and delay of molecular communications.

Transduction in Drosophila olfactory receptor neurons is invariant to air speed

In the vertebrate nose, increasing air speed tends to increase the magnitude of odor-evoked activity in olfactory receptor neurons (ORNs), given constant odor concentration and duration. It is often assumed that the same is true of insect olfactory organs, but this has not been directly tested. In this study, we examined the effect of air speed on ORN responses in Drosophila melanogaster. We constructed an odor delivery device that allowed us to independently vary concentration and air speed, and we used a fast photoionization detector to precisely measure the actual odor concentration at the antenna while simultaneously recording spikes from ORNs in vivo. Our results demonstrate that Drosophila ORN odor responses are invariant to air speed, as long as odor concentration is kept constant. This finding was true across a >100-fold range of air speeds. Because odor hydrophobicity has been proposed to affect the air speed dependence of olfactory transduction, we tested a >1,000-fold range of hydrophobicity values and found that ORN responses are invariant to air speed across this full range. These results have implications for the mechanisms of odor delivery to Drosophila ORNs. Our findings are also significant because flies have a limited ability to control air flow across their antennae, unlike terrestrial vertebrates, which can control air flow within their nasal cavity. Thus, for the fly, invariance to air speed may be adaptive because it confers robustness to changing wind conditions.

Numerical simulations of odorant detection by biologically inspired sensor arrays

The antennules of many marine crustaceans enable them to rapidly locate sources of odorant in turbulent environmental flows and may provide biological inspiration for engineered plume sampling systems. A substantial gap in knowledge concerns how the physical interaction between a sensing device and the chemical filaments forming a turbulent plume affects odorant detection and filters the information content of the plume. We modeled biological arrays of chemosensory hairs as infinite arrays of odorant flux-detecting cylinders and simulated the fluid flow around and odorant flux into the hair-like sensors as they intercepted a single odorant filament. As array geometry and sampling kinematics were varied, we quantified distortion of the flux time series relative to the spatial shape of the original odorant filament as well as flux metrics that may be important to both organisms and engineered systems attempting to measure plume structure and/or identify chemical composition. The most important predictor of signal distortion is the ratio of sensor diameter to odorant filament width. Achieving high peak properties (e.g. sharpness) of the flux time series and maximizing the total number of odorant molecules detected appear to be mutually exclusive design goals. Sensor arrays inspired specifically by the spiny lobster Panulirus argus and mantis shrimp Gonodactylaceus falcatus introduce little signal distortion but these species' neural systems may not be able to resolve plume structure at the level of individual filaments via temporal properties of the odorant flux. Current chemical sensors are similarly constrained. Our results suggest either that the spatial distribution of flux across the aesthetasc array is utilized by P. argus and G. falcatus, or that such high spatiotemporal resolution is unnecessary for effective plume tracking.

Chopper-stabilized gas chromatography-electroantennography: Part I. background, signal processing and example

A new method that can improve gas-chromatography-electroantennographic detection (GC-EAD) by orders of magnitude through a technique known as chopper stabilization combined with matched filtering in colored noise is presented. The EAD is a physiological recording from the antenna of an insect which can be used to find compounds in the GC effluent that the antenna is able to detect, having important applications for pest control and understanding of chemical communication in nature. The new method is demonstrated with whole-animal male Helicoverpa zea antennal preparations for detection of major pheromone component (cis-11-hexadecenal) and compared to results obtained using traditional EAD recording techniques. Results indicate that chopper stabilization under these circumstances can increase odorant detection performance by a factor of approximately 10(4) over traditional methods. The time course of the response of the antenna is also better resolved under chopped conditions. Although the degree of improvement is expected to vary with insect species, odor, and insect preparation, under most circumstances a more sensitive and robust GC-EAD instrument will result from the application of this technique.

