Brain maps, great and small: lessons from comparative studies of primate visual cortical organization

In this paper, we review evidence from comparative studies of primate cortical organization, highlighting recent findings and hypotheses that may help us to understand the rules governing evolutionary changes of the cortical map and the process of formation of areas during development. We argue that clear unequivocal views of cortical areas and their homologies are more likely to emerge for 'core' fields, including the primary sensory areas, which are specified early in development by precise molecular identification steps. In primates, the middle temporal area is probably one of these primordial cortical fields. Areas that form at progressively later stages of development correspond to progressively more recent evolutionary events, their development being less firmly anchored in molecular specification. The certainty with which areal boundaries can be delimited, and likely homologies can be assigned, becomes increasingly blurred in parallel with this evolutionary/developmental sequence. For example, while current concepts for the definition of cortical areas have been vindicated in allowing a clarification of the organization of the New World monkey 'third tier' visual cortex (the third and dorsomedial areas, V3 and DM), our analyses suggest that more flexible mapping criteria may be needed to unravel the organization of higher-order visual association and polysensory areas.

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

Multidimensional analysis of complex networks

Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking. We propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions, space and time. To achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network as a whole. By focusing on space dimension, we characterized spatial alteration in terms of abstraction levels. We proposed a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We verified that statistical indicators depend strongly on the granularity with which a system is described and on the class of networks. We keep fixed the space axes and we isolated the dynamics behind networks evolution process. We detected new instincts that trigger social networks utilization and spread the adoption of novel communities. We formalized this enhanced social network evolution by adopting special nodes (called sirens) that, thanks to their ability to attract new links, were able to construct efficient connection patterns. We simulated the dynamics of the system by considering three well-known growth models. Applying this framework to real and synthetic networks, we showed that the sirens, even when used for a limited time span, effectively shrink the time needed to get a network in mature state. In order to provide a concrete context of our findings, we formalized the cost of setting up such enhancement and provided the best combinations of system's parameters, such as number of sirens, time span of utilization and attractiveness.

Developmental self-construction and -configuration of functional neocortical neuronal networks.

The prenatal development of neural circuits must provide sufficient configuration to support at least a set of core postnatal behaviors. Although knowledge of various genetic and cellular aspects of development is accumulating rapidly, there is less systematic understanding of how these various processes play together in order to construct such functional networks. Here we make some steps toward such understanding by demonstrating through detailed simulations how a competitive co-operative ('winner-take-all', WTA) network architecture can arise by development from a single precursor cell. This precursor is granted a simplified gene regulatory network that directs cell mitosis, differentiation, migration, neurite outgrowth and synaptogenesis. Once initial axonal connection patterns are established, their synaptic weights undergo homeostatic unsupervised learning that is shaped by wave-like input patterns. We demonstrate how this autonomous genetically directed developmental sequence can give rise to self-calibrated WTA networks, and compare our simulation results with biological data.

Caracterización y simulación de arborizaciones dentríticas con redes bayesianas incluyendo variables angulares

