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.

Dynamics of the recruitment of lateral amygdala neurons following successive fear learning to different conditional stimuli

In fear conditioning, an animal learns to associate an unconditioned stimulus (US), such as a shock, and a conditioned stimulus (CS), such as a tone, so that the presentation of the CS alone can trigger conditioned responses. Recent research on the lateral amygdala has shown that following cued fear conditioning, only a subset of higher-excitable neurons are recruited in the memory trace. Their selective deletion after fear conditioning results in a selective erasure of the fearful memory. I hypothesize that the recruitment of highly excitable neurons depends on responsiveness to stimuli, intrinsic excitability and local connectivity. In addition, I hypothesize that neurons recruited for an initial memory also participate in subsequent memories, and that changes in neuronal excitability affect secondary fear learning. To address these hypotheses, I will show that A) a rat can learn to associate two successive short-term fearful memories; B) neuronal populations in the LA are competitively recruited in the memory traces depending on individual neuronal advantages, as well as advantages granted by the local network. By performing two successive cued fear conditioning experiments, I found that rats were able to learn and extinguish the two successive short-term memories, when tested 1 hour after learning for each memory. These rats were equipped with a system of stable extracellular recordings that I developed, which allowed to monitor neuronal activity during fear learning. 233 individual putative pyramidal neurons could modulate their firing rate in response to the conditioned tone (conditioned neurons) and/or non- conditioned tones (generalizing neurons). Out of these recorded putative pyramidal neurons 86 (37%) neurons were conditioned to one or both tones. More precisely, one population of neurons encoded for a shared memory while another group of neurons likely encoded the memories' new features. Notably, in spite of a successful behavioral extinction, the firing rate of those conditioned neurons in response to the conditioned tone remained unchanged throughout memory testing. Furthermore, by analyzing the pre-conditioning characteristics of the conditioned neurons, I determined that it was possible to predict neuronal recruitment based on three factors: 1) initial sensitivity to auditory inputs, with tone-sensitive neurons being more easily recruited than tone- insensitive neurons; 2) baseline excitability levels, with more highly excitable neurons being more likely to become conditioned; and 3) the number of afferent connections received from local neurons, with neurons destined to become conditioned receiving more connections than non-conditioned neurons. - En conditionnement de la peur, un animal apprend à associer un stimulus inconditionnel (SI), tel un choc électrique, et un stimulus conditionné (SC), comme un son, de sorte que la présentation du SC seul suffit pour déclencher des réflexes conditionnés. Des recherches récentes sur l'amygdale latérale (AL) ont montré que, suite au conditionnement à la peur, seul un sous-ensemble de neurones plus excitables sont recrutés pour constituer la trace mnésique. Pour apprendre à associer deux sons au même SI, je fais l'hypothèse que les neurones entrent en compétition afin d'être sélectionnés lors du recrutement pour coder la trace mnésique. Ce recrutement dépendrait d'un part à une activation facilité des neurones ainsi qu'une activation facilité de réseaux de neurones locaux. En outre, je fais l'hypothèse que l'activation de ces réseaux de l'AL, en soi, est suffisante pour induire une mémoire effrayante. Pour répondre à ces hypothèses, je vais montrer que A) selon un processus de mémoire à court terme, un rat peut apprendre à associer deux mémoires effrayantes apprises successivement; B) des populations neuronales dans l'AL sont compétitivement recrutées dans les traces mnésiques en fonction des avantages neuronaux individuels, ainsi que les avantages consentis par le réseau local. En effectuant deux expériences successives de conditionnement à la peur, des rats étaient capables d'apprendre, ainsi que de subir un processus d'extinction, pour les deux souvenirs effrayants. La mesure de l'efficacité du conditionnement à la peur a été effectuée 1 heure après l'apprentissage pour chaque souvenir. Ces rats ont été équipés d'un système d'enregistrements extracellulaires stables que j'ai développé, ce qui a permis de suivre l'activité neuronale pendant l'apprentissage de la peur. 233 neurones pyramidaux individuels pouvaient moduler leur taux d'activité en réponse au son conditionné (neurones conditionnés) et/ou au son non conditionné (neurones généralisant). Sur les 233 neurones pyramidaux putatifs enregistrés 86 (37%) d'entre eux ont été conditionnés à un ou deux tons. Plus précisément, une population de neurones code conjointement pour un souvenir partagé, alors qu'un groupe de neurones différent code pour de nouvelles caractéristiques de nouveaux souvenirs. En particulier, en dépit d'une extinction du comportement réussie, le taux de décharge de ces neurones conditionné en réponse à la tonalité conditionnée est resté inchangée tout au long de la mesure d'apprentissage. En outre, en analysant les caractéristiques de pré-conditionnement des neurones conditionnés, j'ai déterminé qu'il était possible de prévoir le recrutement neuronal basé sur trois facteurs : 1) la sensibilité initiale aux entrées auditives, avec les neurones sensibles aux sons étant plus facilement recrutés que les neurones ne répondant pas aux stimuli auditifs; 2) les niveaux d'excitabilité des neurones, avec les neurones plus facilement excitables étant plus susceptibles d'être conditionnés au son ; et 3) le nombre de connexions reçues, puisque les neurones conditionné reçoivent plus de connexions que les neurones non-conditionnés. Enfin, nous avons constaté qu'il était possible de remplacer de façon satisfaisante le SI lors d'un conditionnement à la peur par des injections bilatérales de bicuculline, un antagoniste des récepteurs de l'acide y-Aminobutirique.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