Olfactory modulation of flight in Drosophila is sensitive, selective and rapid

Freely flying Drosophila melanogaster respond to odors by increasing their flight speed and turning upwind. Both these flight behaviors can be recapitulated in a tethered fly, which permits the odor stimulus to be precisely controlled. In this study, we investigated the relationship between these behaviors and odor-evoked activity in primary sensory neurons. First, we verified that these behaviors are abolished by mutations that silence olfactory receptor neurons (ORNs). We also found that antennal mechanosensors in Johnston's organ are required to guide upwind turns. Flight responses to an odor depend on the identity of the ORNs that are active, meaning that these behaviors involve odor discrimination and not just odor detection. Flight modulation can begin rapidly (within about 85 ms) after the onset of olfactory transduction. Moreover, just a handful of spikes in a single ORN type is sufficient to trigger these behaviors. Finally, we found that the upwind turn is triggered independently from the increase in wingbeat frequency, implying that ORN signals diverge to activate two independent and parallel motor commands. Together, our results show that odor-evoked flight modulations are rapid and sensitive responses to specific patterns of sensory neuron activity. This makes these behaviors a useful paradigm for studying the relationship between sensory neuron activity and behavioral decision-making in a simple and genetically tractable organism.

Statistical approach in search for optimal signal in simple olfactory neuronal models

Several models (concentration detectors and a flux detector) for coding of odor intensity in olfactory sensory neurons are investigated. Behavior of the system is described by different stochastic processes of binding the odorant molecules to the receptors and their activation. Characteristics how well the odorant concentration can be estimated from the knowledge of response, the number of activated neurons, are studied. The approach is based on the Fisher information and analogous measures. These measures of optimality are computed and applied to locate the odorant concentration which is most suitable for coding. The results are compared with the classical deterministic approach which judges the optimal odorant concentration via steepness of the input-output function.

Computational model of the cAMP-mediated sensory response and calcium-dependent adaptation in vertebrate olfactory receptor neurons

We develop a mechanistic mathematical model of the G-protein coupled signaling pathway responsible for generating current responses in frog olfactory receptor neurons. The model incorporates descriptions of ligand-receptor interaction, intracellular transduction events involving the second messenger cAMP, effector ion-channel activity, and calcium-mediated feedback steps. We parameterized the model with respect to suction pipette current recordings from single cells stimulated with multiple odor concentrations. The proposed model accurately predicts the receptor-current response of the neuron to brief and prolonged odorant exposure and is able to produce the adaptation observed under repeated or sustained stimulation.

Dynamic modeling of biochemical reactions with application to signal transduction: principles and tools using Mathematica

Modeling of biochemical phenomena is based on formal reaction kinetics. This requires the translation of the original reaction systems into sets of differential equations expressing the effects of the various reaction steps. The temporal behavior of the system is obtained by solving the differential equations. We present the main concepts on which the formal approach of these two problems is based and we show how the amount of work needed to treat them can be significantly reduced by using a mathematical program package (Mathematica). Symbolic and numerical calculations can be performed with the programs presented and graphic presentations of the behavior of the system be obtained. The basic ideas are illustrated with three examples taken from the area of signal transduction and ion signaling.

Stochastic pulse stimulation in chemoreceptors and its properties

Orientation towards food and mate, especially in insects, is an olfactory-controlled behavior which relies on the detection of small amounts of odorant molecules delivered in turbulent atmospheric conditions, so that randomness in magnitude and time is a major feature of the natural stimulus. The effect of random delivery on the initial step of olfactory transduction, the formation of the receptor-ligand complex, is analyzed in the case of the moth pheromonal system. Two types of randomness are compared, Gaussian (regular) and exponential (irregular). The influence of noise is quantified either with the maxima of the receptor-ligand complex, or with the times at which the concentration of complex crosses a given threshold level. It is shown that the stochastic features of the stimulus helps its detection and that the exponential distribution appears not only as a better description of the natural stimulus, but also as the most efficient from a biological point of view.

Relation between stimulus and response in frog olfactory receptor neurons in vivo

The spiking activity of receptor neurons was recorded extracellularly in the frog olfactory epithelium in response to four odourants applied at precisely controlled concentrations. A set of criteria was formulated to define the spikes in the response. Four variables - latency, duration, number of interspike intervals and frequency - were determined to quantify the responses. They were studied at the single neuron, neuron population and ciliary membrane levels. The dose-response curves were determined using specific functions and their characteristics were evaluated. The characteristic molar concentrations at threshold or at maximum duration and the characteristics of variables, e.g. minimum latency or maximum frequency, have asymmetric histograms with peaks close to the origin and long tails. Dynamic ranges have even more asymmetric histograms, so that a significant fraction of neurons presents a much wider range than their one-decade peak. From these histograms, response properties of the whole neuron population can be inferred. In general, location along the concentration axis (thresholds), width (dynamic ranges) and heights of dose-response curves are independent, which explains the diversity of curves, prevents their global categorization and supports the qualitative coding of odourants. No evidence for odourant-independent types of neurons was found. Finally, receptor activation and ciliary membrane conductance were reconstructed in the framework of a model based on firing data, known mucus biochemical and neuron morpho-electrical characteristics. It is in agreement with independent determinations of Kd of odourant-receptor interaction and of conductance characteristics, and describes their statistical distributions in the neuron population.