El funcionamiento interno del cerebro es todavía hoy en día un misterio, siendo su comprensión uno de los principales desafíos a los que se enfrenta la ciencia moderna. El córtex cerebral es el área del cerebro donde tienen lugar los procesos cerebrales de más alto nivel, cómo la imaginación, el juicio o el pensamiento abstracto. Las neuronas piramidales, un tipo específico de neurona, suponen cerca del 80% de los cerca de los 10.000 millones de que componen el córtex cerebral, haciendo de ellas un objetivo principal en el estudio del funcionamiento del cerebro. La morfología neuronal, y más específicamente la morfología dendrítica, determina cómo estas procesan la información y los patrones de conexión entre neuronas, siendo los modelos computacionales herramientas imprescindibles para el estudio de su rol en el funcionamiento del cerebro. En este trabajo hemos creado un modelo computacional, con más de 50 variables relativas a la morfología dendrítica, capaz de simular el crecimiento de arborizaciones dendríticas basales completas a partir de reconstrucciones de neuronas piramidales reales, abarcando desde el número de dendritas hasta el crecimiento los los árboles dendríticos. A diferencia de los trabajos anteriores, nuestro modelo basado en redes Bayesianas contempla la arborización dendrítica en su conjunto, teniendo en cuenta las interacciones entre dendritas y detectando de forma automática las relaciones entre las variables morfológicas que caracterizan la arborización. Además, el análisis de las redes Bayesianas puede ayudar a identificar relaciones hasta ahora desconocidas entre variables morfológicas. Motivado por el estudio de la orientación de las dendritas basales, en este trabajo se introduce una regularización L1 generalizada, aplicada al aprendizaje de la distribución von Mises multivariante, una de las principales distribuciones de probabilidad direccional multivariante. También se propone una distancia circular multivariante que puede utilizarse para estimar la divergencia de Kullback-Leibler entre dos muestras de datos circulares. Comparamos los modelos con y sin regularizaci ón en el estudio de la orientación de la dendritas basales en neuronas humanas, comprobando que, en general, el modelo regularizado obtiene mejores resultados. El muestreo, ajuste y representación de la distribución von Mises multivariante se implementa en un nuevo paquete de R denominado mvCircular.---ABSTRACT---The inner workings of the brain are, as of today, a mystery. To understand the brain is one of the main challenges faced by current science. The cerebral cortex is the region of the brain where all superior brain processes, like imagination, judge and abstract reasoning take place. Pyramidal neurons, a specific type of neurons, constitute approximately the 80% of the more than 10.000 million neurons that compound the cerebral cortex. It makes the study of the pyramidal neurons crucial in order to understand how the brain works. Neuron morphology, and specifically the dendritic morphology, determines how the information is processed in the neurons, as well as the connection patterns among neurons. Computational models are one of the main tools for studying dendritic morphology and its role in the brain function. We have built a computational model that contains more than 50 morphological variables of the dendritic arborizations. This model is able to simulate the growth of complete dendritic arborizations from real neuron reconstructions, starting with the number of basal dendrites, and ending modeling the growth of dendritic trees. One of the main diferences between our approach, mainly based on the use of Bayesian networks, and other models in the state of the art is that we model the whole dendritic arborization instead of focusing on individual trees, which makes us able to take into account the interactions between dendrites and to automatically detect relationships between the morphologic variables that characterize the arborization. Moreover, the posterior analysis of the relationships in the model can help to identify new relations between morphological variables. Motivated by the study of the basal dendrites orientation, a generalized L1 regularization applied to the multivariate von Mises distribution, one of the most used distributions in multivariate directional statistics, is also introduced in this work. We also propose a circular multivariate distance that can be used to estimate the Kullback-Leibler divergence between two circular data samples. We compare the regularized and unregularized models on basal dendrites orientation of human neurons and prove that regularized model achieves better results than non regularized von Mises model. Sampling, fitting and plotting functions for the multivariate von Mises are implemented in a new R packaged called mvCircular.

Centralized vs. Distributed Connection Management Schemes under Different Traffic Patterns in Wavelength-Convertible Optical Networks

Centralized and Distributed methods are two connection management schemes in wavelength convertible optical networks. In the earlier work, the centralized scheme is said to have lower network blocking probability than the distributed one. Hence, much of the previous work in connection management has focused on the comparison of different algorithms in only distributed scheme or in only centralized scheme. However, we believe that the network blocking probability of these two connection management schemes depends, to a great extent, on the network traffic patterns and reservation times. Our simulation results reveal that the performance improvement (in terms of blocking probability) of centralized method over distributed method is inversely proportional to the ratio of average connection interarrival time to reservation time. After that ratio increases beyond a threshold, those two connection management schemes yield almost the same blocking probability under the same network load. In this paper, we review the working procedure of distributed and centralized schemes, discuss the tradeoff between them, compare these two methods under different network traffic patterns via simulation and give our conclusion based on the simulation data.

Interface HL7 para observation patterns

Com a generalização das tecnologias de informação e comunicação na área da saúde, a monitorização remota de pacientes, a partir de dispositivos móveis, é uma realidade que contribui para uma melhor qualidade de vida dos pacientes. Mas, não são só os pacientes que ganham com a introdução destas tecnologias, também os profissionais de saúde e os hospitais retiram as suas vantagens. Os profissionais de saúde são munidos de uma ferramenta móvel de monitorização permanente de sinais vitais, aumentando desta forma a ligação médico-paciente. Relativamente aos hospitais, estes vêem os custos de manutenção reduzirem, em virtude da possibilidade dos pacientes puderem ser monitorizados a partir dos seus lares. Neste projecto pretende-se identificar mecanismos que possibilitem responder de forma eficaz à necessidade de partilha de informação, nomeadamente protocolos de comunicação, segurança e sistemas de integração. Foi projectado um protótipo, constituído por um middleware e uma aplicação cliente móvel, onde o middleware tem como missão garantir a interoperabilidade entre um servidor HL7 e a aplicação cliente, utilizada pelo profissional de saúde. A normalização da informação médica trocada entre o servidor HL7 e o middleware obedece à norma internacional HL7.

The multipoint Morisita index for the analysis of spatial patterns

In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.

