La vitesse des opérations mentales : son utilité pour la prédiction des déficits cognitifs et du niveau de récupération chez les personnes ayant subi un accident vasculaire cérébral

Le développement et le raffinement de moyens d’évaluation à visées diagnostique et prédictive adaptés à la clientèle victime d’un accident vasculaire cérébral constituent un enjeu important pour les milieux d’intervention et les individus concernés. Ainsi, la mise sur pied d’une instrumentation permettant de justifier, appuyer et orienter les plans de traitement dès l’entrée en réadaptation est à l’origine d’un courant de recherche important. La présente étude s’inscrit dans cet effort de raffinement des outils cliniques utilisés avec cette clientèle. Le projet vise à vérifier plusieurs hypothèses concernant la possibilité de prédire de façon précoce le potentiel de récupération des individus victimes d’un accident vasculaire cérébral à partir d’indices de vitesse des opérations mentales. Dans un premier temps, l’étude a permis de démontrer qu’il est possible d’observer une amélioration significative (p < 0,05) de la plupart des indices de vitesse des opérations mentales, mesurés par des tâches informatisées (les Tests de rendement cognitifs pour adultes : TRCa (Loranger & Pépin, 1993)), entre la première semaine suivant l’entrée en réadaptation et la sixième. Elle suggère également que le temps de réaction avec prise de décision est plus affecté par la lésion cérébrale que le temps de réaction simple. De plus, elle confirme la présence de corrélations significatives (p < 0,05) de modérées à élevées entre les TRCa et des indices de la Mesure d’incapacité fonctionnelle (MIF) à une et à six semaines de l’entrée en réadaptation. Il est également possible d’y noter la présence de corrélations significatives élevées entre les mesures de vitesse des opérations mentales à la première semaine et la MIF à la sixième semaine. Les résultats sont discutés en fonction de leurs implications sur le suivi de cette clientèle en phase de réadaptation

TRIDENT: an Infrared Differential Imaging Camera Optimized for the Detection of Methanated Substellar Companions

A near-infrared camera in use at the Canada-France-Hawaii Telescope (CFHT) and at the 1.6-m telescope of the Observatoire du Mont-Megantic is described. The camera is based on a Hawaii-1 1024x1024 HgCdTe array detector. Its main feature is to acquire three simultaneous images at three wavelengths across the methane absorption bandhead at 1.6 microns, enabling, in theory, an accurate subtraction of the stellar point spread function (PSF) and the detection of faint close methanated companions. The instrument has no coronagraph and features fast data acquisition, yielding high observing efficiency on bright stars. The performance of the instrument is described, and it is illustrated by laboratory tests and CFHT observations of the nearby stars GL526, Ups And and Chi And. TRIDENT can detect (6 sigma) a methanated companion with delta H = 9.5 at 0.5" separation from the star in one hour of observing time. Non-common path aberrations and amplitude modulation differences between the three optical paths are likely to be the limiting factors preventing further PSF attenuation. Instrument rotation and reference star subtraction improve the detection limit by a factor of 2 and 4 respectively. A PSF noise attenuation model is presented to estimate the non-common path wavefront difference effect on PSF subtraction performance.Comment: 41 pages, 16 figures, accepted for publication in PAS

Association between Abdominal Fat (DXA) and Its Subcomponents (CT Scan) before and after Weight Loss in Obese Postmenopausal Women: A MONET Study

Introduction. Subcutaneous fat (ScF) and visceral fat (VF) measurements using CT scan are expensive and may imply significant radiation doses. Cross-sectional studies using CT scan showed that ScF and VF are significantly correlated with abdominal fat measured by DXA (AF-DXA). The association has not been studied after a weight loss. Objective. To determine (1) the associations between AF-DXA and ScF and VF before and after weight loss and (2) the associations between their changes. Methods. 137 overweight/obese postmenopausal women were divided in two groups (1-caloric restriction or 2-caloric restriction + resistance training). AF was assessed using DXA and CT scan. Results. Correlations between AF-DXA and ScF (before: r = 0.87, after; r = 0.87; P < .01) and, AF-DXA and VF (before: r = 0.61, after; r = 0.69; P < .01) are not different before and after the weight loss. Correlations between delta AF-DXA and delta ScF (r = 0.72; P < .01) or delta VF (r = 0.51; P < .01) were found. Conclusion. The use of AF-DXA as a surrogate for VF after weight loss is questionable, but may be interesting for ScF

The resting human brain and motor learning.

