Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.

Brief Announcement: Node Sampling Using Centrifugal Random Walks.

We propose distributed algorithms for sampling networks based on a new class of random walks that we call Centrifugal Random Walks (CRW). A CRW is a random walk that starts at a source and always moves away from it. We propose CRW algorithms for connected networks with arbitrary probability distributions, and for grids and networks with regular concentric connectivity with distance based distributions. All CRW sampling algorithms select a node with the exact probability distribution, do not need warm-up, and end in a number of hops bounded by the network diameter.

Aplicación de la teoría de redes complejas a procesos dinámicos en la sociedad

Podemos definir la sociedad como un sistema complejo que emerge de la cooperación y coordinación de billones de individuos y centenares de países. En este sentido no vivimos en una isla sino que estamos integrados en redes sociales que influyen en nuestro comportamiento. En esta tesis doctoral, presentamos un modelo analítico y una serie de estudios empíricos en los que analizamos distintos procesos sociales dinámicos desde una perspectiva de la teoría de redes complejas. En primer lugar, introducimos un modelo para explorar el impacto que las redes sociales en las que vivimos inmersos tienen en la actividad económica que transcurre sobre ellas, y mas concretamente en hasta qué punto la estructura de estas redes puede limitar la meritocracia de una sociedad. Como concepto contrario a meritocracia, en esta tesis, introducimos el término topocracia. Definimos un sistema como topocrático cuando la influencia o el poder y los ingresos de los individuos vienen principalmente determinados por la posición que ocupan en la red. Nuestro modelo es perfectamente meritocrático para redes completamente conectadas (todos los nodos están enlazados con el resto de nodos). Sin embargo nuestro modelo predice una transición hacia la topocracia a medida que disminuye la densidad de la red, siendo las redes poco densascomo las de la sociedad- topocráticas. En este modelo, los individuos por un lado producen y venden contenidos, pero por otro lado también distribuyen los contenidos producidos por otros individuos mediando entre comprador y vendedor. La producción y distribución de contenidos definen dos medios por los que los individuos reciben ingresos. El primero de ellos es meritocrático, ya que los individuos ingresan de acuerdo a lo que producen. Por el contrario el segundo es topocrático, ya que los individuos son compensados de acuerdo al número de cadenas mas cortas de la red que pasan a través de ellos. En esta tesis resolvemos el modelo computacional y analíticamente. Los resultados indican que un sistema es meritocrático solamente si la conectividad media de los individuos es mayor que una raíz del número de individuos que hay en el sistema. Por tanto, a la luz de nuestros resultados la estructura de la red social puede representar una limitación para la meritocracia de una sociedad. En la segunda parte de esta tesis se presentan una serie de estudios empíricos en los que se analizan datos extraídos de la red social Twitter para caracterizar y modelar el comportamiento humano. En particular, nos centramos en analizar conversaciones políticas, como las que tienen lugar durante campañas electorales. Nuestros resultados indican que la atención colectiva está distribuida de una forma muy heterogénea, con una minoría de cuentas extremadamente influyente. Además, la capacidad de los individuos para diseminar información en Twitter está limitada por la estructura y la posición que ocupan en la red de seguidores. Por tanto, de acuerdo a nuestras observaciones las redes sociales de Internet no posibilitan que la mayoría sea escuchada por la mayoría. De hecho, nuestros resultados implican que Twitter es topocrático, ya que únicamente una minoría de cuentas ubicadas en posiciones privilegiadas en la red de seguidores consiguen que sus mensajes se expandan por toda la red social. En conversaciones políticas, esta minoría de cuentas influyentes se compone principalmente de políticos y medios de comunicación. Los políticos son los mas mencionados ya que la gente les dirige y se refiere a ellos en sus tweets. Mientras que los medios de comunicación son las fuentes desde las que la gente propaga información. En un mundo en el que los datos personales quedan registrados y son cada día mas abundantes y precisos, los resultados del modelo presentado en esta tesis pueden ser usados para fomentar medidas que promuevan la meritocracia. Además, los resultados de los estudios empíricos sobre Twitter que se presentan en la segunda parte de esta tesis son de vital importancia para entender la nueva "sociedad digital" que emerge. En concreto hemos presentado resultados relevantes que caracterizan el comportamiento humano en Internet y que pueden ser usados para crear futuros modelos. Abstract Society can be defined as a complex system that emerges from the cooperation and coordination of billions of individuals and hundreds of countries. Thus, we do not live in social vacuum and the social networks in which we are embedded inevitably shapes our behavior. Here, we present an analytical model and several empirical studies in which we analyze dynamical social systems through a network science perspective. First, we introduce a model to explore how the structure of the social networks underlying society can limit the meritocracy of the economies. Conversely to meritocracy, in this work we introduce the term topocracy. We say that a system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Our model is perfectly meritocratic for fully connected networks but becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. Hence, in the light of our model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies. Next, we present several empirical studies that use data gathered from Twitter to analyze online human behavioral patterns. In particular, we focus on political conversations such as electoral campaigns. We found that the collective attention is highly heterogeneously distributed, as there is a minority of extremely influential accounts. In fact, the ability of individuals to propagate messages or ideas through the platform is constrained by the structure of the follower network underlying the social media and the position they occupy on it. Hence, although people have argued that social media can allow more voices to be heard, our results suggest that Twitter is highly topocratic, as only the minority of well positioned users are widely heard. This minority of influential accounts belong mostly to politicians and traditional media. Politicians tend to be the most mentioned, while media are the sources of information from which people propagate messages. We also propose a methodology to study and measure the emergence of political polarization from social interactions. To this end, we first propose a model to estimate opinions in which a minority of influential individuals propagate their opinions through a social network. The result of the model is an opinion probability density function. Next, we propose an index to quantify the extent to which the resulting distribution is polarized. Finally, we illustrate our methodology by applying it to Twitter data. In a world where personal data is increasingly available, the results of the analytical model introduced in this work can be used to enhance meritocracy and promote policies that help to build more meritocratic societies. Moreover, the results obtained in the latter part, where we have analyzed Twitter, are key to understand the new data-driven society that is emerging. In particular, we have presented relevant information that can be used to benchmark future models for online communication systems or can be used as empirical rules characterizing our online behavior.

