Development of spatial integration depends on top-down and interhemispheric connections that can be perturbed in migraine: a DCM analysis.

In humans, spatial integration develops slowly, continuing through childhood into adolescence. On the assumption that this protracted course depends on the formation of networks with slowly developing top-down connections, we compared effective connectivity in the visual cortex between 13 children (age 7-13) and 14 adults (age 21-42) using a passive perceptual task. The subjects were scanned while viewing bilateral gratings, which either obeyed Gestalt grouping rules [colinear gratings (CG)] or violated them [non-colinear gratings (NG)]. The regions of interest for dynamic causal modeling were determined from activations in functional MRI contrasts stimuli > background and CG > NG. They were symmetrically located in V1 and V3v areas of both hemispheres. We studied a common model, which contained reciprocal intrinsic and modulatory connections between these regions. An analysis of effective connectivity showed that top-down modulatory effects generated at an extrastriate level and interhemispheric modulatory effects between primary visual areas (all inhibitory) are significantly weaker in children than in adults, suggesting that the formation of feedback and interhemispheric effective connections continues into adolescence. These results are consistent with a model in which spatial integration at an extrastriate level results in top-down messages to the primary visual areas, where they are supplemented by lateral (interhemispheric) messages, making perceptual encoding more efficient and less redundant. Abnormal formation of top-down inhibitory connections can lead to the reduction of habituation observed in migraine patients.

Olfactory and/or visual cues for spatial navigation through ontogeny: olfactory cues enable the use of visual cues

This study analyzed the spatial memory capacities of rats in darkness with visual and/or olfactory cues through ontogeny. Tests were conducted with the homing board, where rats had to find the correct escape hole. Four age groups (24 days, 48 days, 3-6 months, and 12 months) were trained in 3 conditions: (a) 3 identical light cues; (b) 5 different olfactory cues; and (c) both types of cues, followed by removal of the olfactory cues. Results indicate that immature rats first take into account olfactory information but are unable to orient with only the help of discrete visual cues. Olfaction enables the use of visual information by 48-day-old rats. Visual information predominantly supports spatial cognition in adult and 12-month-old rats. Results point out cooperation between vision and olfaction for place navigation during ontogeny in rats.

Visual search in spatial neglect studied with a preview paradigm.

Impaired visual search is a hallmark of spatial neglect. When searching for an unique feature (e.g., color) neglect patients often show only slight visual field asymmetries. In contrast, when the target is defined by a combination of features (e.g., color and form) they exhibit a severe deficit of contralesional search. This finding suggests a selective impairment of the serial deployment of spatial attention. Here, we examined this deficit with a preview paradigm. Neglect patients searched for a target defined by the conjunction of shape and color, presented together with varying numbers of distracters. The presentation time was varied such that on some trials participants previewed the target together with same-shape/different-color distracters, for 300 or 600 ms prior to the appearance of additional different-shape/same-color distracters. On the remaining trials the target and all distracters were shown simultaneously. Healthy participants exhibited a serial search strategy only when all items were presented simultaneously, whereas in both preview conditions a pop-out effect was observed. Neglect patients showed a similar pattern when the target was presented in the right hemifield. In contrast, when searching for a target in the left hemifield they showed serial search in the no-preview condition, as well as with a preview of 300 ms, and partly even at 600 ms. A control experiment suggested that the failure to fully benefit from item preview was probably independent of accurate perception of time. Our results, when viewed in the context of existing literature, lead us to conclude that the visual search deficit in neglect reflects two additive factors: a biased representation of attentional priority in favor of ipsilesional information and exaggerated capture of attention by ipsilesional abrupt onsets.

Optimization of spatial resolution for peripheral magnetic resonance angiography.

