Functional, clustered, feedforward, and mesoscale brain networks

The brain is a network spanning multiple scales from subcellular to macroscopic. In this thesis I present four projects studying brain networks at different levels of abstraction. The first involves determining a functional connectivity network based on neural spike trains and using a graph theoretical method to cluster groups of neurons into putative cell assemblies. In the second project I model neural networks at a microscopic level. Using diferent clustered wiring schemes, I show that almost identical spatiotemporal activity patterns can be observed, demonstrating that there is a broad neuro-architectural basis to attain structured spatiotemporal dynamics. Remarkably, irrespective of the precise topological mechanism, this behavior can be predicted by examining the spectral properties of the synaptic weight matrix. The third project introduces, via two circuit architectures, a new paradigm for feedforward processing in which inhibitory neurons have the complex and pivotal role in governing information flow in cortical network models. Finally, I analyze axonal projections in sleep deprived mice using data collected as part of the Allen Institute's Mesoscopic Connectivity Atlas. After normalizing for experimental variability, the results indicate there is no single explanatory difference in the mesoscale network between control and sleep deprived mice. Using machine learning techniques, however, animal classification could be done at levels significantly above chance. This reveals that intricate changes in connectivity do occur due to chronic sleep deprivation.

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.

Theoretical aspects of graph models for MANETs

We survey the main theoretical aspects of models for Mobile Ad Hoc Networks (MANETs). We present theoretical characterizations of mobile network structural properties, different dynamic graph models of MANETs, and finally we give detailed summaries of a few selected articles. In particular, we focus on articles dealing with connectivity of mobile networks, and on articles which show that mobility can be used to propagate information between nodes of the network while at the same time maintaining small transmission distances, and thus saving energy.

GLOBAL AND LOCAL REACTIVITY DESCRIPTORS FOR PICLORAM HERBICIDE: A THEORETICAL QUANTUM STUDY

In this work, we studied the reactivity of picloram in the aqueous phase at the B3LYP/6-311++G(2d,2p) and MP2/6-311++G(2d,2p) levels of theory through global and local reactivity descriptors. The results obtained at the MP2 level indicate that the cationic form of picloram exhibits the highest hardness while the anionic form is the most nucleophilic. From the Fukui function values, the most reactive site for electrophilic and free radical attacks are on the nitrogen in the pyridine ring. The more reactive sites for nucleophilic attacks are located on the nitrogen atom of the amide group and on the carbon atoms located at positions 2 and 3 in the pyridine ring.

Probabilistic Atlas Based Segmentation Using Affine Moment Descriptors and Graph-Cuts

We show a procedure for constructing a probabilistic atlas based on affine moment descriptors. It uses a normalization procedure over the labeled atlas. The proposed linear registration is defined by closed-form expressions involving only geometric moments. This procedure applies both to atlas construction as atlas-based segmentation. We model the likelihood term for each voxel and each label using parametric or nonparametric distributions and the prior term is determined by applying the vote-rule. The probabilistic atlas is built with the variability of our linear registration. We have two segmentation strategy: a) it applies the proposed affine registration to bring the target image into the coordinate frame of the atlas or b) the probabilistic atlas is non-rigidly aligning with the target image, where the probabilistic atlas is previously aligned to the target image with our affine registration. Finally, we adopt a graph cut - Bayesian framework for implementing the atlas-based segmentation.

R-matrices and the tensor product graph method

A systematic method for constructing trigonometric R-matrices corresponding to the (multiplicity-free) tensor product of any two affinizable representations of a quantum algebra or superalgebra has been developed by the Brisbane group and its collaborators. This method has been referred to as the Tensor Product Graph Method. Here we describe applications of this method to untwisted and twisted quantum affine superalgebras.

power network concept : a theoretical and empirical approach to strategy in the global network economy