Coding of periodic pulse stimulation in chemoreceptors

In natural conditions odorants released continuously by animals and plants are broken in discontinuous clumps and filaments. In the case of flying insects these discontinuities are perceived as periodic variations in the concentration of the stimulus. This periodicity has been shown to be essential to orientation and location of mate and food. We study analytically and numerically a model of the receptor-ligand interaction that takes place in the receptor neurons. We show that this model can account quantitatively for the range of optimum stimulus frequencies measured experimentally in the sex-pheromone system of moths. The results obtained suggest that the rate constants characterising the pheromone-receptor interaction are optimally adapted to the temporal characteristics of the signal it perceives.

Stomatopod antennule design: the asymmetry, sampling efficiency and ontogeny of olfactory flicking

Many crustaceans detect odors from distant sources using chemosensory sensilla (aesthetascs) on their antennules. The greater the flow of water through arrays of aesthetascs, the faster the access of odorant to receptors inside the aesthetascs. Stomatopods facilitate odorant access by flicking their antennules, thus increasing the relative velocity of the water reaching their aesthetascs. We used dynamically scaled physical models to investigate how aesthetasc size and spacing and antennule flicking velocity affect flow penetration into the simple aesthetasc arrays of the stomatopod Gonodactylaceus mutatus. Particle image velocimetry of flow fields near models of juvenile and adult antennules revealed that velocity gradients around the aesthetascs are steeper during the outward part of the flick than during the return stroke and that the velocity gradients are steeper at the aesthetasc tips than at their bases. More fluid per unit time flows between aesthetasc rows during the outward stroke than during the return stroke, ensuring that odor sampling is pulsatile. During flicking, velocity gradients are steeper near adult aesthetascs than near juvenile aesthetascs, and adults process more fluid per unit time than juveniles. The resulting differences in odorant access can be related to size- and age-dependent changes in stomatopod ecology.

Effect of spatial extension on noise-enhanced phase locking in a leaky integrate-and-fire model of a neuron

Signal transmission enhanced by noise has been recently investigated in detail on the single compartment, also referred to as single point, leaky integrate-and-fire model neuron under a subthreshold stimulation. In this paper we study how this phenomenon is influenced by taking into account the spatial characteristics of the neuron. A stochastic two-point leaky integrate-and-fire model, comprising a dendritic compartment and trigger zone, under periodic stimulation is studied. A method of how to measure synchronization between the signal and the output in both, experiments and models, is proposed. This method is based on a distance between the exact periodic spiking, as expected for sufficiently strong and noiseless stimulation, and neuronal activity evoked by a subthreshold signal corrupted by noise. It is shown that qualitatively the same phenomenon, phase-locking enhanced by the noise, as found in the spatially unstructured neuron is produced by the spatially complex neuron. However, quantitatively there are significant differences. Namely, the two-point model neuron is more robust against the noise and therefore its amplitude has to be higher to enhance the signal. Further, it is found that the range of the critical levels of noise is larger for the two-point model than for the single-point one. Finally, the enhancing effect at the optimal noise is more efficient in the single-point model and thus the firing patterns at their optimal noise levels are different in both models.

Spiking frequency versus odorant concentration in olfactory receptor neurons

The spiking response of receptor neurons to various odorants has been analyzed at different concentrations. The interspike intervals were measured extracellularly before, during and after the stimulation from the olfactory epithelium of the frog Rana ridibunda. First, a quantitative method was developed to distinguish the spikes in the response from the spontaneous activity. Then, the response intensity, characterized by its median instantaneous frequency, was determined. Finally, based on statistical analyses, this characteristic was related to the concentration and quality of the odorant stimulus. It was found that the olfactory neuron is characterized by a low modulation in frequency and a short range of discriminated intensities. The significance of the results is discussed from both a biological and a modelling point of view.