RATIONALE AND OBJECTIVES: To determine optimum spatial resolution when imaging peripheral arteries with magnetic resonance angiography (MRA). MATERIALS AND METHODS: Eight vessel diameters ranging from 1.0 to 8.0 mm were simulated in a vascular phantom. A total of 40 three-dimensional flash MRA sequences were acquired with incremental variations of fields of view, matrix size, and slice thickness. The accurately known eight diameters were combined pairwise to generate 22 "exact" degrees of stenosis ranging from 42% to 87%. Then, the diameters were measured in the MRA images by three independent observers and with quantitative angiography (QA) software and used to compute the degrees of stenosis corresponding to the 22 "exact" ones. The accuracy and reproducibility of vessel diameter measurements and stenosis calculations were assessed for vessel size ranging from 6 to 8 mm (iliac artery), 4 to 5 mm (femoro-popliteal arteries), and 1 to 3 mm (infrapopliteal arteries). Maximum pixel dimension and slice thickness to obtain a mean error in stenosis evaluation of less than 10% were determined by linear regression analysis. RESULTS: Mean errors on stenosis quantification were 8.8% +/- 6.3% for 6- to 8-mm vessels, 15.5% +/- 8.2% for 4- to 5-mm vessels, and 18.9% +/- 7.5% for 1- to 3-mm vessels. Mean errors on stenosis calculation were 12.3% +/- 8.2% for observers and 11.4% +/- 15.1% for QA software (P = .0342). To evaluate stenosis with a mean error of less than 10%, maximum pixel surface, the pixel size in the phase direction, and the slice thickness should be less than 1.56 mm2, 1.34 mm, 1.70 mm, respectively (voxel size 2.65 mm3) for 6- to 8-mm vessels; 1.31 mm2, 1.10 mm, 1.34 mm (voxel size 1.76 mm3), for 4- to 5-mm vessels; and 1.17 mm2, 0.90 mm, 0.9 mm (voxel size 1.05 mm3) for 1- to 3-mm vessels. CONCLUSION: Higher spatial resolution than currently used should be selected for imaging peripheral vessels.

The MIGCLIM R package - seamless integration of dispersal constraints into projections of species distribution models

The MIGCLIM R package is a function library for the open source R software that enables the implementation of species-specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios. The model is based on a cellular automaton and the basic modeling unit is a cell that is inhabited or not. Model parameters include dispersal distance and kernel, long distance dispersal, barriers to dispersal, propagule production potential and habitat invasibility. The MIGCLIM R package has been designed to be highly flexible in the parameter values it accepts, and to offer good compatibility with existing species distribution modeling software. Possible applications include the projection of future species distributions under environmental change conditions and modeling the spread of invasive species.

L'exploitation des eaux souterraines en Syrie centrale : construction de diagnostics et politiques d'intervention

Syrian dry areas have been for several millennia a place of interaction between human populations and the environment. If environmental constraints and heterogeneity condition the human occupation and exploitation of resources, socio-political, economic and historical elements play a fundamental role. Since the late 1980s, Syrian dry areas are viewed as suffering a serious water crisis, due to groundwater overdraft. The Syrian administration and international development agencies believe that groundwater overexploitation is also leading to a decline of agricultural activities and to poverty increase. Action is thus required to address these problems.However, the overexploitation diagnosis needs to be reviewed. The overexploitation discourse appears in the context of Syria's opening to international organizations and to the market economy. It echoes the international discourse of "global water crisis". The diagnosis is based on national indicators recycling old Soviet data that has not been updated. In the post-Soviet era, the Syrian national water policy seems to abandon large surface water irrigation projects in favor of a strategy of water use rationalization and groundwater conservation in crisis regions, especially in the district of Salamieh.This groundwater conservation policy has a number of inconsistencies. It is justified for the administration and also probably for international donors, since it responds to an indisputable environmental emergency. However, efforts to conserve water are anecdotal or even counterproductive. The water conservation policy appears a posteriori as an extension of the national policy of food self-sufficiency. The dominant interpretation of overexploitation, and more generally of the water crisis, prevents any controversary approach of the status of resources and of the agricultural system in general and thus destroys any attempt to discuss alternatives with respect to groundwater management, allocation, and their inclusion in development programs.A revisited diagnosis of the situation needs to take into account spatial and temporal dimensions of the groundwater exploitation and to analyze the co-evolution of hydrogeological and agricultural systems. It should highlight the adjustments adopted to cope with environmental and economic variability, changes of water availability and regulatory measures enforcements. These elements play an important role for water availability and for the spatial, temporal, sectoral allocation of water resource. The groundwater exploitation in the last century has obviously had an impact on the environment, but the changes are not necessarily catastrophic.The current groundwater use in central Syria increases the uncertainty by reducing the ability of aquifers to buffer climatic changes. However, the climatic factor is not the only source of uncertainty. The high volatility of commodity prices, fuel, land and water, depending on the market but also on the will (and capacity) of the Syrian State to preserve social peace is a strong source of uncertainty. The research should consider the whole range of possibilities and propose alternatives that take into consideration the risks they imply for the water users, the political will to support or not the local access to water - thus involving a redefinition of the economic and social objectives - and finally the ability of international organizations to reconsider pre-established diagnoses.

