971 resultados para Connectivity Patterns


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

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We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes. (C) 2011 Elsevier B.V. All rights reserved.

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Theoretical and empirical studies demonstrate that the total amount of forest and the size and connectivity of fragments have nonlinear effects on species survival. We tested how habitat amount and configuration affect understory bird species richness and abundance. We used mist nets (almost 34,000 net hours) to sample birds in 53 Atlantic Forest fragments in southeastern Brazil. Fragments were distributed among 3 10,800-ha landscapes. The remaining forest in these landscapes was below (10% forest cover), similar to (30%), and above (50%) the theoretical fragmentation threshold (approximately 30%) below which the effects of fragmentation should be intensified. Species-richness estimates were significantly higher (F = 3715, p = 0.00) where 50% of the forest remained, which suggests a species occurrence threshold of 30-50% forest, which is higher than usually occurs (<30%). Relations between forest cover and species richness differed depending on species sensitivity to forest conversion and fragmentation. For less sensitive species, species richness decreased as forest cover increased, whereas for highly sensitive species the opposite occurred. For sensitive species, species richness and the amount of forest cover were positively related, particularly when forest cover was 30-50%. Fragment size and connectivity were related to species richness and abundance in all landscapes, not just below the 30% threshold. Where 10% of the forest remained, fragment size was more related to species richness and abundance than connectivity. However, the relation between connectivity and species richness and abundance was stronger where 30% of the landscape was forested. Where 50% of the landscape was forested, fragment size and connectivity were both related to species richness and abundance. Our results demonstrated a rapid loss of species at relatively high levels of forest cover (30-50%). Highly sensitive species were 3-4 times more common above the 30-50% threshold than below it; however, our results do not support a unique fragmentation threshold.

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Population genetic and phylogeography of two common mediterranean species were studied in 10 localities located on the coasts of Toscana, Puglia and Calabria. The aim of the study was to verify the extent of genetic breaks, in areas recognized as boundaries between Mediterranean biogeographic sectors. From about 100 sequences obtained from the mitochondrial Cytochrome Oxidase subunit I (COI) gene of Halocynthia papillosa and Hexaplex trunculus genetic diversity, genetic structure at small and large distances and demographic history of both specieswere analyzed. No evidences of genetic breaks were found for the two species in Toscana and Puglia. The genetic structure of H. trunculus evidences the extent of a barrier to gene flow localized in Calabria, which could be represented by the Siculo-Tunisian Strait and the Strait of Messina. The observed patterns showed similar level of gene flow at small distances in both species, although the two species have different larval ecology. These results suggest that other factors, such as currents, local dynamics and seasonal temperatures, influence the connectivity along the Italian peninsula. The geographic distribution of the haplotypes shows that H. papillosacould represent a single genetic pool in expansion, whereas H. trunculus has two distinct genetic pools in expansion. The demographic pattern of the two species suggests that Pleistocene sea level oscillations, in particular of the LGM, may have played a key role in shaping genetic structure of the two species. This knowledge provides basic information, useful for the definition of management plans, or for the design of a network of marine protected areas along the Italian peninsula.

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Aim Parrots are thought to have originated on Gondwana during the Cretaceous. The initial split within crown group parrots separated the New Zealand taxa from the remaining extant species and was considered to coincide with the separation of New Zealand from Gondwana 82-85 Ma, assuming that the diversification of parrots was mainly shaped by vicariance. However, the distribution patterns of several extant parrot groups cannot be explained without invoking transoceanic dispersal, challenging this assumption. Here, we present a temporal and spatial framework for the diversification of parrots using external avian fossils as calibration points in order to evaluate the relative importance of the influences of past climate change, plate tectonics and ecological opportunity. Location Australasian, African, Indo-Malayan and Neotropical regions. Methods Phylogenetic relationships were investigated using partial sequences of the nuclear genes c-mos, RAG-1 and Zenk of 75 parrot and 21 other avian taxa. Divergence dates and confidence intervals were estimated using a Bayesian relaxed molecular clock approach. Biogeographic patterns were evaluated taking temporal connectivity between areas into account. We tested whether diversification remained constant over time and if some parrot groups were more species-rich than expected given their age. Results Crown group diversification of parrots started only about 58 Ma, in the Palaeogene, significantly later than previously thought. The Australasian lories and possibly also the Neotropical Arini were found to be unexpectedly species-rich. Diversification rates probably increased around the Eocene/Oligocene boundary and in the middle Miocene, during two periods of major global climatic aberrations characterized by global cooling. Main conclusions The diversification of parrots was shaped by climatic and geological events as well as by key innovations. Initial vicariance events caused by continental break-up were followed by transoceanic dispersal and local radiations. Habitat shifts caused by climate change and mountain orogenesis may have acted as a catalyst to the diversification by providing new ecological opportunities and challenges as well as by causing isolation as a result of habitat fragmentation. The lories constitute the only highly nectarivorous parrot clade, and their diet shift, associated with morphological innovation, may have acted as an evolutionary key innovation, allowing them to explore underutilized niches and promoting their diversification.

