Structural covariance of superficial white matter in mild Alzheimer's disease compared to normal aging.

INTRODUCTION: Interindividual variations in regional structural properties covary across the brain, thus forming networks that change as a result of aging and accompanying neurological conditions. The alterations of superficial white matter (SWM) in Alzheimer's disease (AD) are of special interest, since they follow the AD-specific pattern characterized by the strongest neurodegeneration of the medial temporal lobe and association cortices. METHODS: Here, we present an SWM network analysis in comparison with SWM topography based on the myelin content quantified with magnetization transfer ratio (MTR) for 39 areas in each hemisphere in 15 AD patients and 15 controls. The networks are represented by graphs, in which nodes correspond to the areas, and edges denote statistical associations between them. RESULTS: In both groups, the networks were characterized by asymmetrically distributed edges (predominantly in the left hemisphere). The AD-related differences were also leftward. The edges lost due to AD tended to connect nodes in the temporal lobe to other lobes or nodes within or between the latter lobes. The newly gained edges were mostly confined to the temporal and paralimbic regions, which manifest demyelination of SWM already in mild AD. CONCLUSION: This pattern suggests that the AD pathological process coordinates SWM demyelination in the temporal and paralimbic regions, but not elsewhere. A comparison of the MTR maps with MTR-based networks shows that although, in general, the changes in network architecture in AD recapitulate the topography of (de)myelination, some aspects of structural covariance (including the interhemispheric asymmetry of networks) have no immediate reflection in the myelination pattern.

Social Cognition is not Reducible to Theory of Mind. When Children use Deontic Rules to Predict Others' Behaviors

The objective of this paper is to discuss whether children have a capacity for deonticreasoning that is irreducible to mentalizing. The results of two experiments point tothe existence of such non-mentalistic understanding and prediction of the behaviourof others. In Study 1, young children (3- and 4-year-olds) were told different versionsof classic false-belief tasks, some of which were modified by the introduction of a ruleor a regularity. When the task (a standard change of location task) included a rule, theperformance of 3-year-olds, who fail traditional false-belief tasks, significantly improved.In Study 2, 3-year-olds proved to be able to infer a rule from a social situation and touse it in order to predict the behaviour of a character involved in a modified versionof the false-belief task. These studies suggest that rules play a central role in the socialcognition of young children and that deontic reasoning might not necessarily involvemind reading.

[(18)F]FDG-PET Standard Uptake Value as a Metabolic Predictor of Bone Marrow Response to Radiation: Impact on Acute and Late Hematological Toxicity in Cervical Cancer Patients Treated With Chemoradiation Therapy.

PURPOSE: To quantify the relationship between bone marrow (BM) response to radiation and radiation dose by using (18)F-labeled fluorodeoxyglucose positron emission tomography [(18)F]FDG-PET standard uptake values (SUV) and to correlate these findings with hematological toxicity (HT) in cervical cancer (CC) patients treated with chemoradiation therapy (CRT). METHODS AND MATERIALS: Seventeen women with a diagnosis of CC were treated with standard doses of CRT. All patients underwent pre- and post-therapy [(18)F]FDG-PET/computed tomography (CT). Hemograms were obtained before and during treatment and 3 months after treatment and at last follow-up. Pelvic bone was autosegmented as total bone marrow (BMTOT). Active bone marrow (BMACT) was contoured based on SUV greater than the mean SUV of BMTOT. The volumes (V) of each region receiving 10, 20, 30, and 40 Gy (V10, V20, V30, and V40, respectively) were calculated. Metabolic volume histograms and voxel SUV map response graphs were created. Relative changes in SUV before and after therapy were calculated by separating SUV voxels into radiation therapy dose ranges of 5 Gy. The relationships among SUV decrease, radiation dose, and HT were investigated using multiple regression models. RESULTS: Mean relative pre-post-therapy SUV reductions in BMTOT and BMACT were 27% and 38%, respectively. BMACT volume was significantly reduced after treatment (from 651.5 to 231.6 cm(3), respectively; P<.0001). BMACT V30 was significantly correlated with a reduction in BMACT SUV (R(2), 0.14; P<.001). The reduction in BMACT SUV significantly correlated with reduction in white blood cells (WBCs) at 3 months post-treatment (R(2), 0.27; P=.04) and at last follow-up (R(2), 0.25; P=.04). Different dosimetric parameters of BMTOT and BMACT correlated with long-term hematological outcome. CONCLUSIONS: The volumes of BMTOT and BMACT that are exposed to even relatively low doses of radiation are associated with a decrease in WBC counts following CRT. The loss in proliferative BM SUV uptake translates into low WBC nadirs after treatment. These results suggest the potential of intensity modulated radiation therapy to spare BMTOT to reduce long-term hematological toxicity.

Temporal distribution and magnitude of the vulnerability period around stroke depend on stroke subtype.