Temporal and spatial distribution of Leishmania mexicana infections in a population of Neotoma micropus

A 19-month mark-release-recapture study of Neotoma micropus with sequential screening for Leishmania mexicana was conducted in Bexar County, Texas, USA. The overall prevalence rate was 14.7% and the seasonal prevalence rates ranged from 3.8 to 26.7%. Nine incident cases were detected, giving an incidence rate of 15.5/100 rats/year. Follow-up of 101 individuals captured two or more times ranged from 14 to 462 days. Persistence of L. mexicana infections averaged 190 days and ranged from 104 to 379 days. Data on dispersal, density, dispersion, and weight are presented, and the role of N. micropus as a reservoir host for L. mexicana is discussed.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Developmental and Anatomical Constraints on Vertebrate Genome Evolution

Pendant ma thèse de doctorat, j'ai utilisé des espèces modèles, comme la souris et le poisson-zèbre, pour étudier les facteurs qui affectent l'évolution des gènes et leur expression. Plus précisément, j'ai montré que l'anatomie et le développement sont des facteurs clés à prendre en compte, car ils influencent la vitesse d'évolution de la séquence des gènes, l'impact sur eux de mutations (i.e. la délétion du gène est-elle létale ?), et leur tendance à se dupliquer. Où et quand il est exprimé impose à un gène certaines contraintes ou au contraire lui donne des opportunités d'évoluer. J'ai pu comparer ces tendances aux modèles classiques d'évolution de la morphologie, que l'on pensait auparavant refléter directement les contraintes s'appliquant sur le génome. Nous avons montré que les contraintes entre ces deux niveaux d'organisation ne peuvent pas être transférées simplement : il n'y a pas de lien direct entre la conservation du génotype et celle de phénotypes comme la morphologie. Ce travail a été possible grâce au développement d'outils bioinformatiques. Notamment, j'ai travaillé sur le développement de la base de données Bgee, qui a pour but de comparer l'expression des gènes entre différentes espèces de manière automatique et à large échelle. Cela implique une formalisation de l'anatomie, du développement et de concepts liés à l'homologie grâce à l'utilisation d'ontologies. Une intégration cohérente de données d'expression hétérogènes (puces à ADN, marqueurs de séquence exprimée, hybridations in situ) a aussi été nécessaire. Cette base de données est mise à jour régulièrement et disponible librement. Elle devrait contribuer à étendre les possibilités de comparaison de l'expression des gènes entre espèces pour des études d'évo-devo (évolution du développement) et de génomique. During my PhD, I used model species of vertebrates, such as mouse and zebrafish, to study factors affecting the evolution of genes and their expression. More precisely I have shown that anatomy and development are key factors to take into account, influencing the rate of gene sequence evolution, the impact of mutations (i.e. is the deletion of a gene lethal?), and the propensity of a gene to duplicate. Where and when genes are expressed imposes constraints, or on the contrary leaves them some opportunity to evolve. We analyzed these patterns in relation to classical models of morphological evolution in vertebrates, which were previously thought to directly reflect constraints on the genomes. We showed that the patterns of evolution at these two levels of organization do not translate smoothly: there is no direct link between the conservation of genotype and phenotypes such as morphology. This work was made possible by the development of bioinformatics tools. Notably, I worked on the development of the database Bgee, which aims at comparing gene expression between different species in an automated and large-scale way. This involves the formalization of anatomy, development, and concepts related to homology, through the use of ontologies. A coherent integration of heterogeneous expression data (microarray, expressed sequence tags, in situ hybridizations) is also required. This database is regularly updated and freely available. It should contribute to extend the possibilities for comparison of gene expression between species in evo-devo and genomics studies.