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We present an overview of different methods for decomposing a multichannel spontaneous electroencephalogram (EEG) into sets of temporal patterns and topographic distributions. All of the methods presented here consider the scalp electric field as the basic analysis entity in space. In time, the resolution of the methods is between milliseconds (time-domain analysis), subseconds (time- and frequency-domain analysis) and seconds (frequency-domain analysis). For any of these methods, we show that large parts of the data can be explained by a small number of topographic distributions. Physically, this implies that the brain regions that generated one of those topographies must have been active with a common phase. If several brain regions are producing EEG signals at the same time and frequency, they have a strong tendency to do this in a synchronized mode. This view is illustrated by several examples (including combined EEG and functional magnetic resonance imaging (fMRI)) and a selective review of the literature. The findings are discussed in terms of short-lasting binding between different brain regions through synchronized oscillations, which could constitute a mechanism to form transient, functional neurocognitive networks.

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Cerebral electrical activity is highly nonstationary because the brain reacts to ever changing external stimuli and continuously monitors internal control circuits. However, a large amount of energy is spent to maintain remarkably stationary activity patterns and functional inter-relations between different brain regions. Here we examine linear EEG correlations in the peri-ictal transition of focal onset seizures, which are typically understood to be manifestations of dramatically changing inter-relations. Contrary to expectations we find stable correlation patterns with a high similarity across different patients and different frequency bands. This skeleton of spatial correlations may be interpreted as a signature of standing waves of electrical brain activity constituting a dynamical ground state. Such a state could promote the formation of spatiotemporal neuronal assemblies and may be important for the integration of information stemming from different local circuits of the functional brain network.

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Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.

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Studying individual differences in conscious awareness can potentially lend fundamental insights into the neural bases of binding mechanisms and consciousness (Cohen Kadosh and Henik, 2007). Partly for this reason, considerable attention has been devoted to the neural mechanisms underlying grapheme–color synesthesia, a healthy condition involving atypical brain activation and the concurrent experience of color photisms in response to letters, numbers, and words. For instance, the letter C printed in black on a white background may elicit a yellow color photism that is perceived to be spatially colocalized with the inducing stimulus or internally in the “mind's eye” as, for instance, a visual image. Synesthetic experiences are involuntary, idiosyncratic, and consistent over time (Rouw et al., 2011). To date, neuroimaging research on synesthesia has focused on brain areas activated during the experience of synesthesia and associated structural brain differences. However, activity patterns of the synesthetic brain at rest remain largely unexplored. Moreover, the neural correlates of synesthetic consistency, the hallmark characteristic of synesthesia, remain elusive.

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PURPOSE To assess possible effects of working memory (WM) training on cognitive functionality, functional MRI and brain connectivity in patients with juvenile MS. METHODS Cognitive status, fMRI and inter-network connectivity were assessed in 5 cases with juvenile MS aged between 12 and 18 years. Afterwards they received a computerized WM training for four weeks. Primary cognitive outcome measures were WM (visual and verbal) and alertness. Activation patterns related to WM were assessed during fMRI using an N-Back task with increasing difficulty. Inter-network connectivity analyses were focused on fronto-parietal (left and right), default-mode (dorsal and ventral) and the anterior salience network. Cognitive functioning, fMRI and inter-network connectivity were reassessed directly after the training and again nine months following training. RESULTS Response to treatment was seen in two patients. These patients showed increased performance in WM and alertness after the training. These behavioural changes were accompanied by increased WM network activation and systematic changes in inter-network connectivity. The remaining participants were non-responders to treatment. Effects on cognitive performance were maintained up to nine months after training, whereas effects observed by fMRI disappeared. CONCLUSIONS Responders revealed training effects on all applied outcome measures. Disease activity and general intelligence may be factors associated with response to treatment.

