[Dyspnea «sine materia¼]. / La dyspnée «sine materia¼.

Dyspnea is a symptom of respiratory discomfort commonly encountered in clinical practice which, in most of the cases, relates to a cardiopulmonary or a metabolic disorder. Its genesis is complex and results from numerous interactions within cortical and limbic brain areas following intero- and nociceptive stimuli. The term dyspnea «sine materia¼ points to a state where no clear underlying cardiopulmonary or metabolic pathology has been identified and we include here the hyperventilation syndrome and the physical deconditioning. Treatment of dyspnea «sine materia¼ is based on behavioural psychotherapy and on reathtletisation programme in case of physical deconditioning.

La dyspnée est un symptôme d'inconfort respiratoire extrêmement courant en médecine qui traduit, le plus souvent, un désordre cardiorespiratoire ou métabolique. Sa genèse est complexe et résulte de l'intégration, au niveau du cortex et du système limbique, de messages intéro- et nociceptifs. Par dyspnée «sine materia¼, nous entendons ici une dyspnée sans pathologie cardiorespiratoire ou métabolique sous-jacente avérée et nous y incluons celle du syndrome d'hyperventilation et du déconditionnement physique. La prise en charge de la dyspnée «sine materia¼ et, notamment, celle du syndrome d'hyperventilation repose sur la psychothérapie comportementale et la gestion du déconditionnement physique par des programmes de réathlétisation.

Surrogate spike train generation through dithering in operational time.

Detecting the excess of spike synchrony and testing its significance can not be done analytically for many types of spike trains and relies on adequate surrogate methods. The main challenge for these methods is to conserve certain features of the spike trains, the two most important being the firing rate and the inter-spike interval statistics. In this study we make use of operational time to introduce generalizations to spike dithering and propose two novel surrogate methods which conserve both features with high accuracy. Compared to earlier approaches, the methods show an improved robustness in detecting excess synchrony between spike trains.

Complexity distribution as a measure for assembly size and temporal precision.

The efficient detection of higher-order synchronization in massively parallel data is of great importance in understanding computational processes in the cortex and represents a significant statistical challenge. To overcome the combinatorial explosion of different spike patterns taking place as the number of neurons increases, a method based on population measures would prove very useful. Following previous work in this direction, we examine the distribution of spike counts across neurons per time bin ('complexity distribution') and devise a method to reliably extract the size and temporal precision of synchronous groups of neurons, even in the presence of strong rate covariations.

Efficient identification of assembly neurons within massively parallel spike trains.

The chance of detecting assembly activity is expected to increase if the spiking activities of large numbers of neurons are recorded simultaneously. Although such massively parallel recordings are now becoming available, methods able to analyze such data for spike correlation are still rare, as a combinatorial explosion often makes it infeasible to extend methods developed for smaller data sets. By evaluating pattern complexity distributions the existence of correlated groups can be detected, but their member neurons cannot be identified. In this contribution, we present approaches to actually identify the individual neurons involved in assemblies. Our results may complement other methods and also provide a way to reduce data sets to the "relevant" neurons, thus allowing us to carry out a refined analysis of the detailed correlation structure due to reduced computation time.

High-bandwidth hybrid quantum repeater.

We present a physical- and link-level design for the creation of entangled pairs to be used in quantum repeater applications where one can control the noise level of the initially distributed pairs. The system can tune dynamically, trading initial fidelity for success probability, from high fidelity pairs (F=0.98 or above) to moderate fidelity pairs. The same physical resources that create the long-distance entanglement are used to implement the local gates required for entanglement purification and swapping, creating a homogeneous repeater architecture. Optimizing the noise properties of the initially distributed pairs significantly improves the rate of generating long-distance Bell pairs. Finally, we discuss the performance trade-off between spatial and temporal resources.