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2014

A game theoretical approach to the algebraic counterpart of the Wagner hierarchy

La hiérarchie de Wagner constitue à ce jour la plus fine classification des langages ω-réguliers. Par ailleurs, l'approche algébrique de la théorie de langages formels montre que ces ensembles ω-réguliers correspondent précisément aux langages reconnaissables par des ω-semigroupes finis pointés. Ce travail s'inscrit dans ce contexte en fournissant une description complète de la contrepartie algébrique de la hiérarchie de Wagner, et ce par le biais de la théorie descriptive des jeux de Wadge. Plus précisément, nous montrons d'abord que le degré de Wagner d'un langage ω-régulier est effectivement un invariant syntaxique. Nous définissons ensuite une relation de réduction entre ω-semigroupes pointés par le biais d'un jeu infini de type Wadge. La collection de ces structures algébriques ordonnée par cette relation apparaît alors comme étant isomorphe à la hiérarchie de Wagner, soit un quasi bon ordre décidable de largeur 2 et de hauteur ω. Nous exposons par la suite une procédure de décidabilité de cette hiérarchie algébrique : on décrit une représentation graphique des ω-semigroupes finis pointés, puis un algorithme sur ces structures graphiques qui calcule le degré de Wagner de n'importe quel élément. Ainsi le degré de Wagner de tout langage ω-régulier peut être calculé de manière effective directement sur son image syntaxique. Nous montrons ensuite comment construire directement et inductivement une structure de n''importe quel degré. Nous terminons par une description détaillée des invariants algébriques qui caractérisent tous les degrés de cette hiérarchie. Abstract The Wagner hierarchy is known so far to be the most refined topological classification of ω-rational languages. Also, the algebraic study of formal languages shows that these ω-rational sets correspond precisely to the languages recognizable by finite pointed ω-semigroups. Within this framework, we provide a construction of the algebraic counterpart of the Wagner hierarchy. We adopt a hierarchical game approach, by translating the Wadge theory from the ω-rational language to the ω-semigroup context. More precisely, we first show that the Wagner degree is indeed a syntactic invariant. We then define a reduction relation on finite pointed ω-semigroups by means of a Wadge-like infinite two-player game. The collection of these algebraic structures ordered by this reduction is then proven to be isomorphic to the Wagner hierarchy, namely a well-founded and decidable partial ordering of width 2 and height $\omega^\omega$. We also describe a decidability procedure of this hierarchy: we introduce a graph representation of finite pointed ω-semigroups allowing to compute their precise Wagner degrees. The Wagner degree of every ω-rational language can therefore be computed directly on its syntactic image. We then show how to build a finite pointed ω-semigroup of any given Wagner degree. We finally describe the algebraic invariants characterizing every Wagner degree of this hierarchy.

Theoretical study of magnetism, structure and chemical order in transition-metal alloy clusters

Research on transition-metal nanoalloy clusters composed of a few atoms is fascinating by their unusual properties due to the interplay among the structure, chemical order and magnetism. Such nanoalloy clusters, can be used to construct nanometer devices for technological applications by manipulating their remarkable magnetic, chemical and optical properties. Determining the nanoscopic features exhibited by the magnetic alloy clusters signifies the need for a systematic global and local exploration of their potential-energy surface in order to identify all the relevant energetically low-lying magnetic isomers. In this thesis the sampling of the potential-energy surface has been performed by employing the state-of-the-art spin-polarized density-functional theory in combination with graph theory and the basin-hopping global optimization techniques. This combination is vital for a quantitative analysis of the quantum mechanical energetics. The first approach, i.e., spin-polarized density-functional theory together with the graph theory method, is applied to study the Fe$_m$Rh$_n$ and Co$_m$Pd$_n$ clusters having $N = m+n \leq 8$ atoms. We carried out a thorough and systematic sampling of the potential-energy surface by taking into account all possible initial cluster topologies, all different distributions of the two kinds of atoms within the cluster, the entire concentration range between the pure limits, and different initial magnetic configurations such as ferro- and anti-ferromagnetic coupling. The remarkable magnetic properties shown by FeRh and CoPd nanoclusters are attributed to the extremely reduced coordination number together with the charge transfer from 3$d$ to 4$d$ elements. The second approach, i.e., spin-polarized density-functional theory together with the basin-hopping method is applied to study the small Fe$_6$, Fe$_3$Rh$_3$ and Rh$_6$ and the larger Fe$_{13}$, Fe$_6$Rh$_7$ and Rh$_{13}$ clusters as illustrative benchmark systems. This method is able to identify the true ground-state structures of Fe$_6$ and Fe$_3$Rh$_3$ which were not obtained by using the first approach. However, both approaches predict a similar cluster for the ground-state of Rh$_6$. Moreover, the computational time taken by this approach is found to be significantly lower than the first approach. The ground-state structure of Fe$_{13}$ cluster is found to be an icosahedral structure, whereas Rh$_{13}$ and Fe$_6$Rh$_7$ isomers relax into cage-like and layered-like structures, respectively. All the clusters display a remarkable variety of structural and magnetic behaviors. It is observed that the isomers having similar shape with small distortion with respect to each other can exhibit quite different magnetic moments. This has been interpreted as a probable artifact of spin-rotational symmetry breaking introduced by the spin-polarized GGA. The possibility of combining the spin-polarized density-functional theory with some other global optimization techniques such as minima-hopping method could be the next step in this direction. This combination is expected to be an ideal sampling approach having the advantage of avoiding efficiently the search over irrelevant regions of the potential energy surface.

