Caractérisation temporelle d'un canal télécom atmospherique horizontal urbain

International audienceFree Space Optics (FSO) are breakable under some climatic conditions. However characterization of the propagation channel by studying wavelength transmisttance and data coming from a wavefront experiment could improve FSO's performance.Les communications optiques sans fils sont fragiles sous certaines conditions climatiques. Cependant caractériser le canal de propagation en étudiant la transmission des longueurs d'ondes et de données provenant d'une expérience de front d'onde pourra améliorer les performances des communications optiques sans fils

A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP

Humans perform remarkably well in many cognitive tasks including pattern recognition. However, the neuronal mechanisms underlying this process are not well understood. Nevertheless, artificial neural networks, inspired in brain circuits, have been designed and used to tackle spatio-temporal pattern recognition tasks. In this paper we present a multineuronal spike pattern detection structure able to autonomously implement online learning and recognition of parallel spike sequences (i.e., sequences of pulses belonging to different neurons/neural ensembles). The operating principle of this structure is based on two spiking/synaptic neurocomputational characteristics: spike latency, that enables neurons to fire spikes with a certain delay and heterosynaptic plasticity, that allows the own regulation of synaptic weights. From the perspective of the information representation, the structure allows mapping a spatio-temporal stimulus into a multidimensional, temporal, feature space. In this space, the parameter coordinate and the time at which a neuron fires represent one specific feature. In this sense, each feature can be considered to span a single temporal axis. We applied our proposed scheme to experimental data obtained from a motor inhibitory cognitive task. The test exhibits good classification performance, indicating the adequateness of our approach. In addition to its effectiveness, its simplicity and low computational cost suggest a large scale implementation for real time recognition applications in several areas, such as brain computer interface, personal biometrics authentication or early detection of diseases.Comment: Submitted to Frontiers in Neuroscienc

Cross layer optimisation for adaptive-optics corrected satellite to Ground laser links

For future satellite-to-ground communications link, very high throughput might be achievable at a reasonable cost assuming the use of existing single mode components developed for fiber technologies (optical detectors and amplifiers, MUX/DEMUX...). The influence of atmospheric turbulence degrades the injection efficiency of the incoming wave into single mode components. This leads to signal fading and channel impairments. Several mitigation strategies are considered to prevent them. The use of adaptive optics (AO) should contribute to reduce substantially the criticality of the fading at the expense of potentially complex and expensive systems if very high stability of the injection is requested. The use of appropriate numerical mitigation techniques (coding+interleaving) can help to relax the specifications and cost of AO systems but could lead among others to unmanageable buffer size. Thus the specification of AO correction and interleavers/forward error codes should be addressed jointly. A model to evaluate the channel capacity in terms of outage probability and packet error rate has been developed that jointly takes into account partial correction by AO and channel interleaving. It includes the capability to evaluate coded transmission performance over the correlated FSO channel in satellite-to-ground scenarios. This model is presented here and confronted to numerical simulations for several distinct correction cases. The interdependence of AO correction with numerical mitigation techniques is investigated

Performance evaluation of coded transmission for adaptive-optics corrected satellite-to-ground laser links

Performance estimation of coded LEO satellite-to ground laser transmissions partially corrected by adaptive-optics are presented. Through numerical simulations, the conjugation of adaptive-optics with a cross-layering optimization of data reliability mechanisms is investigated. The emphasis is put on the minimization of the data memories required at both the transmitter and the receiver in order to guarantee an error-free downlink

Resting-State Beta-Band Recovery Network Related to Cognitive Improvement After Stroke

