Anatomo-functional correspondence in the superior temporal sulcus

The superior temporal sulcus (STS) is an intriguing region both for its complex anatomy and for the multiple functions that it hosts. Unfortunately, most studies explored either the functional organization or the anatomy of the STS only. Here, we link these two aspects by investigating anatomo-functional correspondences between the voice-sensitive cortex (Temporal Voice Areas) and the STS depth. To do so, anatomical and functional scans of 116 subjects were processed such as to generate individual surface maps on which both depth and functional voice activity can be analyzed. Individual depth profiles of manually drawn STS and functional profiles from a voice localizer (voice > non-voice) maps were extracted and compared to assess anatomo-functional correspondences. Three major results were obtained: first, the STS exhibits a highly significant rightward depth asymmetry in its middle part. Second, there is an anatomo-functional correspondence between the location of the voice-sensitive peak and the deepest point inside this asymmetrical region bilaterally. Finally, we showed that this correspondence was independent of the gender and, using a machine learning approach, that it existed at the individual level. These findings offer new perspectives for the understanding of anatomo-functional correspondences in this complex cortical region

Joint Bayesian endmember extraction and linear unmixing for hyperspectral imagery

This paper studies a fully Bayesian algorithm for endmember extraction and abundance estimation for hyperspectral imagery. Each pixel of the hyperspectral image is decomposed as a linear combination of pure endmember spectra following the linear mixing model. The estimation of the unknown endmember spectra is conducted in a unified manner by generating the posterior distribution of abundances and endmember parameters under a hierarchical Bayesian model. This model assumes conjugate prior distributions for these parameters, accounts for non-negativity and full-additivity constraints, and exploits the fact that the endmember proportions lie on a lower dimensional simplex. A Gibbs sampler is proposed to overcome the complexity of evaluating the resulting posterior distribution. This sampler generates samples distributed according to the posterior distribution and estimates the unknown parameters using these generated samples. The accuracy of the joint Bayesian estimator is illustrated by simulations conducted on synthetic and real AVIRIS images

Algorithmes bayésiens pour le démélange supervisé, semi-supervisé et non-supervisé d’images hyperspectrales

Cet article présente des algorithmes totalement bayésiens pour le démélange d’images hyperspectrales. Chaque pixel de l’image est décomposée selon une combinaison de spectres de références pondérés par des coefficients d’abondances selon un modèle de mélange linéaire. Dans un cadre supervisé, nous supposons connus les spectres de références. Le problème consiste alors à estimer les coefficients du mélange sous des contraintes de positivité et d’additivité. Une loi a priori adéquate est choisie pour ces coefficients qui sont estimés à partir de leur loi a posteriori. Un algorithme de Monte Carlo par chaîne de Markov (MCMC) est développé pour approcher les estimateurs. Dans un cadre semi-supervisé, les spectres participant au mélange seront supposés inconnus. Nous faisons l’hypothèse qu’ils appartiennent à une bibliothèque spectrale. Un algorithme MCMC à sauts réversibles permet dans ce cas de résoudre le problème de sélection de modèle. Enfin, dans un dernier cadre d’étude, les algorithmes précédents sont étendus au démélange non-supervisé d’images hyperspectrales, c’est-à-dire au problème d’estimation conjointe des spectres et des coefficients de mélange. Ce problème de séparation aveugle de sources est résolu dans un sous-espace approprié

Time series prediction via aggregation : an oracle bound including numerical cost

We address the problem of forecasting a time series meeting the Causal Bernoulli Shift model, using a parametric set of predictors. The aggregation technique provides a predictor with well established and quite satisfying theoretical properties expressed by an oracle inequality for the prediction risk. The numerical computation of the aggregated predictor usually relies on a Markov chain Monte Carlo method whose convergence should be evaluated. In particular, it is crucial to bound the number of simulations needed to achieve a numerical precision of the same order as the prediction risk. In this direction we present a fairly general result which can be seen as an oracle inequality including the numerical cost of the predictor computation. The numerical cost appears by letting the oracle inequality depend on the number of simulations required in the Monte Carlo approximation. Some numerical experiments are then carried out to support our findings

A unique coral biomineralization pattern has resisted 40 million years of major ocean chemistry change

Today coral reefs are threatened by changes to seawater conditions associated with rapid anthropogenic global climate change. Yet, since the Cenozoic, these organisms have experienced major fluctuations in atmospheric CO2 levels (from greenhouse conditions of high pCO2 in the Eocene to low pCO2 ice-house conditions in the Oligocene-Miocene) and a dramatically changing ocean Mg/Ca ratio. Here we show that the most diverse, widespread, and abundant reef-building coral genus Acropora (20 morphological groups and 150 living species) has not only survived these environmental changes, but has maintained its distinct skeletal biomineralization pattern for at least 40 My: Well-preserved fossil Acropora skeletons from the Eocene, Oligocene, and Miocene show ultra-structures indistinguishable from those of extant representatives of the genus and their aragonitic skeleton Mg/Ca ratios trace the inferred ocean Mg/Ca ratio precisely since the Eocene. Therefore, among marine biogenic carbonate fossils, well-preserved acroporid skeletons represent material with very high potential for reconstruction of ancient ocean chemistry