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The retina is a specialized neuronal structure that transforms the optical image into electrical signals which are transmitted to the brain via the optic nerve. As part of the strategy to cover a stimulus range as broad as 10 log units, from dim starlight to bright sunlight, retinal circuits are broadly divided into rod and cone pathways, responsible for dark and light-adapted vision, respectively. ^ In this dissertation, confocal microscopy and immunocytochemical methods were combined to study the synaptic connectivity of the rod pathway from the level of individual synapses to whole populations of neurons. The study was focused on synaptic interactions at the rod bipolar terminal. The purpose is to understand the synaptic structure of the dyad synapse made by rod bipolar terminals, including the synaptic components and connections, and their physiological functions in the rod pathway. In addition, some additional components and connections of the rod pathway were also studied in these experiments. The major results can be summarized as following: At the dyad synapse of rod bipolar terminals, three postsynaptic components—processes of All amacrine cells and the varicosities of S1 or S2 amacrine cells express different glutamate receptor subunits, which may underlie the functional diversity of these postsynaptic neurons. A reciprocal feedback system is formed by rod bipolar terminals and S1/S2 amacrine cells. Analysis showed these two wide-field GABA amacrine cells have stereotyped synaptic connections with the appropriate morphology and distribution to perform specific functions. In addition, S1 and S2 cells have different coupling patterns and, in general, there is no coupling between the two types. Besides the classic rod pathway though rod bipolar cells and All amacrine cells, the finding of direct connections between certain types of OFF cone bipolar cells and rods indicates the presence of an alternative rod pathway in the rabbit retina. ^ In summary, this dissertation presents a detailed view of the connection and receptors at rod bipolar terminals. Based on the morphology, distribution and coupling, different functional roles were identified for S1 and S2 amacrine cells. Finally, an alternative to the classic rod pathway was found in the rabbit retina. ^

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The structural connectivity of the brain is considered to encode species-wise and subject-wise patterns that will unlock large areas of understanding of the human brain. Currently, diffusion MRI of the living brain enables to map the microstructure of tissue, allowing to track the pathways of fiber bundles connecting the cortical regions across the brain. These bundles are summarized in a network representation called connectome that is analyzed using graph theory. The extraction of the connectome from diffusion MRI requires a large processing flow including image enhancement, reconstruction, segmentation, registration, diffusion tracking, etc. Although a concerted effort has been devoted to the definition of standard pipelines for the connectome extraction, it is still crucial to define quality assessment protocols of these workflows. The definition of quality control protocols is hindered by the complexity of the pipelines under test and the absolute lack of gold-standards for diffusion MRI data. Here we characterize the impact on structural connectivity workflows of the geometrical deformation typically shown by diffusion MRI data due to the inhomogeneity of magnetic susceptibility across the imaged object. We propose an evaluation framework to compare the existing methodologies to correct for these artifacts including whole-brain realistic phantoms. Additionally, we design and implement an image segmentation and registration method to avoid performing the correction task and to enable processing in the native space of diffusion data. We release PySDCev, an evaluation framework for the quality control of connectivity pipelines, specialized in the study of susceptibility-derived distortions. In this context, we propose Diffantom, a whole-brain phantom that provides a solution to the lack of gold-standard data. The three correction methodologies under comparison performed reasonably, and it is difficult to determine which method is more advisable. We demonstrate that susceptibility-derived correction is necessary to increase the sensitivity of connectivity pipelines, at the cost of specificity. Finally, with the registration and segmentation tool called regseg we demonstrate how the problem of susceptibility-derived distortion can be overcome allowing data to be used in their original coordinates. This is crucial to increase the sensitivity of the whole pipeline without any loss in specificity.

