Assessing brain connectivity through electroencephalographic signal processing and modeling analysis

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.

A study of brain functional connectivity and cognitive processes in long COVID-19 patients

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.

Bleeding Complications In Dengue Are Not Associated With Significant Changes In The Modulators Of The Endothelial Barrier.

Bleeding complications in dengue may occur irrespective of the presence of plasma leakage. We compared plasma levels of modulators of the endothelial barrier among three dengue groups: bleedings without plasma leakage, dengue hemorrhagic fever, and non-complicated dengue. The aim was to evaluate whether the presence of subtle alterations in microvascular permeability could be detected in bleeding patients. Plasma levels of VEGF-A and its soluble receptors were not associated with the occurrence of bleeding in patients without plasma leakage. These results provide additional rationale for considering bleeding as a complication independent of endothelial barrier breakdown, as proposed by the 2009 WHO classification.

Vascular Endothelial Growth Factor Increases During Blood-brain Barrier-enhanced Permeability Caused By Phoneutria Nigriventer Spider Venom.

Phoneutria nigriventer spider accidental envenomation provokes neurotoxic manifestations, which when critical, results in epileptic-like episodes. In rats, P. nigriventer venom (PNV) causes blood-brain barrier breakdown (BBBb). The PNV-induced excitotoxicity results from disturbances on Na(+), K(+) and Ca(2+) channels and glutamate handling. The vascular endothelial growth factor (VEGF), beyond its angiogenic effect, also, interferes on synaptic physiology by affecting the same ion channels and protects neurons from excitotoxicity. However, it is unknown whether VEGF expression is altered following PNV envenomation. We found that adult and neonates rats injected with PNV showed immediate neurotoxic manifestations which paralleled with endothelial occludin, β-catenin, and laminin downregulation indicative of BBBb. In neonate rats, VEGF, VEGF mRNA, and Flt-1 receptors, glutamate decarboxylase, and calbindin-D28k increased in Purkinje neurons, while, in adult rats, the BBBb paralleled with VEGF mRNA, Flk-1, and calbindin-D28k increases and Flt-1 decreases. Statistically, the variable age had a role in such differences, which might be due to age-related unequal maturation of blood-brain barrier (BBB) and thus differential cross-signaling among components of the glial neurovascular unit. The concurrent increases in the VEGF/Flt-1/Flk-1 system in the cerebellar neuron cells and the BBBb following PNV exposure might imply a cytokine modulation of neuronal excitability consequent to homeostatic perturbations induced by ion channels-acting PNV neuropeptides. Whether such modulation represents neuroprotection needs further investigation.

Vasopressina e morte encefálica

Brain death results in the breakdown of effective central regulatory mechanisms of cardiocirculatory stability, even in patients with artificial mechanical ventilation, correction of electrolytic and acid-basic disorders and maximal conventional pharmacological support of the circulation. Recent evidences have shown that the fall of vasopressin levels in the blood circulation significantly influences the cardiocirculatory stability of patients with brain death, and its exogenous administration is defended by many authors for the management of multiorgan donor patients. In this brief review we analyse and discuss some experimental and clinical relevant studies about the role of vasopressin in the control of cardiocirculatory stability in brain death, and its potential usefulness in the management of multiorgan donor. We conclude that the role of vasopressin in the pathophysiology of brain death and its usefulness as a pharmacological agent in the management of multiorgan donor are not well elucidated, deserving further investigations.

Mudanças no Código Florestal e seu impacto na ecologia e diversidade dos mamíferos no Brasil

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.

Recovery and upgrading bovine rumen protein by extrusion: effect of lipid content on protein disulphide cross-linking, solubility and molecular weight

Bovine rumen protein with two levels of residual lipids (1.9 per cent or 3.8 per cent) was subjected to thermoplastic extrusion under different temperatures and moisture contents. Protein solubility in different buffers, disulphide cross-linking and molecular weight distribution were determined on the extrudates. After extrusion, samples with 1.9 per cent residual lipids content had a higher concentration of protein insoluble by undetermined forces, irrespective of feed moisture and processing temperature used. Lipid content of 3.8 per cent in the feed material resulted in more protein participating in the extrudate network through non-covalent interactions (hydrophobic and electrostatic) and disulphide bonds. A small dependency of the extrusion process on moisture and temperature and a marked dependency on lipid content, especially phospholipid, was observed, Electrophoresis under non-reducing conditions showed that protein extrusion with low feed moisture promoted high molecular breakdown inside the barrel, probably due to intense shear force, and further protein aggregation at the die end

The Brain as a Distributed Intelligent Processing System: An EEG Study

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.

Integration and visualization of systems biology data in context of the genome

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.

Beyond the Fragmentation Threshold Hypothesis: Regime Shifts in Biodiversity Across Fragmented Landscapes

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.

Chain motifs: The tails and handles of complex networks

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.

Transport properties in nontwist area-preserving maps

Nontwist systems, common in the dynamical descriptions of fluids and plasmas, possess a shearless curve with a concomitant transport barrier that eliminates or reduces chaotic transport, even after its breakdown. In order to investigate the transport properties of nontwist systems, we analyze the barrier escape time and barrier transmissivity for the standard nontwist map, a paradigm of such systems. We interpret the sensitive dependence of these quantities upon map parameters by investigating chaotic orbit stickiness and the associated role played by the dominant crossing of stable and unstable manifolds. (C) 2009 American Institute of Physics. [doi: 10.1063/1.3247349]

Supergraph techniques for D=3, N=1 broken supersymmetric theories

We enlarge the usual D = 3 N = 1 supergraph techniques to include the case of (explicitly or spontaneously) broken supersymmetric gauge theories. To illustrate the utility of these techniques, we calculate the two-loop effective potential of the SQED(3) by using the tadpole and the vacuum bubble methods. In these methods, to investigate the possibility of supersymmetry breaking, the superfields must be shifted by theta(alpha) dependent classical superfields (vacuum expectation values), what implies in the explicit breakdown of supersymmetry in the intermediate steps of the calculation. Nevertheless, after studying the minimum of the resulting effective potential, we find that supersymmetry is conserved, while gauge symmetry is dynamically broken, with a mass generated for the gauge superfield.

Communication structure of cortical networks

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).

Automatic Network Fingerprinting through Single-Node Motifs

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.