The iso-Score Curve Graph. A new tool for competitive bidding

The present work describes a new tool that helps bidders improve their competitive bidding strategies. This new tool consists of an easy-to-use graphical tool that allows the use of more complex decision analysis tools in the field of Competitive Bidding. The graphic tool described here tries to move away from previous bidding models which attempt to describe the result of an auction or a tender process by means of studying each possible bidder with probability density functions. As an illustration, the tool is applied to three practical cases. Theoretical and practical conclusions on the great potential breadth of application of the tool are also presented.

Theoretical Approximations Between Brazilian and Spanish Authors' Production in the Field of Knowledge Organization in the Production of Journals on Information Science in Brazil

This work identifies and analyzes literature about knowledge organization (KO), expressed in scientific journals communication of information science (IS). It performs an exploratory study on the Base de Dados Referencial de Artigos de Periodicos em Ciência da Informacio (BRAPCI, Reference Database of Journal Articles on Information Science) between the years 2000 and 2010. The descriptors relating to "knowledge organization" are used in order to recover and analyze the corresponding articles and to identify descriptors and concepts which integrate the semantic universe related to KO. Through the analysis of content, based on metrical studies, this article gathers and interprets data relating to documents and authors. Through this, it demonstrates the development of this field and its research fronts according to the observed characteristics, as well as noting the transformation indicative in the production of knowledge. The work describes the influences of the Spanish researchers on Brazilian literature in the fields of knowledge and information organization. As a result, it presents the most cited and productive authors, the theoretical currents which support them, and the most significant relationships of the Spanish-Brazilian authors network. Based on the constant key-words analysis in the cited articles, the co-existence of the French conception current and the incipient Spanish influence in Brazil is observed. Through this, it contributes to the comprehension of the thematic range relating to KO, stimulating both criticism and self-criticism, debate and knowledge creation, based on studies that have been developed and institutionalized in academic contexts in Spain and Brazil.

Synthesis, X-ray Crystal Structure and Theoretical Calculations of Antileishmanial Neolignan Analogues

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Synthesis, X-ray crystal structure and theoretical calculations of antileishmanial neolignan analogues

A síntese e a estrutura cristalina por difração de raios-X de dois análogos de neolignanas, 2-(4-clorofenil)-1-feniletanona (20) e 2-[tio(4-clorofenil)]-1-(3,4-dimetoxifenil)propan-1-ona (12) são descritas. O composto 12 apresenta atividade intracelular contra Leishmania donovani e Leishmania amazonensis de amastigotas que causam a leishmaniose tegumentar e visceral. Além disso, a teoria do funcional de densidade (DFT) com o funcional híbrido B3LYP foi empregado para calcular um conjunto de descritores moleculares para dezenove análogos sintéticos de neolignanas com atividades antileishmaniose. Posteriormente, a análise discriminante stepwise foi realizada para investigar possíveis relações entre a estrutura molecular e atividades biológicas. Por meio dessa análise os compostos foram classificados em dois grupos ativos e inativos de acordo com seu grau de atividade biológica, e as propriedades mais importantes foram as cargas de alguns átomos, a afinidade eletrônica e o ClogP.

Theoretical models for the antitrypanosomal activity of thiosemicarbazone derivatives

Thiosemicarbazones are cruzain inhibitors which have been identified as potential antitrypanosomal agents. In this work, several molecular properties were calculated at the density functional theory (DFT)/B3LYP/6-311G* level for a set of 44 thiosemicarbazones. Unsupervised and supervised pattern recognition techniques (hierarchical cluster analysis, principal component analysis, kth-nearest neighbors, and soft independent modeling by class analogy) were used to obtain structureactivity relationship models, which are able to classify unknown compounds according to their activities. The chemometric analyses performed here revealed that 12 descriptors can be considered responsible for the discrimination between high and low activity compounds. Classification models were validated with an external test set, showing that predictive classifications were achieved with the selected variable set. The results obtained here are in good agreement with previous findings from the literature, suggesting that our models can be useful on further investigations on the molecular determinants for the antichagasic activity. (C) 2012 Wiley Periodicals, Inc.