Dynamical Modeling of the Moth Pheromone-Sensitive Olfactory Receptor Neuron within Its Sensillar Environment

In insects, olfactory receptor neurons (ORNs), surrounded with auxiliary cells and protected by a cuticular wall, form small discrete sensory organs – the sensilla. The moth pheromone-sensitive sensillum is a well studied example of hair-like sensillum that is favorable to both experimental and modeling investigations. The model presented takes into account both the molecular processes of ORNs, i.e. the biochemical reactions and ionic currents giving rise to the receptor potential, and the cellular organization and compartmentalization of the organ represented by an electrical circuit. The number of isopotential compartments needed to describe the long dendrite bearing pheromone receptors was determined. The transduction parameters that must be modified when the number of compartments is increased were identified. This model reproduces the amplitude and time course of the experimentally recorded receptor potential. A first complete version of the model was analyzed in response to pheromone pulses of various strengths. It provided a quantitative description of the spatial and temporal evolution of the pheromone-dependent conductances, currents and potentials along the outer dendrite and served to determine the contribution of the various steps in the cascade to its global sensitivity. A second simplified version of the model, utilizing a single depolarizing conductance and leak conductances for repolarizing the ORN, was derived from the first version. It served to analyze the effects on the sensory properties of varying the electrical parameters and the size of the main sensillum parts. The consequences of the results obtained on the still uncertain mechanisms of olfactory transduction in moth ORNs – involvement or not of G-proteins, role of chloride and potassium currents – are discussed as well as the optimality of the sensillum organization, the dependence of biochemical parameters on the neuron spatial extension and the respective contributions of the biochemical and electrical parameters to the overall neuron response

Maximum relative speeds of living organisms: why do bacteria perform as fast as ostriches?

International audienceSelf-locomotion is central to animal behaviour and survival. It is generally analysed by focusing on preferred speeds and gaits under particular biological and physical constraints. In the present paper we focus instead on the maximum speed and we study its order-of-magnitude scaling with body size, from bacteria to the largest terrestrial and aquatic organisms. Using data for about 460 species of various taxonomic groups, we find a maximum relative speed of the order of magnitude of ten body lengths per second over a 10 20-fold mass range of running and swimming animals. This result implies a locomotor time scale of the order of one tenth of second, virtually independent on body size, anatomy and locomotion style, whose ubiquity requires an explanation building on basic properties of motile organisms. From first-principle estimates, we relate this generic time scale to other basic biological properties, using in particular the recent generalisation of the muscle specific tension to molecular motors. Finally, we go a step further by relating this time scale to still more basic quantities, as environmental conditions at Earth in addition to fundamental physical and chemical constants

Force per cross-sectional area from molecules to muscles: a general property of biological motors

International audienceWe propose to formally extend the notion of specific tension, i.e. force per cross-sectional area—classically used for muscles, to quantify forces in molecular motors exerting various biological functions. In doing so, we review and compare the maximum tensions exerted by about 265 biological motors operated by about 150 species of different taxonomic groups. The motors considered range from single molecules and motile appendages of microorganisms to whole muscles of large animals. We show that specific tensions exerted by molecular and non-molecular motors follow similar statistical distributions, with in particular, similar medians and (logarithmic) means. Over the 10 19 mass (M) range of the cell or body from which the motors are extracted, their specific tensions vary as M α with α not significantly different from zero. The typical specific tension found in most motors is about 200 kPa, which generalizes to individual molecular motors and microorganisms a classical property of macroscopic muscles. We propose a basic order-of-magnitude interpretation of this result

Modelling the signal delivered by a population of first-order neurons in a moth olfactory system

A statistical model of the population of first-order olfactory receptor neurons (ORNs) is proposed and analysed. It describes the relationship between stimulus intensity (odour concentration) and coding variables such as rate and latency of the population of several thousand sex-pheromone sensitive ORNs in male moths. Although these neurons likely express the same olfactory receptor, they exhibit, at any concentration, a relatively large heterogeneity of responses in both peak firing frequency and latency of the first action potential fired after stimulus onset. The stochastic model is defined by a multivariate distribution of six model parameters that describe the dependence of the peak firing rate and the latency on the stimulus dose. These six parameters and their mutual linear correlations were estimated from experiments in single ORNs and included in the multidimensional model distribution. The model is utilized to reconstruct the peak firing rate and latency of the message sent to the brain by the whole ORN population at different stimulus intensities and to establish their main qualitative and quantitative properties. Finally, these properties are shown to be in agreement with those found previously in a vertebrate ORN population

Rôle de l'inhibition intra- et inter-glomérulaire dans la synchronisation neuronale et le codage phéromonal chez manduca sexta

ISBN : 978-2-9532965-0-1Une synchronisation neuronale est observée dès le premier étage de traitement du système olfactif, à savoir le lobe antennaire chez l'insecte. Dans le cas du papillon de nuit Manduca sexta, cette synchronisation est plus importante en présence du mélange phéromonal qu'en présence d'un composé simple. Dans cet article, nous proposons un modèle du complexe macroglomérulaire qui reproduit les données expérimentales et permet de mettre en lumière le rôle de l'inhibition intra- et inter-glomérulaire dans la synchronisation neuronale et le codage phéromonal

Machine learning for automatic prediction of the quality of electrophysiological recordings

The quality of electrophysiological recordings varies a lot due to technical and biological variability and neuroscientists inevitably have to select “good” recordings for further analyses. This procedure is time-consuming and prone to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert electrophysiologists. Generalisation performance is then assessed on unseen data, classified by the same or by another expert. We observe that the learning machine can be equally, if not more, consistent in its judgements as individual experts amongst each other. Best performance is achieved for a limited number of informative features; the optimal feature set being different from one data set to another. With 80–90% of correct judgements, the performance of the system is very promising within the data sets of each expert but judgments are less reliable when it is used across sets of recordings from different experts. We conclude that the proposed approach is relevant to the selection of electrophysiological recordings, provided parameters are adjusted to different types of experiments and to individual experimenters