909 resultados para migratory connectivity


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Brain functioning relies on the interaction of several neural populations connected through complex connectivity networks, enabling the transmission and integration of information. Recent advances in neuroimaging techniques, such as electroencephalography (EEG), have deepened our understanding of the reciprocal roles played by brain regions during cognitive processes. The underlying idea of this PhD research is that EEG-related functional connectivity (FC) changes in the brain may incorporate important neuromarkers of behavior and cognition, as well as brain disorders, even at subclinical levels. However, a complete understanding of the reliability of the wide range of existing connectivity estimation techniques is still lacking. The first part of this work addresses this limitation by employing Neural Mass Models (NMMs), which simulate EEG activity and offer a unique tool to study interconnected networks of brain regions in controlled conditions. NMMs were employed to test FC estimators like Transfer Entropy and Granger Causality in linear and nonlinear conditions. Results revealed that connectivity estimates reflect information transmission between brain regions, a quantity that can be significantly different from the connectivity strength, and that Granger causality outperforms the other estimators. A second objective of this thesis was to assess brain connectivity and network changes on EEG data reconstructed at the cortical level. Functional brain connectivity has been estimated through Granger Causality, in both temporal and spectral domains, with the following goals: a) detect task-dependent functional connectivity network changes, focusing on internal-external attention competition and fear conditioning and reversal; b) identify resting-state network alterations in a subclinical population with high autistic traits. Connectivity-based neuromarkers, compared to the canonical EEG analysis, can provide deeper insights into brain mechanisms and may drive future diagnostic methods and therapeutic interventions. However, further methodological studies are required to fully understand the accuracy and information captured by FC estimates, especially concerning nonlinear phenomena.

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In this work, a prospective study conducted at the IRCCS Istituto delle Scienze Neurologiche di Bologna is presented. The aim was to investigate the brain functional connectivity of a cohort of patients (N=23) suffering from persistent olfactory dysfunction after SARS-CoV-2 infection (Post-COVID-19 syndrome), as compared to a matching group of healthy controls (N=26). In particular, starting from individual resting state functional-MRI data, different analytical approaches were adopted in order to find potential alterations in the connectivity patterns of patients’ brains. Analyses were conducted both at a whole-brain level and with a special focus on brain regions involved in the processing of olfactory stimuli (Olfactory Network). Statistical correlations between functional connectivity alterations and the results of olfactory and neuropsychological tests were investigated, to explore the associations with cognitive processes. The three approaches implemented for the analysis were the seed-based correlation analysis, the group-level Independent Component analysis and a graph-theoretical analysis of brain connectivity. Due to the relative novelty of such approaches, many implementation details and methodologies are not standardized yet and represent active research fields. Seed-based and group-ICA analyses’ results showed no statistically significant differences between groups, while relevant alterations emerged from those of the graph-based analysis. In particular, patients’ olfactory sub-graph appeared to have a less pronounced modular structure compared to the control group; locally, a hyper-connectivity of the right thalamus was observed in patients, with significant involvement of the right insula and hippocampus. Results of an exploratory correlation analysis showed a positive correlation between the graphs global modularity and the scores obtained in olfactory tests and negative correlations between the thalamus hyper-connectivity and memory tests scores.

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Multi-element analyses of sediment samples from the Santos-Cubatão Estuarine System were carried out to investigate the spatial and seasonal variability of trace-element concentrations. The study area contains a rich mangrove ecosystem that is a habitat for tens of thousands of resident and migratory birds, some of them endangered globally. Enrichments of metals in fine-grained surface sediments are, in decreasing order, Hg, Mn, La, Ca, Sr, Cd, Zn, Pb, Ba, Cu, Cr, Fe, Nb, Y, Ni and Ga, relative to pre-industrial background levels. The maximum enrichment ranged from 49 (Hg) to 3.1 (Ga). Mercury concentrations were greater in the Cubatão river than in other sites, while the other elements showed greater concentrations in the Morrão river. Concentrations of Mn were significantly greater in winter and autumn than in summer and spring. However, other elements (e.g. Cd and Pb) showed the opposite, with greater concentrations in summer and spring. This study suggests that seasonal changes in physical and chemical conditions may affect the degree of sediment enrichment and therefore make the assessment of contamination difficult. Consequently, these processes need to be considered when assessing water quality and the potential contamination of biota.