Changes in resting-state functionally connected parieto-frontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task-free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting-state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting-state fMRI, jointly with a dual-regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

Knowledge Discovery in Spectral Data by Means of Complex Networks

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

The Influence of Communication Range on Connectivity for Resilient Wireless Sensor Networks Using a Probabilistic Approach.

Wireless sensor networks (WSNs) consist of thousands of nodes that need to communicate with each other. However, it is possible that some nodes are isolated from other nodes due to limited communication range. This paper focuses on the influence of communication range on the probability that all nodes are connected under two conditions, respectively: (1) all nodes have the same communication range, and (2) communication range of each node is a random variable. In the former case, this work proves that, for 0menor queepsmenor quee^(-1) , if the probability of the network being connected is 0.36eps , by means of increasing communication range by constant C(eps) , the probability of network being connected is at least 1-eps. Explicit function C(eps) is given. It turns out that, once the network is connected, it also makes the WSNs resilient against nodes failure. In the latter case, this paper proposes that the network connection probability is modeled as Cox process. The change of network connection probability with respect to distribution parameters and resilience performance is presented. Finally, a method to decide the distribution parameters of node communication range in order to satisfy a given network connection probability is developed.

Design and optimization of optical, fiber based PSK demodulators for high-bit-rate optical networks