Background: We aimed to analyze the rate and time distribution of pre- and post-morbid cerebrovascular events in a single ischemic stroke population, and whether these depend on the etiology of the index stroke. Methods: In 2,203 consecutive patients admitted to a single stroke center registry (ASTRAL), the ischemic stroke that led to admission was considered the index event. Frequency distribution and cumulative relative distribution graphs of the most recent and first recurrent event (ischemic stroke, transient ischemic attack, intracranial or subarachnoid hemorrhage) were drawn in weekly and daily intervals for all strokes and for all stroke types. Results: The frequency of events at identical time points before and after the index stroke was mostly reduced in the first week after (vs. before) stroke (1.0 vs. 4.2%, p < 0.001) and the first month (2.7 vs. 7.4%, p < 0.001), and then ebbed over the first year (8.4 vs. 13.1%, p < 0.001). On daily basis, the peak frequency was noticed at day -1 (1.6%) with a reduction to 0.7% on the index day and 0.17% 24 h after. The event rate in patients with atherosclerotic stroke was particularly high around the index event, but 1-year cumulative recurrence rate was similar in all stroke types. Conclusions: We confirm a short window of increased vulnerability in ischemic stroke and show a 4-, 3- and 2-fold reduction in post-stroke events at 1 week, 1 month and 1 year, respectively, compared to identical pre-stroke periods. This break in the 'stroke wave' is particularly striking after atherosclerotic and lacunar strokes.

Extreme prematurity and intra uterine growth restriction effects in brain network topology at school age

Higher risk for long-term behavioral and emotional sequelae, with attentional problems (with or without hyperactivity) is now becoming one of the hallmarks of extreme premature (EP) birth and birth after pregancy conditions leading to poor intra uterine growth restriction (IUGR) [1,2]. However, little is know so far about the neurostructural basis of these complexe brain functional abnormalities that seem to have their origins in early critical periods of brain development. The development of cortical axonal pathways happens in a series of sequential events. The preterm phase (24-36 post conecptional weeks PCW) is known for being crucial for growth of the thalamocortical fiber bundles as well as for the development of long projectional, commisural and projectional fibers [3]. Is it logical to expect, thus, that being exposed to altered intrauterine environment (altered nutrition) or to extrauterine environment earlier that expected, lead to alterations in the structural organization and, consequently, alter the underlying white matter (WM) structure. Understanding rate and variability of normal brain development, and detect differences from typical development may offer insight into the neurodevelopmental anomalies that can be imaged at later stages. Due to its unique ability to non-invasively visualize and quantify in vivo white matter tracts in the brain, in this study we used diffusion MRI (dMRI) tractography to derive brain graphs [4,5,6]. This relatively simple way of modeling the brain enable us to use graph theory to study topological properties of brain graphs in order to study the effects of EP and IUGR on childrens brain connectivity at age 6 years old.

Introduction

Although increasing our knowledge of the properties of networks of cities is essential, these properties can be measured at the city level, and must be assessed by analyzing actor networks. The present volume focuses less on individual characteristics and more on the interactions of actors and institutions that create functional territories in which the structure of existing links constrains emerging links. Rather than basing explanations on external factors, the goal is to determine the extent to which network properties reflect spatial distributions and create local synergies at the meso level that are incorporated into global networks at the macro level where different geographical scales occur. The paper introduces the way to use the graphs structure to identify empirically relevant groups and levels that explain dynamics. It defines what could be called âeurooemulti-levelâeuro, âeurooemulti-scaleâeuro, or âeurooemultidimensionalâeuro networks in the context of urban geography. It explains how the convergence of the network multi-territoriality paradigm collaboratively formulated, and manipulated by geographers and computer scientists produced the SPANGEO project, which is exposed in this volume.

Differentiation of heroin and cocaine using dual-energy CT-an experimental study.

OBJECTIVE: To evaluate if heroin and cocaine can be distinguished using dual-energy CT. MATERIALS AND METHODS: Twenty samples of heroin and cocaine at different concentrations and standardized compression (SC) were scanned in dual-energy mode on a newest generation Dual Energy 64-row MDCT scanner. CT number, spectral graphs, and dual-energy index (DEI) were evaluated. Results were prospectively tested on six original samples from a body packer. Wilcoxon's test was used for statistical evaluation. RESULTS: Values are given as median and range. Under SC, the CT number of cocaine samples (-29.87 Hounsfield unit (HU) [-125.85; 16.16 HU]) was higher than the CT number of heroin samples (-184.37 HU [-199.81; -159.25 HU]; p < 0.01). Slope of spectral curves for cocaine was -2.36 HU/keV [-7.15; -0.67 HU/keV], and for heroin, 1.75 HU/keV [1.28; 2.5 HU/keV] (p < 0.01). DEI was 0.0352 [0.0081; 0.0528] for cocaine and significantly higher than for heroin samples (-0.0127 [-0.0097; -0.0159]; p < 0.001). While CT number was inconclusive, all six original packs were correctly classified after evaluation of the spectral curve and DEI. In contrast to the CT number, slope of the spectral curve and DEI were independent of concentration and compression. CONCLUSION: The slope of the spectral curve and the DEI from dual-energy CT data can be used to distinguish heroin and cocaine in vitro; these results are independent of compression and concentration in the measured range.

Enhanced compressed sensing recovery with level set normals.

We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.

Artificial evolution on network structures : how time and space influence dynamics

Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.

Timing History: The Introduction of Graphical Analysis in 19th Century British Economics

The introduction of time-series graphs into British economics in the 19th century depended on the « timing » of history. This involved reconceptualizing history into events which were both comparable and measurable and standardized by time unit. Yet classical economists in Britain in the early 19th century viewed history as a set of heterogenous and complex events and statistical tables as giving unrelated facts. Both these attitudes had to be broken down before time-series graphs could be brought into use for revealing regularities in economic events by the century's end.