Stroke is the second leading cause of death worldwide and it causes important long-term cognitive and physical deficits that hamper patients' daily activity. Neuropsychological rehabilitation (NR) has increasingly become more important to recover from cognitive disability and to improve the functionality and quality of life of these patients. Since in most stroke cases, restoration of functional connectivity (FC) precedes or accompanies cognitive and behavioral recovery, understanding the electrophysiological signatures underlying stroke recovery mechanisms is a crucial scientific and clinical goal. For this purpose, a longitudinal study was carried out with a sample of 10 stroke patients, who underwent two neuropsychological assessments and two resting-state magnetoencephalographic (MEG) recordings, before and after undergoing a NR program. Moreover, to understand the degree of cognitive and neurophysiological impairment after stroke and the mechanisms of recovery after cognitive rehabilitation, stroke patients were compared to 10 healthy controls matched for age, sex, and educational level. After intra and inter group comparisons, we found the following results: (1) Within the stroke group who received cognitive rehabilitation, almost all cognitive domains improved relatively or totally; (2) They exhibit a pattern of widespread increased in FC within the beta band that was related to the recovery process (there were no significant differences between patients who underwent rehabilitation and controls); (3) These FC recovery changes were related with the enhanced of cognitive performance. Furthermore, we explored the capacity of the neuropsychological scores before rehabilitation, to predict the FC changes in the brain network. Significant correlations were found in global indexes from the WAIS-III: Performance IQ (PIQ) and Perceptual Organization index (POI) (i.e., Picture Completion, Matrix Reasoning, and Block Design)

A Neuro-Inspired System for Online Learning and Recognition of Parallel Spike Trains, Based on Spike Latency, and Heterosynaptic STDP

Humans perform remarkably well in many cognitive tasks including pattern recognition. However, the neuronal mechanisms underlying this process are not well understood. Nevertheless, artificial neural networks, inspired in brain circuits, have been designed and used to tackle spatio-temporal pattern recognition tasks. In this paper we present a multi-neuronal spike pattern detection structure able to autonomously implement online learning and recognition of parallel spike sequences (i.e., sequences of pulses belonging to different neurons/neural ensembles). The operating principle of this structure is based on two spiking/synaptic neurocomputational characteristics: spike latency, which enables neurons to fire spikes with a certain delay and heterosynaptic plasticity, which allows the own regulation of synaptic weights. From the perspective of the information representation, the structure allows mapping a spatio-temporal stimulus into a multi-dimensional, temporal, feature space. In this space, the parameter coordinate and the time at which a neuron fires represent one specific feature. In this sense, each feature can be considered to span a single temporal axis. We applied our proposed scheme to experimental data obtained from a motor-inhibitory cognitive task. The results show that out method exhibits similar performance compared with other classification methods, indicating the effectiveness of our approach. In addition, its simplicity and low computational cost suggest a large scale implementation for real time recognition applications in several areas, such as brain computer interface, personal biometrics authentication, or early detection of diseases

Statistical properties of single-mode fiber coupling of satellite-to-ground laser links partially corrected by adaptive optics

In the framework of satellite-to-ground laser downlinks, an analytical model describing the variations of the instantaneous coupled flux into a single-mode fiber after correction of the incoming wavefront by partial adaptive optics (AO) is presented. Expressions for the probability density function and the cumulative distribution function as well as for the average fading duration and fading duration distribution of the corrected coupled flux are given. These results are of prime interest for the computation of metrics related to coded transmissions over correlated channels, and they are confronted by end-to-end wave-optics simulations in the case of a geosynchronous satellite (GEO)-to-ground and a low earth orbit satellite (LEO)-to-ground scenario. Eventually, the impact of different AO performances on the aforementioned fading duration distribution is analytically investigated for both scenarios

Noninvasive prediction of shunt operation outcome in idiopathic normal pressure hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is a syndrome characterized by gait disturbance, cognitive deterioration and urinary incontinence in elderly individuals. These symptoms can be improved by shunt operation in some but not all patients. Therefore, discovering predictive factors for the surgical outcome is of great clinical importance. We used normalized power variance (NPV) of electroencephalography (EEG) waves, a sensitive measure of the instability of cortical electrical activity, and found significantly higher NPV in beta frequency band at the right fronto-temporo-occipital electrodes (Fp2, T4 and O2) in shunt responders compared to non-responders. By utilizing these differences, we were able to correctly identify responders and non-responders to shunt operation with a positive predictive value of 80% and a negative predictive value of 88%. Our findings indicate that NPV can be useful in noninvasively predicting the clinical outcome of shunt operation in patients with iNPH

Scopolamine effects on functional brain connectivity : a pharmacological model of Alzheimer's disease

Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.Peer reviewe