El objetivo principal de esta tesis ha sido el diseño y la optimización de receptores implementados con fibra óptica, para ser usados en redes ópticas de alta velocidad que empleen formatos de modulación de fase. En los últimos años, los formatos de modulación de fase (Phase Shift keying, PSK) han captado gran atención debido a la mejora de sus prestaciones respecto a los formatos de modulación convencionales. Principalmente, presentan una mejora de la eficiencia espectral y una mayor tolerancia a la degradación de la señal causada por la dispersión cromática, la dispersión por modo de polarización y los efectos no-lineales en la fibra óptica. En este trabajo, se analizan en detalle los formatos PSK, incluyendo sus variantes de modulación de fase diferencial (Differential Phase Shift Keying, DPSK), en cuadratura (Differential Quadrature Phase Shift Keying, DQPSK) y multiplexación en polarización (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), con la finalidad de diseñar y optimizar los receptores que permita su demodulación. Para ello, se han analizado y desarrollado nuevas estructuras que ofrecen una mejora en las prestaciones del receptor y una reducción de coste comparadas con las actualmente disponibles. Para la demodulación de señales DPSK, en esta tesis, se proponen dos nuevos receptores basados en un interferómetro en línea Mach-Zehnder (MZI) implementado con tecnología todo-fibra. El principio de funcionamiento de los MZI todo-fibra propuestos se asienta en la interferencia modal que se produce en una fibra multimodo (MMF) cuando se situada entre dos monomodo (SMF). Este tipo de configuración (monomodo-multimodo-monomodo, SMS) presenta un buen ratio de extinción interferente si la potencia acoplada en la fibra multimodo se reparte, principal y equitativamente, entre dos modos dominantes. Con este objetivo, se han estudiado y demostrado tanto teórica como experimentalmente dos nuevas estructuras SMS que mejoran el ratio de extinción. Una de las propuestas se basa en emplear una fibra multimodo de índice gradual cuyo perfil del índice de refracción presenta un hundimiento en su zona central. La otra consiste en una estructura SMS con las fibras desalineadas y donde la fibra multimodo es una fibra de índice gradual convencional. Para las dos estructuras, mediante el análisis teórico desarrollado, se ha demostrado que el 80 – 90% de la potencia de entrada se acopla a los dos modos dominantes de la fibra multimodo y se consigue una diferencia inferior al 10% entre ellos. También se ha demostrado experimentalmente que se puede obtener un ratio de extinción de al menos 12 dB. Con el objeto de demostrar la capacidad de estas estructuras para ser empleadas como demoduladores de señales DPSK, se han realizado numerosas simulaciones de un sistema de transmisión óptico completo y se ha analizado la calidad del receptor bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo o la tolerancia a las dispersiones cromática y por modo de polarización. En todos los casos se ha concluido que los receptores propuestos presentan rendimientos comparables a los obtenidos con receptores convencionales. En esta tesis, también se presenta un diseño alternativo para la implementación de un receptor DQPSK, basado en el uso de una fibra mantenedora de la polarización (PMF). A través del análisi teórico y del desarrollo de simulaciones numéricas, se ha demostrado que el receptor DQPSK propuesto presenta prestaciones similares a los convencionales. Para complementar el trabajo realizado sobre el receptor DQPSK basado en PMF, se ha extendido el estudio de su principio de demodulación con el objeto de demodular señales PM-DQPSK, obteniendo como resultado la propuesta de una nueva estructura de demodulación. El receptor PM-DQPSK propuesto se basa en la estructura conjunta de una única línea de retardo junto con un rotador de polarización. Se ha analizado la calidad de los receptores DQPSK y PM-DQPSK bajo diferentes perspectivas, tales como la sensibilidad, la tolerancia a un filtrado óptico severo, la tolerancia a las dispersiones cromática y por modo de polarización o su comportamiento bajo condiciones no-ideales. En comparación con los receptores convencionales, nuestra propuesta exhibe prestaciones similares y además permite un diseño más simple que redunda en un coste potencialmente menor. En las redes de comunicaciones ópticas actuales se utiliza la tecnología de multimplexación en longitud de onda (WDM) que obliga al uso de filtros ópticos con bandas de paso lo más estrechas posibles y a emplear una serie de dispositivos que incorporan filtros en su arquitectura, tales como los multiplexores, demultiplexores, ROADMs, conmutadores y OXCs. Todos estos dispositivos conectados entre sí son equivalentes a una cadena de filtros cuyo ancho de banda se va haciendo cada vez más estrecho, llegando a distorsionar la forma de onda de las señales. Por esto, además de analizar el impacto del filtrado óptico en las señales de 40 Gbps DQPSK y 100 Gbps PM-DQPSK, este trabajo de tesis se completa estudiando qué tipo de filtro óptico minimiza las degradaciones causadas en la señal y analizando el número máximo de filtros concatenados que permiten mantener la calidad requerida al sistema. Se han estudiado y simulado cuatro tipos de filtros ópticos;Butterworth, Bessel, FBG y F-P. ABSTRACT The objective of this thesis is the design and optimization of optical fiber-based phase shift keying (PSK) demodulators for high-bit-rate optical networks. PSK modulation formats have attracted significant attention in recent years, because of the better performance with respect to conventional modulation formats. Principally, PSK signals can improve spectrum efficiency and tolerate more signal degradation caused by chromatic dispersion, polarization mode dispersion and nonlinearities in the fiber. In this work, many PSK formats were analyzed in detail, including the variants of differential phase modulation (Differential Phase Shift Keying, DPSK), in quadrature (Differential Quadrature Phase Shift Keying, DQPSK) and polarization multiplexing (Polarization Multiplexing Differential Quadrature Phase Shift Keying, PM-DQPSK), in order to design and optimize receivers enabling demodulations. Therefore, novel structures, which offer good receiver performances and a reduction in cost compared to the current structures, have been analyzed and developed. Two novel receivers based on an all-fiber in-line Mach-Zehnder interferometer (MZI) were proposed for DPSK signal demodulation in this thesis. The operating principle of the all-fiber MZI is based on the modal interference that occurs in a multimode fiber (MMF) when it is located between two single-mode fibers (SMFs). This type of configuration (Single-mode-multimode-single-mode, SMS) can provide a good extinction ratio if the incoming power from the SMF could be coupled equally into two dominant modes excited in the MMF. In order to improve the interference extinction ratio, two novel SMS structures have been studied and demonstrated, theoretically and experimentally. One of the two proposed MZIs is based on a graded-index multimode fiber (MMF) with a central dip in the index profile, located between two single-mode fibers (SMFs). The other one is based on a conventional graded-index MMF mismatch spliced between two SMFs. Theoretical analysis has shown that, in these two schemes, 80 – 90% of the incoming power can be coupled into the two dominant modes exited in the MMF, and the power difference between them is only ~10%. Experimental results show that interference extinction ratio of 12 dB could be obtained. In order to demonstrate the capacity of these two structures for use as DPSK signal demodulators, numerical simulations in a completed optical transmission system have been carried out, and the receiver quality has been analyzed under different perspectives, such as sensitivity, tolerance to severe optical filtering or tolerance to chromatic and polarization mode dispersion. In all cases, from the simulation results we can conclude that the two proposed receivers can provide performances comparable to conventional ones. In this thesis, an alternative design for the implementation of a DQPSK receiver, which is based on a polarization maintaining fiber (PMF), was also presented. To complement the work made for the PMF-based DQPSK receiver, the study of the demodulation principle has been extended to demodulate PM-DQPSK signals, resulting in the proposal of a novel demodulation structure. The proposed PM-DQPSK receiver is based on only one delay line and a polarization rotator. The quality of the proposed DQPSK and PM-DQPSK receivers under different perspectives, such as sensitivity, tolerance to severe optical filtering, tolerance to chromatic dispersion and polarization mode dispersion, or behavior under non-ideal conditions. Compared with the conventional receivers, our proposals exhibit similar performances but allow a simpler design which can potentially reduce the cost. The wavelength division multiplexing (WDM) technology used in current optical communications networks requires the use of optical filters with a passband as narrow as possible, and the use of a series of devices that incorporate filters in their architecture, such as multiplexers, demultiplexers, switches, reconfigurable add-drop multiplexers (ROADMs) and optical cross-connects (OXCs). All these devices connected together are equivalent to a chain of filters whose bandwidth becomes increasingly narrow, resulting in distortion to the waveform of the signals. Therefore, in addition to analyzing the impact of optical filtering on signal of 40 Gbps DQPSK and 100 Gbps PM-DQPSK, we study which kind of optical filter minimizes the signal degradation and analyze the maximum number of concatenated filters for maintaining the required quality of the system. Four types of optical filters, including Butterworth, Bessel, FBG and FP, have studied and simulated.