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Universidade Estadual de Campinas. Faculdade de Educação Física

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Os ecossistemas florestais do Brasil abrigam um dos mais altos níveis de diversidade de mamíferos da Terra, e boa parte dessa diversidade se encontra nas áreas legalmente protegidas em áreas de domínio privado. As reservas legais (RLs) e áreas de proteção permanente (APPs) representam estratégias importantes para a proteção e manutenção dessa diversidade. Mudanças propostas no Código Florestal certamente trarão efeitos irreversíveis para a diversidade de mamíferos no Brasil. Os mamíferos apresentam papéis-chave nos ecossistemas, atuando como polinizadores e dispersores de sementes. A extinção local de algumas espécies pode reduzir os serviços ecológicos nas RLs e APPs. Outra consequência grave da redução de áreas de vegetação nativa caso a mudança no Código Florestal seja aprovada será o aumento no risco de transmição de doenças, trazendo sério problemas a saúde pública no Brasil.

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The Paraná-Paraguay basin encompasses central western Brazil, northeastern Paraguay, eastern Bolivia and northern Argentina. The Pantanal is a flooded plain with marked dry and rainy seasons that, due to its soil characteristics and low declivity, has a great water holding capacity supporting abundant fish fauna. Piaractus mesopotamicus, or pacu, endemic of the Paraná-Paraguay basin, is a migratory species economically important in fisheries and ecologically as a potential seed disperser. In this paper we employ eight microsatellite loci to assess the population structure of 120 pacu sampled inside and outside the Pantanal of Mato Grosso. Our main objective was to test the null hypothesis of panmixia and to verify if there was a different structuring pattern between the Pantanal were there were no physical barriers to fish movement and the heavily impounded Paraná and Paranapanema rivers. All loci had moderate to high levels of polymorphism, the number of alleles varied from three to 18. The average observed heterozygosity varied from 0.068 to 0.911. After the Bonferroni correction three loci remained significant for deviations from Hardy-Weinberg, and for those the frequency of null alleles was estimated. F ST and R ST pairwise comparisons detected low divergence among sampling sites, and differentiation was significant only between Paranapanema and Cuiabá and Paranapanema and Taquari. No correlation between genetic distance and the natural logarithm of the geographic distance was detected. Results indicate that for conservation purposes and for restoration programs small genetic differences detected in the Cuiabá and Paranapanema rivers should be taken in consideration.

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Many species in the genus Sporophila are migratory. Migration patterns, while poorly studied, may be influenced by seed production which can be very seasonal in some regions. The distribution of S. bouvreuil extends from the Amazon and Suriname south through a large part of the open regions of Brazil. Sporophila pileata, on the other hand, is found in southeastern and southern Brazil as well as Argentina and Paraguay. Both of these species migrate, but their movement patterns are poorly known. To better understand the geographical and the seasonal distributions of S. bouvreuil and S. pileata, we grouped the records into two categories: the breeding season (September to March) and the putative migration season (April to August). We found two areas of sympatry between S. bouvreuil and S. pileata in the Brazilian states of Minas Gerais and São Paulo. For S. bouvreuil we suggest that populations that breed in the Amazon migrate to the Cerrado or Caatinga, where they will encounter resident populations of the same species. These resident populations may take part in short distance migrations. Sporophila pileata, on the other hand, occur in the Cerrado and open areas within the Atlantic Forest and it is not yet possible to determine migratory tendencies or destinations in the non-breeding season.

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Background: Various neuroimaging studies, both structural and functional, have provided support for the proposal that a distributed brain network is likely to be the neural basis of intelligence. The theory of Distributed Intelligent Processing Systems (DIPS), first developed in the field of Artificial Intelligence, was proposed to adequately model distributed neural intelligent processing. In addition, the neural efficiency hypothesis suggests that individuals with higher intelligence display more focused cortical activation during cognitive performance, resulting in lower total brain activation when compared with individuals who have lower intelligence. This may be understood as a property of the DIPS. Methodology and Principal Findings: In our study, a new EEG brain mapping technique, based on the neural efficiency hypothesis and the notion of the brain as a Distributed Intelligence Processing System, was used to investigate the correlations between IQ evaluated with WAIS (Whechsler Adult Intelligence Scale) and WISC (Wechsler Intelligence Scale for Children), and the brain activity associated with visual and verbal processing, in order to test the validity of a distributed neural basis for intelligence. Conclusion: The present results support these claims and the neural efficiency hypothesis.

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Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.

