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

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

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

Excitable Scale Free Networks

When a simple excitable system is continuously stimulated by a Poissonian external source, the response function (mean activity versus stimulus rate) generally shows a linear saturating shape. This is experimentally verified in some classes of sensory neurons, which accordingly present a small dynamic range (defined as the interval of stimulus intensity which can be appropriately coded by the mean activity of the excitable element), usually about one or two decades only. The brain, on the other hand, can handle a significantly broader range of stimulus intensity, and a collective phenomenon involving the interaction among excitable neurons has been suggested to account for the enhancement of the dynamic range. Since the role of the pattern of such interactions is still unclear, here we investigate the performance of a scale-free (SF) network topology in this dynamic range problem. Specifically, we study the transfer function of disordered SF networks of excitable Greenberg-Hastings cellular automata. We observe that the dynamic range is maximum when the coupling among the elements is critical, corroborating a general reasoning recently proposed. Although the maximum dynamic range yielded by general SF networks is slightly worse than that of random networks, for special SF networks which lack loops the enhancement of the dynamic range can be dramatic, reaching nearly five decades. In order to understand the role of loops on the transfer function we propose a simple model in which the density of loops in the network can be gradually increased, and show that this is accompanied by a gradual decrease of dynamic range.Comment: 6 pages, 4 figure

Imaging of Early-Stage Cracking on Real-Size Concrete Structure from 4-Points Bending Test

International audienceTraditional ultrasonic imaging techniques encounter difficulty on complexes material such as concrete, which is in part due the use of coherent waves in a very heterogeneous material. From this angle, technique called LOCADIFF has been developed for monitoring heterogeneous media using multiply scattered waves [1, 2]. We consider that modifications in the medium are equivalent to the presence of extra scatterers, which are characterized by their effective scattering cross-section &#963,. Within this view, LOCADIFF allows to locate the modification by measuring the spatio-temporal de-correlation of multiply scattered waves and by solving the corresponding inverse problem. Based on LOCADIFF, a newly developed imaging technique has been reported [3]. By mapping the intensity of modification on localized microstructure, the new technique is able to detect perturbations at multiple locations. Here we present the application of this new technique on a real-size 15 tons concrete structure for imaging early-stage cracking procedure issued from four point bending load, as part of the CEOS.fr project. Experimental results show that this technique can not only locate cracks that appeared simultaneously at multiple locations, but also detect them and observe their developments since an early-stage

Mise à disposition d'un espace Gitlab et Jupyter pour les apprenants du Mooc "Recherche Reproductible"

Ces développements ont été implémentés dans le cadre du Mooc “Recherche reproductible : principes méthodologiques pour une science transparente” : https://www.fun-mooc.fr/courses/course-v1:inria+41016+session01bis/aboutCe rapport a pour objectif de décrire l'architecture et le déploiement d'un environement de travail pour éditer et historiser des notebooks dans le cadre du Mooc "Recherche reproductible : principes méthodologiques pour une science transparente". Nous aborderons le sujet avec une vue assez haut-niveau pour avoir un aperçu des contraintes techniques et comment les différents services ont été mis en place. Le principal enjeu étant d'utiliser le protocole LTI pour permettre une authentification unique pour l'apprenant à partir de son compte FUN. Nous décrirons comment nous avons su adapter des solutions open-sources tel que Jupyterhub et Gitlab pour répondre à ces besoins et à ces contraintes

Intensity Coding in Two-Dimensional Excitable Neural Networks

In the light of recent experimental findings that gap junctions are essential for low level intensity detection in the sensory periphery, the Greenberg-Hastings cellular automaton is employed to model the response of a two-dimensional sensory network to external stimuli. We show that excitable elements (sensory neurons) that have a small dynamical range are shown to give rise to a collective large dynamical range. Therefore the network transfer (gain) function (which is Hill or Stevens law-like) is an emergent property generated from a pool of small dynamical range cells, providing a basis for a "neural psychophysics". The growth of the dynamical range with the system size is approximately logarithmic, suggesting a functional role for electrical coupling. For a fixed number of neurons, the dynamical range displays a maximum as a function of the refractory period, which suggests experimental tests for the model. A biological application to ephaptic interactions in olfactory nerve fascicles is proposed.Comment: 17 pages, 5 figure

Function and central projections of gustatory receptor neurons on the antenna of the noctuid moth Spodoptera littoralis

Chemosensory information is crucial for most insects to feed and reproduce. Olfactory signals are mainly used at a distance, whereas gustatory stimuli play an important role when insects directly contact chemical substrates. In noctuid moths, although the antennae are the main olfactory organ, they also bear taste sensilla. These taste sensilla detect sugars and hence are involved in appetitive learning but could also play an important role in food evaluation by detecting salts and bitter substances. To investigate this, we measured the responses of individual taste sensilla on the antennae of Spodoptera littoralis to sugars and salts using tip recordings. We also traced the projections of their neuronal axons into the brain. In each sensillum, we found one or two neurons responding to sugars: one NaCl-responsive and one water-sensitive neuron. Responses of these neurons were dose-dependent and similar across different locations on the antenna. Responses were dependent on the sex for sucrose and on both sex and location for glucose and fructose. We did not observe a spatial map for the projections from specific regions of the antennae to the deutocerebrum or the tritocerebrum/suboesophageal ganglion complex. In accordance with physiological recordings, back-fills from individual sensilla revealed up to four axons, in most cases targeting different projection zones