Resilient Wireless Sensor Networks Using Topology Control: A Review

Wireless sensor networks (WSNs) may be deployed in failure-prone environments, and WSNs nodes easily fail due to unreliable wireless connections, malicious attacks and resource-constrained features. Nevertheless, if WSNs can tolerate at most losing k − 1 nodes while the rest of nodes remain connected, the network is called k − connected. k is one of the most important indicators for WSNs’ self-healing capability. Following a WSN design flow, this paper surveys resilience issues from the topology control and multi-path routing point of view. This paper provides a discussion on transmission and failure models, which have an important impact on research results. Afterwards, this paper reviews theoretical results and representative topology control approaches to guarantee WSNs to be k − connected at three different network deployment stages: pre-deployment, post-deployment and re-deployment. Multi-path routing protocols are discussed, and many NP-complete or NP-hard problems regarding topology control are identified. The challenging open issues are discussed at the end. This paper can serve as a guideline to design resilient WSNs.

A novel ground fault non-directional selective protection method for ungrounded distribution networks

This paper presents a new selective and non-directional protection method to detect ground faults in neutral isolated power systems. The new proposed method is based on the comparison of the rms value of the residual current of all the lines connected to a bus, and it is able to determine the line with ground defect. Additionally, this method can be used for the protection of secondary substation. This protection method avoids the unwanted trips produced by wrong settings or wiring errors, which sometimes occur in the existing directional ground fault protections. This new method has been validated through computer simulations and experimental laboratory tests.