Conditionnement opérant de neurones du cortex moteur du rat pour un contrôle gradué de prothèse

Spinal cord injuries, along with myopathies, strokes or amputations can lead to very severe conditions where motor commands cannot be executed as intended. To cope with these deficits, brain-machine interfaces have been developed. Most research groups working in this field have conceived interfaces that try to reconstruct a movement from neuronal activity in the brain. Here, we tackle the problem differently by conditioning one or a few neurons in the motor cortex of awake rats to control the speed of a one dimensional actuator by increasing or decreasing their firing rate. In this protocol, knowing the initial coding space of the conditioned neurons was not a prerequisite. We observed that most neurons' activity could be modulated through operant conditioning, and could control the position of a bottle with water reward in front of the animal in real-time and for several seconds. Moreover, during the learning period, the conditioned neurons exhibited special properties compared to other non-conditioned neurons, in terms of their firing rate variability, latency of response and strength of rate modulation. This is the first demonstration of an external device controlled in real-time by conditioned neurons that adjust their activity to constantly changing demands.Les traumatismes médullaires, ainsi que les myopathies, les accidents vasculaires cérébraux ou les amputations peuvent entraîner de très lourds handicaps où la commande motrice ne peut plus être exécutée correctement. Les interfaces cerveau-machine ont été développées pour contrecarrer ces déficits. La plupart des groupes de recherche travaillant dans le domaine ont conçu des interfaces qui tentent de reconstruire un mouvement à partir de l'activité neuronale du cerveau. Dans notre cas, nous attaquons le problème différemment en conditionnant un neurone ou un petit nombre d'entre eux dans le cortex moteur de rats éveillés afin qu'ils contrôlent la vitesse d'un actuateur en une dimension en augmentant ou en diminuant leur taux de décharge. Dans ce protocole, connaître l'espace initial de codage des neurones conditionnés n'était pas un prérequis. Nous avons observé que l'activité de la plupart des neurones pouvait être modulée par conditionnement opérant, et pouvaient contrôler en temps réel et pendant plusieurs secondes la position d'une bouteille contenant une récompense liquide située en face de l'animal. De plus, pendant la période d'apprentissage, les neurones conditionnés ont affiché des propriétés spéciales comparées aux autres neurones non conditionnés, en termes de variabilité du taux de décharge, de latence de la réponse et de force de la modulation. Cela constitue la première démonstration d'un outil externe contrôlé en temps réel par des neurones conditionnés devant ajuster leur activité selon des objectifs constamment redéfinis

Prévision du trafic des voyageurs sur lignes ferroviaires à grande vitesse : expériences avec deux modèles d'analyses sur la relation Barcelone-frontière française

This paper describes the current situation of the transport flows by modes in the international relations between Spain and the rest of Europe. It explains the geographic zoning adopted for accurately establishing origin/destination flows. Details the different models used for traffic forecasting, including everything necessary for evaluating the induced traffic on all new high speed lines in accordance with French experience. Finally the paper will provide the results obtained for the total traffic and for each origin/destination.Cette communication a pour but d'exposer la situation actuelle des flux de trafic par modes de transport sur les relations internationales par la frontière méditerranéenne. Elle explicite les différents modèles employés pour prévoir le trafic y compris celui adopté pour quantifier le trafic induit, en se basant sur l'expérience française en ce domaine. Le rapport indique les résultats obtenus, pour les principales origine/destination. Les résultats sont comparés à ceux qui ressortent de l'application du modèle développé par la NEA. On remarque le très bon accord entre les résultats de l'une et l'autre méthodologie

Bidirectional control of a one-dimensional robotic actuator by operant conditioning of a single unit in rat motor cortex

International audienceThe design of efficient neuroprosthetic devices has become a major challenge for the long-term goal of restoring autonomy to motor-impaired patients. One approach for brain control of actuators consists in decoding the activity pattern obtained by simultaneously recording large neuronal ensembles in order to predict in real-time the subject's intention, and move the prosthesis accordingly. An alternative way is to assign the output of one or a few neurons by operant conditioning to control the prosthesis with rules defined by the experimenter, and rely on the functional adaptation of these neurons during learning to reach the desired behavioral outcome. Here, several motor cortex neurons were recorded simultaneously in head-fixed awake rats and were conditioned, one at a time, to modulate their firing rate up and down in order to control the speed and direction of a one-dimensional actuator carrying a water bottle. The goal was to maintain the bottle in front of the rat's mouth, allowing it to drink. After learning, all conditioned neurons modulated their firing rate, effectively controlling the bottle position so that the drinking time was increased relative to chance. The mean firing rate averaged over all bottle trajectories depended non-linearly on position, so that the mouth position operated as an attractor. Some modifications of mean firing rate were observed in the surrounding neurons, but to a lesser extent. Notably, the conditioned neuron reacted faster and led to a better control than surrounding neurons, as calculated by using the activity of those neurons to generate simulated bottle trajectories. Our study demonstrates the feasibility, even in the rodent, of using a motor cortex neuron to control a prosthesis in real-time bidirectionally. The learning process includes modifications of the activity of neighboring cortical neurons, while the conditioned neuron selectively leads the activity patterns associated with the prosthesis control

Data from: Characterizing and comparing the seasonality of influenza-like illnesses and invasive pneumococcal diseases using seasonal waveforms

The seasonalities of influenza-like illnesses (ILIs) and invasive pneumococcal diseases (IPDs) remain incompletely understood. Experimental evidence indicates that influenza-virus infection predisposes to pneumococcal disease, so that a correspondence in the seasonal patterns of ILIs and IPDs might exist at the population level. We developed a method to characterize seasonality by means of easily interpretable summary statistics of seasonal shape—or seasonal waveforms. Non-linear mixed-effects models were used to estimate those waveforms based on weekly case reports of ILIs and IPDs in five regions spanning continental France from July 2000 to June 2014. We found high variability of ILI seasonality, with marked fluctuations of peak amplitudes and peak times, but a more conserved epidemic duration. In contrast, IPD seasonality was best modeled by a markedly regular seasonal baseline, punctuated by two winter peaks in late December–early January and January–February. Comparing ILI and IPD seasonal waveforms, we found indication of a small, positive correlation. Direct models regressing IPDs on ILIs provided comparable results, even though they estimated moderately larger associations. The method proposed is broadly applicable to diseases with unambiguous seasonality and is well-suited to analyze spatially or temporally grouped data, which are common in epidemiology

Data and R codes associated with "Characterizing and Comparing the Seasonality of Influenza-Like Illnesses and Invasive Pneumococcal Diseases Using Seasonal Waveforms"

The zipped folder contains the data and the R scripts needed to perform the estimation of the influenza-like illness (ILI) seasonal waveforms, based on region-level weekly incidence data in France during 2000/01–2013/14