A Sociological Analysis of Contemporary Irish Social Drinking Patterns

This thesis seeks to provide an understanding of contemporary Irish social drinking patterns by conducting a detailed analysis of the evolving sociological theories of alcohol consumption in Ireland. ‘Alcohol is a social drug which, to this day, evokes the divisive moral qualities that originated, or at least were solidified, in the last century with the birth of temperance movements’ (Cassidy, 1997:175). The temperance movement in Ireland under Father Mathew, a legacy which still reverberates in Irish society, served to further ingrain the ‘image of the whisky drinking Irishman’ (Ibid: 17). This is seen in such work as Stivers (1976) who uses sociological labelling theory to provide verification of a deviant Irish status, biologically, socially and culturally predisposed to alcohol. The author argues that these temperance movements sought to remove the linkages of alcohol and “Irishness” but this quasi-stigmatisation process created a “self-fulfilling prophecy”, which further abetted the legitimisation of alcohol within cultural spheres. The tourism industry, in connection with drink manufacturers, has had a monumental role in alcohol’s contemporary position within the upper echelons of Irish culture and heritage. Their hand in the commodification of “Stage Irishy”, seen as “craic”, has further entrenched the links between consumption of alcohol and the consumption of Irish Identity “McGovern, 2002). Furthermore, commercial interests are keen to cash in and maintain the dominance of alcohol in Irish society. This thesis concludes that this factor, in connection with the accelerated modernisation that Ireland has experienced since the mid-nineties, has malleable consequences for Irish society. As Keohane and Kuhling (2007) assert, post-modern consumption patterns of excess and ‘insatiability’ have been introduced into contemporary Irish drinking patterns and are affecting the nature of alcohol consumption in Ireland.This resource was contributed by The National Documentation Centre on Drug Use.

Phlebotominae (Diptera: Psycodidae) fauna in the Chaco region and Cutaneous Leishmaniasis transmission patterns in Argentina

In Argentina, the incidence of American Cutaneous Leishmaniasis (ACL) has shown a steady increase over the last few decades. In the Chaco biogeographical region, specifically, several outbreaks of ACL were recently reported in addition to the usual time-space scattering of ACL cases. However, little is known about the sandfly composition in the eastern, humid Chaco (HC) region or the western, dry Chaco (DC) region. Therefore, phlebotomine captures were performed throughout this region and an analysis of the distribution of reported ACL cases was conducted in order to assess the vector diversity in ACL endemic and epidemic scenarios in the Chaco region. The results support the hypothesis of two distinct patterns: (1) the DC, where Lutzomyia migonei was the most prevalent species, had isolated ACL cases and a zoonotic cycle; (2) the HC, where Lutzomyia neivai was the most prevalent species, had an increase in ACL incidence and outbreaks and an anthropozoonotic cycle. The epidemic risk in the Chaco region may be associated with the current climate trends, landscape modification, connection with other ACL foci, and Lu. neivai predominance and abundance. Therefore, changes in sandfly population diversity and density in the Chaco region are an indicator of emergent epidemic risk in sentinel capture sites.

Turnover and accumulation of genetic diversity across large time-scale cycles of isolation and connection of populations.

Major climatic and geological events but also population history (secondary contacts) have generated cycles of population isolation and connection of long and short periods. Recent empirical and theoretical studies suggest that fast evolutionary processes might be triggered by such events, as commonly illustrated in ecology by the adaptive radiation of cichlid fishes (isolation and reconnection of lakes and watersheds) and in epidemiology by the fast adaptation of the influenza virus (isolation and reconnection in hosts). We test whether cyclic population isolation and connection provide the raw material (standing genetic variation) for species evolution and diversification. Our analytical results demonstrate that population isolation and connection can provide, to populations, a high excess of genetic diversity compared with what is expected at equilibrium. This excess is either cyclic (high allele turnover) or cumulates with time depending on the duration of the isolation and the connection periods and the mutation rate. We show that diversification rates of animal clades are associated with specific periods of climatic cycles in the Quaternary. We finally discuss the importance of our results for macroevolutionary patterns and for the inference of population history from genomic data.

Violent Video Game Playing, Moral Reasoning, and Attitudes Towards Violence in Adolescents: Is There a Connection?

In this study of 109 adolescents from the eighth grade of seven public elementary schools in Ontario, the relationship among adolescents’ violent video game playing patterns, habits and attitudes, their levels of moral reasoning, and their attitudes towards violence in real life was investigated. In addition, gender differences were addressed. The mixed-methodology was employed combining qualitative and quantitative data. The research results confirmed that playing video games in general is a very popular activity among those adolescents. Significant negative relationship was found between adolescents’ amount of time playing violent video games during the day and their scores on The Sociomoral Reflection Measure. Significant difference was also found between adolescents who play violent video games and those who do not play violent video games on their scores on The Attitudes Towards Violence Scale. Boys and girls significantly differed in the amount of playing video games during the day, the reasons for playing video games, their favourite video game choices, and their favourite video game character choices. Boys and girls also significantly differed on their choices of personality traits of selected video game characters, the identification with video game characters, and their mood experiences while playing video games. The findings are put into the educational context and the context of normal development, and suggestions are given for parents, for educators, and for future violent video game research.

Ecological modeling and pest population management: a possible and necessary connection in a changing world

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Population, social equity and changing production patterns

Includes bibliography