4,982 research outputs found
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 bayĂ©siens pour le dĂ©mĂ©lange supervisĂ©, semi-supervisĂ© et non-supervisĂ© dâimages hyperspectrales
Cet article prĂ©sente des algorithmes totalement bayĂ©siens pour le dĂ©mĂ©lange dâimages hyperspectrales. Chaque pixel de lâimage est dĂ©composĂ©e selon une combinaison de spectres de rĂ©fĂ©rences pondĂ©rĂ©s par des coefficients dâabondances selon un modĂšle de mĂ©lange linĂ©aire. Dans un cadre supervisĂ©, nous supposons connus les spectres de rĂ©fĂ©rences. Le problĂšme consiste alors Ă estimer les coefficients du mĂ©lange sous des contraintes de positivitĂ© et dâadditivitĂ©. Une loi a priori adĂ©quate est choisie pour ces coefficients qui sont estimĂ©s Ă partir de leur loi a posteriori. Un algorithme de Monte Carlo par chaĂźne de Markov (MCMC) est dĂ©veloppĂ© pour approcher les estimateurs. Dans un cadre semi-supervisĂ©, les spectres participant au mĂ©lange seront supposĂ©s inconnus. Nous faisons lâhypothĂšse quâils appartiennent Ă une bibliothĂšque spectrale. Un algorithme MCMC Ă sauts rĂ©versibles permet dans ce cas de rĂ©soudre le problĂšme de sĂ©lection de modĂšle. Enfin, dans un dernier cadre dâĂ©tude, les algorithmes prĂ©cĂ©dents sont Ă©tendus au dĂ©mĂ©lange non-supervisĂ© dâimages hyperspectrales, câest-Ă -dire au problĂšme dâestimation conjointe des spectres et des coefficients de mĂ©lange. Ce problĂšme de sĂ©paration aveugle de sources est rĂ©solu dans un sous-espace appropriĂ©
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
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 prĂ©sentons ici une mĂ©thode d'analyse d'images de diffĂ©rence 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'intermĂ©diaire du dĂ©bit sanguin cĂ©rĂ©bral, de rendre compte de l'Ă©tat fonctionnel du cerveau. En utilisant la diffĂ©rence entre deux images d'un mĂȘme sujet, on essaye de dĂ©terminer les diffĂ©rences d'activitĂ© cĂ©rĂ©brale entre deux Ă©tats. Ces diffĂ©rences sont supposĂ©es ĂȘtre spĂ©cifiques d'une tĂąche isolĂ©e par la diffĂ©rence entre les deux Ă©tats, et nous les appellerons « activations fonctionnelles ». L'objectif est donc de caractĂ©riser les activations fonctionnelles dans ces images de diffĂ©rence, tout en prĂ©servant l'information individuelle propre au sujet, ce qui n'est pas le cas des mĂ©thodes statistiques classiques, qui s'intĂ©ressent surtout Ă l'information moyenne sur l'ensemble des sujets. Un espace d'Ă©chelles (« scale-space ») linĂ©aire tri-dimensionnel est d'abord construit Ă partir de l'image de diffĂ©rence originale, puis des objets sont extraits Ă chaque niveau d'Ă©chelle de maniĂšre entiĂšrement automatique. ces objets sont ensuites liĂ©s dans les Ă©chelles pour former d'autres objets dans le scale-space. Des mesures sont alors dĂ©finies et associĂ©es Ă chacun d'eux, afin de caractĂ©riser les activations fonctionnelles. Une Ă©tude sur la pertinence des objets dĂ©finis et l'utilisation possible des mesures associĂ©es est prĂ©sentĂ©e
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 , behaving similarly to the standard-model Higgs boson, two
extra neutral bosons and , and a charged pair . The special
feature of the MCPM is that, concerning the Yukawa couplings, the bosons ,
and 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
, and in proton-proton collisions at LHC energies. Also the
subsequent leptonic decays of these bosons into the , and channels are studied as well as the dominant
background processes. We estimate the integrated luminosities needed in
collisions at center-of-mass energies of 8 TeV and 14 TeV for significant
observations of the Higgs bosons , and in these muonic
channels
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
Wild-type ALK and activating ALK-R1275Q and ALK-F1174L mutations upregulate Myc and initiate tumor formation in murine neural crest progenitor cells.
The anaplastic lymphoma kinase (ALK) gene is overexpressed, mutated or amplified in most neuroblastoma (NB), a pediatric neural crest-derived embryonal tumor. The two most frequent mutations, ALK-F1174L and ALK-R1275Q, contribute to NB tumorigenesis in mouse models, and cooperate with MYCN in the oncogenic process. However, the precise role of activating ALK mutations or ALK-wt overexpression in NB tumor initiation needs further clarification.
Human ALK-wt, ALK-F1174L, or ALK-R1275Q were stably expressed in murine neural crest progenitor cells (NCPC), MONC-1 or JoMa1, immortalized with v-Myc or Tamoxifen-inducible Myc-ERT, respectively. While orthotopic implantations of MONC-1 parental cells in nude mice generated various tumor types, such as NB, osteo/chondrosarcoma, and undifferentiated tumors, due to v-Myc oncogenic activity, MONC-1-ALK-F1174L cells only produced undifferentiated tumors. Furthermore, our data represent the first demonstration of ALK-wt transforming capacity, as ALK-wt expression in JoMa1 cells, likewise ALK-F1174L, or ALK-R1275Q, in absence of exogenous Myc-ERT activity, was sufficient to induce the formation of aggressive and undifferentiated neural crest cell-derived tumors, but not to drive NB development. Interestingly, JoMa1-ALK tumors and their derived cell lines upregulated Myc endogenous expression, resulting from ALK activation, and both ALK and Myc activities were necessary to confer tumorigenic properties on tumor-derived JoMa1 cells in vitro
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