Cerebral asymmetries in sleep-dependent processes of memory consolidation

peer reviewedPreference for previously seen, unfamiliar objects reflects a memory bias on affective judgment, known as the "mere exposure effect" (MEE). Here, we investigated the effect of time, post-exposure sleep, and the brain hemisphere solicited on preference generalization toward objects viewed in different perspectives. When presented in the right visual field (RVF), which promotes preferential processing in the left hemisphere, same and mirrored exemplars were preferred immediately after exposure. MEE generalized to much dissimilar views after three nights of sleep. Conversely, object presentation in the left visual field (LVF), promoting right hemisphere processing, elicited a MEE for same views immediately after exposure, then for mirror views after sleep. Most importantly, sleep deprivation during the first post-exposure night, although followed by two recovery nights, extinguished MEE for all views in the LVF but not in the RVF. Besides demonstrating that post-exposure time and sleep facilitate the generalization process by which we integrate various representations of an object, our results suggest that mostly in the right hemisphere, sleep may be mandatory to consolidate the memory bias underlying affective preference. These interhemispheric differences tentatively call for a reappraisal of the role of cerebral asymmetries in wake- and sleep-dependent processes of memory consolidation

Fast sequential source localization using the projected companion matrix approach

International audienceThe sequential forms of the spectral MUSIC algorithm, such as the Sequential MUSIC (S-MUSIC) and the Recursively Applied and Projected MUSIC (RAP-MUSIC) algorithms, use the previously estimated DOA (Direction Of Arrival) to form an intermediate array gain matrix and project both the array manifold and the signal subspace estimate into its orthogonal complement. By doing this, these methods avoid the delicate search of multiple maxima and yield a more accurate DOA estimation in difficult scenarios. However, these high-resolution algorithms adapted to a general array geometry suffer from a high computational cost. On the other hand, for linear equispaced sensor array, the root- MUSIC algorithm is a fast and accurate high-resolution scheme which also avoids the delicate search of multiple maxima but a sequential scheme based on the root-MUSIC algorithm does not exist. This paper fills this need. Thus, we present a new sequential high-resolution estimation method, called the Projected Companion Matrix MUSIC (PCM-MUSIC) method, in the context of source localisation in the case of linear equispaced sensor array. Remark that the proposed algorithm can be used without modification in the context of spectral analysis

Pulsed high magnetic field measurement via a Rubidium vapor sensor

We present a new technique to measure pulsed magnetic fields based on the use of Rubidium in gas phase as a metrological standard. We have therefore developed an instrument based on laser inducing transitions at about 780~nm (D2 line) in a Rubidium gas contained in a mini-cell of 3~mm~x~3~mm cross section. To be able to insert such a cell in a standard high field pulsed magnet we have realized a fibred probe kept at a fixed temperature. Transition frequencies for both the $\pi$ (light polarization parallel to the magnetic field) and $\sigma$ (light polarization perpendicular to the magnetic field) configurations are measured by a commercial wavemeter. One innovation of our sensor is that in addition of monitoring the light transmitted by the Rb cell, which is usual, we also monitor the fluorescence emission of the gas sample from a very small volume with the advantage of reducing the impact of the field inhomogeneity on the field measurement. Our sensor has been tested up to about 58~T.Comment: Submitted to Review Scientific Instrument

Analyse des performances de reseaux de capteurs 2D et 3D pour la localisation de source

National audienceDans le contexte de la localisation passive de sources par un réseau de capteurs, les performances d'estimation concernant les angles d'arrivée des sources (azimut et élévation) sont liées au type d'estimateur mis en oeuvre, mais aussi à la géometrie du réseau considéré. Bien que de nombreux résultats soient disponibles concernant les antennes linéaires ainsi que les antennes circulaires, d'autres géométries existent dans la littérature et ont été moins étudiées. Dans cet article, nous étudions l'impact en termes de performance d'estimation pour l'azimut et l'élévation d'une source déterministe pour deux configurations de réseaux. Il s'agit d'une antenne planaire (2D) dite ”en V” et de son homologue en trois dimensions. L'outil utilisé ici est la borne de Cramér-Rao largement utilisée par la communauté du traitement du signal pour caractériser les performances d'estimation du fait qu'elle peut être atteinte (sous certaines conditions) par des estimateurs de type maximum de vraisemblance