Towards testing a two-Higgs-doublet model with maximal CP symmetry at the LHC: construction of a Monte Carlo event generator

A Monte Carlo event generator is constructed for a two-Higgs-doublet model with maximal CP symmetry, the MCPM. The model contains five physical Higgs bosons; the $\rho'$, behaving similarly to the standard-model Higgs boson, two extra neutral bosons $h'$ and $h"$, and a charged pair $H^\pm$. The special feature of the MCPM is that, concerning the Yukawa couplings, the bosons $h'$, $h"$ and $H^\pm$ couple directly only to the second generation fermions but with strengths given by the third-generation-fermion masses. Our event generator allows the simulation of the Drell-Yan-type production processes of $h'$, $h"$ and $H^\pm$ in proton-proton collisions at LHC energies. Also the subsequent leptonic decays of these bosons into the $\mu^+ \mu^-$, $\mu^+ \nu_\mu$ and $\mu^- \bar \nu_\mu$ channels are studied as well as the dominant background processes. We estimate the integrated luminosities needed in $p p$ collisions at center-of-mass energies of 8 TeV and 14 TeV for significant observations of the Higgs bosons $h'$, $h"$ and $H^\pm$ in these muonic channels

Multiscale structure description of positon Emission tomography difference images

A method is presented here which aims at analyzing Positon Emission Tomography difference images . This method is based on a explicit description of the structure of the images. Positon Emission Tomography images are used to investigate the functional organisation of the brain, looking at the cerebral blood flow . The differences between two images from the same subject lead to th e changes of activity between two particular states . These differences, called "functional activations", are supposed to be specific o f a particular task . The aim is then to detect functional activations while preserving individual information, unlike classical statistica l methods which look mainly for the average information across several subjects . We then build a 3-dimensional linear scale-spac e from the original image. Objects are extracted at each level of scale in a fully-automatic way. Then they are linked across th e scales to get multi-scale objects in the scale-space . A vector of measures is associated to each of these multi-scale objects in order to characterize functional activations . We present a short study to determine the relevancy of these measures and the way the y can be used .Nous présentons ici une méthode d'analyse d'images de différence issues de la Tomographie par Emission de Positons (TEP) qui repose sur une description explicite de la structure de ces images. Les images TEP permettent, par l'intermédiaire du débit sanguin cérébral, de rendre compte de l'état fonctionnel du cerveau. En utilisant la différence entre deux images d'un même sujet, on essaye de déterminer les différences d'activité cérébrale entre deux états. Ces différences sont supposées être spécifiques d'une tâche isolée par la différence entre les deux états, et nous les appellerons « activations fonctionnelles ». L'objectif est donc de caractériser les activations fonctionnelles dans ces images de différence, tout en préservant l'information individuelle propre au sujet, ce qui n'est pas le cas des méthodes statistiques classiques, qui s'intéressent surtout à l'information moyenne sur l'ensemble des sujets. Un espace d'échelles (« scale-space ») linéaire tri-dimensionnel est d'abord construit à partir de l'image de différence originale, puis des objets sont extraits à chaque niveau d'échelle de manière entièrement automatique. ces objets sont ensuites liés dans les échelles pour former d'autres objets dans le scale-space. Des mesures sont alors définies et associées à chacun d'eux, afin de caractériser les activations fonctionnelles. Une étude sur la pertinence des objets définis et l'utilisation possible des mesures associées est présentée

Occupational choice of return migrants in Moldova

This paper analyzes the occupational choice of return migrants. Using the survey data on different aspects of migration in Moldova, we find that those who stayed illegally in the host country tend to go into wage employment on return to the home country. We also show that relatively better educated migrants tend not to be in formal employment (i.e., appear not to participate in the labor market), whereas those with relatively lower skills or who obtained a worse-than-expected outcome in the host country are more likely to be wage employed in the home country on return. We offer an economic analysis of these paradoxical results

Development of an analogue optical link for the front-end read-out of the ATLAS electromagnetic calorimeter

We have developed an analogue optical data transmission system intended to meet the read-out requirements of the ATLAS liquid argon electromagnetic calorimeter. Eight-way demonstrators have been built and tested. The link uses arrays of VCSEL diodes as the optical emitters, coupled to a 70 m long fibre ribbon to simulate the distance between the detector and the control room. The receiver is based around a custom-designed PIN photodiode array. We describe here the final results of laboratory tests on a demonstrator, laying stress on the VCSEL-to-fibre coupling issues, and the overall performance of the full link. A 9-bit dynamic range is achieved, with a 5on-linearity