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Ecological systems are vulnerable to irreversible change when key system properties are pushed over thresholds, resulting in the loss of resilience and the precipitation of a regime shift. Perhaps the most important of such properties in human-modified landscapes is the total amount of remnant native vegetation. In a seminal study Andren proposed the existence of a fragmentation threshold in the total amount of remnant vegetation, below which landscape-scale connectivity is eroded and local species richness and abundance become dependent on patch size. Despite the fact that species patch-area effects have been a mainstay of conservation science there has yet to be a robust empirical evaluation of this hypothesis. Here we present and test a new conceptual model describing the mechanisms and consequences of biodiversity change in fragmented landscapes, identifying the fragmentation threshold as a first step in a positive feedback mechanism that has the capacity to impair ecological resilience, and drive a regime shift in biodiversity. The model considers that local extinction risk is defined by patch size, and immigration rates by landscape vegetation cover, and that the recovery from local species losses depends upon the landscape species pool. Using a unique dataset on the distribution of non-volant small mammals across replicate landscapes in the Atlantic forest of Brazil, we found strong evidence for our model predictions - that patch-area effects are evident only at intermediate levels of total forest cover, where landscape diversity is still high and opportunities for enhancing biodiversity through local management are greatest. Furthermore, high levels of forest loss can push native biota through an extinction filter, and result in the abrupt, landscape-wide loss of forest-specialist taxa, ecological resilience and management effectiveness. The proposed model links hitherto distinct theoretical approaches within a single framework, providing a powerful tool for analysing the potential effectiveness of management interventions.

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A great part of the interest in complex networks has been motivated by the presence of structured, frequently nonuniform, connectivity. Because diverse connectivity patterns tend to result in distinct network dynamics, and also because they provide the means to identify and classify several types of complex network, it becomes important to obtain meaningful measurements of the local network topology. In addition to traditional features such as the node degree, clustering coefficient, and shortest path, motifs have been introduced in the literature in order to provide complementary descriptions of the network connectivity. The current work proposes a different type of motif, namely, chains of nodes, that is, sequences of connected nodes with degree 2. These chains have been subdivided into cords, tails, rings, and handles, depending on the type of their extremities (e.g., open or connected). A theoretical analysis of the density of such motifs in random and scale-free networks is described, and an algorithm for identifying these motifs in general networks is presented. The potential of considering chains for network characterization has been illustrated with respect to five categories of real-world networks including 16 cases. Several interesting findings were obtained, including the fact that several chains were observed in real-world networks, especially the world wide web, books, and the power grid. The possibility of chains resulting from incompletely sampled networks is also investigated.

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Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

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Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.

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Using nine microsatellite loci, we investigated genetic structure and diversity in 83 Brazilian cassava accessions, including several landraces, in the Cerrado biome in Mato Grosso do Sul, Brazil. All nine loci were polymorphic, averaging 6.00 alleles per locus. Treating each of seven municipalities as a cassava group or population, they averaged 3.5 alleles per locus, with 97% polymorphic loci, high values for observed heterozygosity (0.32) and gene diversity (0.56). Total genetic variability was high (0.668), and most of this genetic variability was concentrated within municipalities (0.577). Cluster and structure analyses divided accessions into two major clusters or populations (K = 2). Also, a significant genetic versus geographic correlation was found (r = 0.4567; P < 0.0260). Migratory routes in the Cerrado are considered main contributors to the region`s high cassava diversity and spatial genetic structure, amplifying interactions between traditional farmers and the evolutionary dynamics of this crop.

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MgB(2) is considered to be an important conductor for applications. Optimizing flux pinning in these conductors can improve their critical currents. Doping can influence flux pinning efficiency and grain connectivity, and also affect the resistivity, upper critical field and critical temperature. This study was designed to attempt the doping of MgB(2) on the Mg sites with metal-diborides using high-energy ball milling. MgB(2) samples were prepared by milling pre-reacted MgB(2) and TaB(2) powders using a Spex 8000M mill with WC jars and balls in a nitrogen-filled glove box. The mixing concentration in (Mg(1-x)Ta(x))B(2) was up to x = 0.10. Samples were removed from the WC jars after milling times up to 4000 minutes and formed into pellets using cold isostatic pressing. The pellets were heat treated in a hot isostatic press (HIP) at 1000 degrees C under a pressure of 30 kpsi for 24 hours. The influence that milling time and TaB(2) addition had on the microstructure and the resulting superconducting properties of TaB(2)-added MgB(2) is discussed. Improvement J(c) of at high magnetic fields and of pinning could be obtained in milled samples with added TaB(2) The sample with added 5at.% TaB(2) and milled for 300 minutes showed values of J(c) similar to 7 x 10(5) A/cm(2) and F(p) similar to 14 GN/m(3) at 2T, 4.2 K. The milled and TaB(2)-mixed samples showed higher values of mu(0)H(irr) than the unmilled-unmixed sample.