Functionally related brain networks are engaged even in the absence of an overt behavior. The role of this resting state activity, evident as low-frequency fluctuations of BOLD (see [1] for review, [2-4]) or electrical [5, 6] signals, is unclear. Two major proposals are that resting state activity supports introspective thought or supports responses to future events [7]. An alternative perspective is that the resting brain actively and selectively processes previous experiences [8]. Here we show that motor learning can modulate subsequent activity within resting networks. BOLD signal was recorded during rest periods before and after an 11 min visuomotor training session. Motor learning but not motor performance modulated a fronto-parietal resting state network (RSN). Along with the fronto-parietal network, a cerebellar network not previously reported as an RSN was also specifically altered by learning. Both of these networks are engaged during learning of similar visuomotor tasks [9-22]. Thus, we provide the first description of the modulation of specific RSNs by prior learning--but not by prior performance--revealing a novel connection between the neuroplastic mechanisms of learning and resting state activity. Our approach may provide a powerful tool for exploration of the systems involved in memory consolidation

Integral-field near-infrared spectroscopy of two blue dwarf galaxies: NGC 5253 and He 2-10

We present integral field spectroscopy in the near infrared (NIR) of He 2-10 and NGC 5253, two well known nearby dwarf irregular galaxies showing high star-formation rates. Our data provide an unprecedented detailed view of the interstellar medium and star formation in these galaxies, allowing us to obtain spatially resolved information from the NIR emission and absorption line tracers. We study the spatial distribution and kinematics of different components of the interstellar medium (ISM) mostly through the Bracket series lines, the molecular hydrogen spectrum, [FeII] emission, and CO absorptions. Although the ISM is mostly photo-excited, as derived by the [FeII]/Bry and H2 line ratios, some regions corresponding to non-thermal radio sources show a [FeII]/Bry excess due to a significant contribution of SN driven shocks. In He 2-10 we find that the molecular gas clouds, as traced by CO(2-1) and H2 infrared line, show consistent morphologies and velocities when studied with the two different tracers. Moreover, there is a clear association with the youngest super star clusters as traced by the ionized gas. In the same galaxy we observe a cavity depleted of gas, which is surrounded by some of the most active regions of star formation, that we interpret as a signature of feedback-induced star formation from older episodes of star formation. Finally, we measured high turbulence in the ISM of both galaxies, sigma~30-80 km/s, driven by the high star-formation activity.Comment: 12 pages, 10 figures, accepted for publication in A&

Optimal inference with suboptimal models:Addiction and active Bayesian inference

When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent's beliefs - based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment - as opposed to the agent's beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less 'optimally' than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject's generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described 'limited offer' task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work

Maximum likelihood models and algorithms for gene tree evolution with duplications and losses

<p>Abstract</p> <p>Background</p> <p>The abundance of new genomic data provides the opportunity to map the location of gene duplication and loss events on a species phylogeny. The first methods for mapping gene duplications and losses were based on a parsimony criterion, finding the mapping that minimizes the number of duplication and loss events. Probabilistic modeling of gene duplication and loss is relatively new and has largely focused on birth-death processes.</p> <p>Results</p> <p>We introduce a new maximum likelihood model that estimates the speciation and gene duplication and loss events in a gene tree within a species tree with branch lengths. We also provide an, in practice, efficient algorithm that computes optimal evolutionary scenarios for this model. We implemented the algorithm in the program DrML and verified its performance with empirical and simulated data.</p> <p>Conclusions</p> <p>In test data sets, DrML finds optimal gene duplication and loss scenarios within minutes, even when the gene trees contain sequences from several hundred species. In many cases, these optimal scenarios differ from the lca-mapping that results from a parsimony gene tree reconciliation. Thus, DrML provides a new, practical statistical framework on which to study gene duplication.</p

Association between Abdominal Fat (DXA) and Its Subcomponents (CT Scan) before and after Weight Loss in Obese Postmenopausal Women: A MONET Study

Introduction. Subcutaneous fat (ScF) and visceral fat (VF) measurements using CT scan are expensive and may imply significant radiation doses. Cross-sectional studies using CT scan showed that ScF and VF are significantly correlated with abdominal fat measured by DXA (AF-DXA). The association has not been studied after a weight loss. Objective. To determine (1) the associations between AF-DXA and ScF and VF before and after weight loss and (2) the associations between their changes. Methods. 137 overweight/obese postmenopausal women were divided in two groups (1-caloric restriction or 2-caloric restriction + resistance training). AF was assessed using DXA and CT scan. Results. Correlations between AF-DXA and ScF (before: r = 0.87, after; r = 0.87; P &lt; .01) and, AF-DXA and VF (before: r = 0.61, after; r = 0.69; P &lt; .01) are not different before and after the weight loss. Correlations between delta AF-DXA and delta ScF (r = 0.72; P &lt; .01) or delta VF (r = 0.51; P &lt; .01) were found. Conclusion. The use of AF-DXA as a surrogate for VF after weight loss is questionable, but may be interesting for ScF