Weiss-Weinstein Bound and SNR Threshold Analysis for DOA Estimation with a COLD Array

International audienceIn the context of polarized sources localization using a cocentered orthogonal loop and dipole array, direction-of-arrival estimation performance in terms of mean square error are investigated. In order to evaluate these performance for both asymptotic and non-asymptotic scenarios (low number of snapshot and/or low signal to noise ratio) we derive closed-form expressions of the Weiss-Weinstein bound. The analysis is performed under both conditional and unconditional source signal models. We show the good ability of the proposed bound to predict the well known threshold effect. We also show the influence of the polarization parameters

GLRT-Based Framework for the Multidimensional Statistical Resolution Limit

International audienceRecently, a criterion for Multidimensional Statistical Resolution Limit (MSRL) evaluation, which is defined as the minimal separation to resolve two closely spaced signals depending on several parameters, was empirically proposed in [1] but without a statistical analysis. In this paper, we fill this lack by demonstrating that this MSRL criterion is asymptotically equivalent (upon to a translator factor) to a UMP (Uniformly Most Powerful) test among all invariant statistical tests. This result is an extension of a previous work on mono-dimensional SRL (i.e., when the signals only depend on one parameter). As an illustrative example, the 3-D harmonic retrieval case for wireless channel sounding is treated to show the good agreement of the proposed result

NONMATRIX CLOSED-FORM EXPRESSIONS OF THE CRAMER-RAO BOUNDS FOR NEAR-FIELD LOCALIZATION PARAMETERS

International audienceNear-field source localization problem by a passive antenna array makes the assumption that the time-varying sources are located near the antenna. In this situation, the far-field assumption (planar wavefront) is no longer valid and we have to consider a more complicated model parameterized by the bearing (as in the far-field case) and by the distance, named range, between the source and a reference sensor. We can find a plethora of estimation schemes in the literature but the ultimate performance has not been fully investigated. In this paper, we derive and analyze the Cram´er-Rao Bound (CRB) for a single time-varying source. In this case, we obtain nonmatrix closed-form expressions. Our approach has two advantages: (i) the computational cost for a large number of snapshots of a matrix-based CRB can be high while our approach is cheap and (ii) some useful informations can be deduced from the behavior of the bound. In particular, we show that closer is the source from the array and/or higher is the carrier frequency, better is the estimation of the range

Statistical Resolution Limit for the Multidimensional Harmonic Retrieval Model: Hypothesis Test and Cramer-Rao Bound Approaches

Special issue on Advances in Angle-of-Arrival and Multidimensional Signal Processing for Localization and CommunicationsInternational audienceThe Statistical Resolution Limit (SRL), which is defined as the minimal separation between parameters to allow a correct resolvability, is an important statistical tool to quantify the ultimate performance for parametric estimation problems. In this paper we generalize the concept of the SRL to the Multidimensional SRL (MSRL) applied to the multidimensional harmonic retrieval model. In this paper, we derive the SRL for the so-called multidimensional harmonic retrieval model by using a generalization of the previously introduced SRL concepts that we call Multidimensional SRL (MSRL). We first derive the MSRL using an hypothesis test approach. This statistical test is shown to be asymptotically an uniformly most powerful test which is the strongest optimality statement that one could expect to obtain. Second, we link the proposed asymptotic MSRL based on the hypothesis test approach to a new extension of the SRL based on the Cramér-Rao Bound approach. Thus, a closed-form expression of the asymptotic MSRL is given and analyzed in the framework of the multidimensional harmonic retrieval model. Particularly, it is proved that the optimal MSRL is obtained for equi-powered sources and/or an equi-distributed number of sensors on each multi-way array