Imaging Properties of MS Lesions Correlate with Attention Deficits in Early Multiple Sclerosis

Introduction: Cognitive impairment affects 40-65% of multiple sclerosis (MS) patients, often since early stages of the disease (relapsing remitting MS, RRMS). Frequently affected functions are memory, attention or executive abilities but the most sensitive measure of cognitive deficits in early MS is the information processing speed (Amato, 2008). MRI has been extensively exploited to investigate the substrate of cognitive dysfunction in MS but the underlying physiopathological mechanisms remain unclear. White matter lesion load, whole-brain atrophy and cortical lesions' number play a role but correlations are in some cases modest (Rovaris, 2006; Calabrese, 2009). In this study, we aimed at characterizing and correlating the T1 relaxation times of cortical and sub-cortical lesions with cognitive deficits detected by neuropsychological tests in a group of very early RR MS patients. Methods: Ten female patients with very early RRMS (age: 31.6 ±4.7y; disease duration: 3.8 ±1.9y; EDSS disability score: 1.8 ±0.4) and 10 age- and gender-matched healthy volunteers (mean age: 31.2 ±5.8y) were included in the study. All participants underwent the following neuropsychological tests: Rao's Brief Repeatable Battery of Neuropsychological tests (BRB-N), Stockings of Cambridge, Trail Making Test (TMT, part A and B), Boston Naming Test, Hooper Visual Organization Test and copy of the Rey-Osterrieth Complex Figure. Within 2 weeks from neuropsychological assessment, participants underwent brain MRI at 3T (Magnetom Trio a Tim System, Siemens, Germany) using a 32-channel head coil. The imaging protocol included 3D sequences with 1x1x1.2 mm3 resolution and 256x256x160 matrix, except for axial 2D-FLAIR: -DIR (T2-weighted, suppressing both WM and CSF; Pouwels, 2006) -MPRAGE (T1-weighted; Mugler, 1991) -MP2RAGE (T1-weighted with T1 maps; Marques, 2010) -FLAIR SPACE (only for patient 4-10, T2-weighted; Mugler, 2001) -2D Axial FLAIR (0.9x0.9x2.5 mm3, 256x256x44 matrix). Lesions were identified by one experienced neurologist and radiologist using all contrasts, manually contoured and assigned to regional locations (cortical or sub-cortical). Lesion number, volume and T1 relaxation time were calculated for lesions in each contrast and in a merged mask representing the union of the lesions from all contrasts. T1 relaxation times of lesions were normalized with the mean T1 value in corresponding control regions of the healthy subjects. Statistical analysis was performed using GraphPad InStat software. Cognitive scores were compared between patients and controls with paired t-tests; p values ≤ 0.05 were considered significant. Spearmann correlation tests were performed between the cognitive tests, which differed significantly between patients and controls, and lesions' i) number ii) volume iii) T1 relaxation time iv) disease duration and v) years of study. Results: Cortical and sub-cortical lesions count, T1 values and volume are reported in Table 1 (A and B). All early RRMS patients showed cortical lesions (CLs) and the majority consisted of CLs type I (lesions with a cortical component extending to the sub-cortical tissue). The rest of cortical lesions were characterized as type II (intra-cortical lesions). No type III/IV lesions (large sub-pial lesions) were detected. RRMS patients were slightly less educated (13.5±2.5y vs. 16.3±1.8y of study, p=0.02) than the controls. Signs of cortical dysfunction (i.e. impaired learning, language, visuo-spatial skills or gnosis) were rare in all patients. However, patients showed on average lower scores on measures of visual attention and information processing speed (TMT-part A: p=0.01; TMT-part B: p=0.006; PASAT-included in the BRB-N: p=0.04). The T1 relaxation values of CLs type I negatively correlated with the TMT-part A score (r=0.78, p<0.01). The correlations of TMT-part B score and PASAT score with T1 relaxation time of lesions as well and the correlation between TMT-part A, TMT-part B and PASAT score with lesions' i) number ii) volume iii) disease duration and iv) years of study did not reach significance. In order to preclude possible influences from partial volume effects on the T1 values, the correlation between lesion volume and T1 value of CLs type I was calculated; no correlation was found, suggesting that partial volume effects did not affect the statistics. Conclusions: The present pilot study reports for the first time the presence and the T1 characteristics at 3 T of cortical lesions in very early RRMS (< 6 y disease duration). It also shows that CLS type I represents the most frequent cortical lesion type in this cohort of RRMS patients. In addition, it reveals a negative correlation between the attentional test TMT-part A and the T1 properties of cortical lesions type I. In other words, lower attention deficits are concomitant with longer T1-relaxation time in cortical lesions. In respect to this last finding, it could be speculated that long relaxation time correspond to a certain degree of tissue loss that is enough to stimulate compensatory mechanisms. This hypothesis is in line with previous fMRI studies showing functional compensatory mechanisms to help maintaining normal or sub-normal attention performances in RR MS patients (Penner, 2003).