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Understanding flow path connectivity within a geothermal reservoir is a critical component for efficiently producing sustained flow rates of hot fluids from the subsurface. I present a new approach for characterizing subsurface fracture connectivity that combines petrographic and cold cathodoluminescence (CL) microscopy with stable isotope analysis (δ18O and δ13C) and clumped isotope (Δ47) thermometry of fracture-filling calcite cements from a geothermal reservoir in northern Nevada. Calcite cement samples were derived from both drill cuttings and core samples taken at various depths from wells within the geothermal field. CL microscopy of some fracture filling cements shows banding parallel to the fracture walls as well as brecciation, indicating that the cements are related to fracture opening and fault slip. Variations in trace element composition indicated by the luminescence patterns reflect variations in the composition and source of fluids moving through the fractures as they opened episodically. Calcite δ13C and δ18O results also show significant variation among the sampled cements, reflecting multiple generations of fluids and fracture connectivity. Clumped isotope analyses performed on a subset of the cements analyzed for conventional δ18O and δ13C mostly show calcite growth temperatures around 150°C—above the current ambient rock temperature, which indicates a common temperature trend for the geothermal reservoir. However, calcite cements sampled along faults located within the well field showed both cold (18.7°C) and hot (226.1°C) temperatures. The anomalously cool temperature found along the fault, using estimates from clumped isotope thermometry, suggests a possible connection to surface waters for the geothermal source fluids for this system. This information may indicate that some of the faults within the well field are transporting meteoric water from the surface to be heated at depth, which then is circulated through a complex network of fractures and other faults.

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Autism is a developmental disorder that is currently defined in terms of a triad of impairments in social interaction, communication, and behavioural flexibility. Psychological models have focussed on deficits in high level social and cognitive processes, such as ‘weak central coherence’ and deficits in ‘theory of mind’. Converging evidence from different fields of neuroscience research indicates that the underlying neural dysfunction is associated with atypical patterns of cortical connectivity (Rippon et al., 2007). This arises very early in development and results in sensory, perceptual and cognitive deficits at a much earlier and more fundamental level than previously suggested, but with cascading effects on higher level psychological and social processes. Earlier research in this sphere has focussed mainly on patterns of underconnectivity in distributed cortical networks underpinning process such as language and executive function. (Just et al., 2007). Such research mainly utilises imaging techniques with high spatial resolution. This paper focuses on evidence associated with local over-connectivity, evident in more low level and transitory processes and hence more easily measurable with techniques with high temporal resolution, such as MEG and EEG. Results are described which provide evidence of such local over-connectivity, characterised by atypical results in the gamma frequency range (Brown et al., 2005) together with discussions about the future directions of such research and its implications for remediation.

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Despite the increasing body of evidence supporting the hypothesis of schizophrenia as a disconnection syndrome, studies of resting-state EEG Source Functional Connectivity (EEG-SFC) in people affected by schizophrenia are sparse. The aim of the present study was to investigate resting-state EEG-SFC in 77 stable, medicated patients with schizophrenia (SCZ) compared to 78 healthy volunteers (HV). In order to study the effect of illness duration, SCZ were divided in those with a short duration of disease (SDD; n = 25) and those with a long duration of disease (LDD; n = 52). Resting-state EEG recordings in eyes closed condition were analyzed and lagged phase synchronization (LPS) indices were calculated for each ROI pair in the source-space EEG data. In delta and theta bands, SCZ had greater EEG-SFC than HV; a higher theta band connectivity in frontal regions was observed in LDD compared with SDD. In the alpha band, SCZ showed lower frontal EEG-SFC compared with HV whereas no differences were found between LDD and SDD. In the beta1 band, SCZ had greater EEG-SFC compared with HVs and in the beta2 band, LDD presented lower frontal and parieto-temporal EEG-SFC compared with HV. In the gamma band, SDD had greater connectivity values compared with LDD and HV. This study suggests that resting state brain network connectivity is abnormally organized in schizophrenia, with different patterns for the different EEG frequency components and that EEG can be a powerful tool to further elucidate the complexity of such disordered connectivity.