Development of place navigation in rats from weaning to puberty.

Young hooded rats were trained to escape onto a hidden platform after swimming in a pool of opaque water. Subjects 21, 28, 35, 42, and 64 days of age on the first training day were given 28 trials on 5 consecutive days. Half of the rats were required to localize the platform in relation to external room cues only ("place only" condition) and the other half were helped by the presence of a visible cue on the platform ("cue + place" condition). A deficiency in place navigation was observed in the 21- and 28-day groups; they showed slow escape and took circuitous routes more often than older rats. This deficiency was related to a poor spatial bias toward the training position when the subjects were allowed to swim for 30 s in the absence of the platform, at the end of the 28-trial training period (probe trial). The 35-day group showed adult-like learning ability in both training conditions, but failed to show searching behavior during the probe trial after having been trained in the presence of the proximal cue. Only rats older than 40 days showed typical adult behavior such as swimming directly toward the platform from any starting position and localized searching around the absent platform's position during the probe trial, no matter what the training conditions were. These results suggest that central nervous system structures responsible for place learning in the rat are functional from around 32 days of age, but fail to trigger searching behavior following cued training before the sixth week.

Fine-scale spatial genetic structure and gene dispersal in Silene latifolia.

Plants are sessile organisms, often characterized by limited dispersal. Seeds and pollen are the critical stages for gene flow. Here we investigate spatial genetic structure, gene dispersal and the relative contribution of pollen vs seed in the movement of genes in a stable metapopulation of the white campion Silene latifolia within its native range. This short-lived perennial plant is dioecious, has gravity-dispersed seeds and moth-mediated pollination. Direct measures of pollen dispersal suggested that large populations receive more pollen than small isolated populations and that most gene flow occurs within tens of meters. However, these studies were performed in the newly colonized range (North America) where the specialist pollinator is absent. In the native range (Europe), gene dispersal could fall on a different spatial scale. We genotyped 258 individuals from large and small (15) subpopulations along a 60 km, elongated metapopulation in Europe using six highly variable microsatellite markers, two X-linked and four autosomal. We found substantial genetic differentiation among subpopulations (global F(ST)=0.11) and a general pattern of isolation by distance over the whole sampled area. Spatial autocorrelation revealed high relatedness among neighboring individuals over hundreds of meters. Estimates of gene dispersal revealed gene flow at the scale of tens of meters (5-30 m), similar to the newly colonized range. Contrary to expectations, estimates of dispersal based on X and autosomal markers showed very similar ranges, suggesting similar levels of pollen and seed dispersal. This may be explained by stochastic events of extensive seed dispersal in this area and limited pollen dispersal.

Clustering and hot spot detection in socio-economic spatio-temporal data

Distribution of socio-economic features in urban space is an important source of information for land and transportation planning. The metropolization phenomenon has changed the distribution of types of professions in space and has given birth to different spatial patterns that the urban planner must know in order to plan a sustainable city. Such distributions can be discovered by statistical and learning algorithms through different methods. In this paper, an unsupervised classification method and a cluster detection method are discussed and applied to analyze the socio-economic structure of Switzerland. The unsupervised classification method, based on Ward's classification and self-organized maps, is used to classify the municipalities of the country and allows to reduce a highly-dimensional input information to interpret the socio-economic landscape. The cluster detection method, the spatial scan statistics, is used in a more specific manner in order to detect hot spots of certain types of service activities. The method is applied to the distribution services in the agglomeration of Lausanne. Results show the emergence of new centralities and can be analyzed in both transportation and social terms.