Estudio Multimodal de la Funcionalidad Cortical en ratones Transgénicos con Síndrome X Frágil y la modulación del dolor

El dolor es un síntoma frecuente en la práctica médica. En España, un estudio realizado en el año 2000 demostró que cada médico atiende un promedio de 181 pacientes con dolor por mes, la mayoría de ellos con dolor crónico moderado1. Del 7%-8% de la población europea está afectada y hasta el 5% puede ser grave2-3, se estima, que afecta a más de dos millones de españoles4. En la consulta de Atención Primaria, los pacientes con dolor neuropático tienen tasas de depresión mucho mayores 5-6-7. El dolor neuropático8 es el dolor causado por daño o enfermedad que afecta al sistema somato-sensorial, es un problema de salud pública con un alto coste laboral, debido a que existe cierto desconocimiento de sus singularidades, tanto de su diagnóstico como de su tratamiento, que al fallar, el dolor se perpetúa y se hace más rebelde a la hora de tratarlo, en la mayoría de las ocasiones pasa a ser crónico. Los mecanismos fisiopatológicos son evolutivos, se trata de un proceso progresivo e integrado que avanza si no recibe tratamiento, ocasionando graves repercusiones en la calidad de vida de los pacientes afectados9. De acuerdo a Prusiner (premio nobel de medicina 1997), en todas las enfermedades neurodegenerativas hay algún tipo de proceso anormal de la función neuronal. Las enfermedades neurodegenerativas son la consecuencia de anormalidades en el proceso de ciertas proteínas que intervienen en el ciclo celular, por lo tanto da lugar al cúmulo de las mismas en las neuronas o en sus proximidades, disminuyendo o anulando sus funciones, como la enfermedad de Alzheimer y el mismo SXF. La proteína FMRP (Fragile Mental Retardation Protein), esencial para el desarrollo cognitivo normal, ha sido relacionada con la vía piramidal del dolor10-11-12. El Síndrome de X Frágil13-14 (SXF), se debe a la mutación del Gen (FMR-1). Como consecuencia de la mutación, el gen se inactiva y no puede realizar la función de sintetizar la proteína FMRP. Por su incidencia se le considera la primera causa de Deficiencia Mental Hereditaria sólo superada por el Síndrome de Down. La electroencefalografía (EEG) es el registro de la actividad bioeléctrica cerebral que ha traído el desarrollo diario de los estudios clínicos y experimentales para el descubrimiento, diagnóstico y tratamiento de un gran número de anormalidades neurológicas y fisiológicas del cerebro y el resto del sistema nervioso central (SNC) incluyendo el dolor. El objetivo de la presente investigación es por medio de un estudio multimodal, desarrollar nuevas formas de presentación diagnóstica mediante técnicas avanzadas de procesado de señal y de imagen, determinando así los vínculos entre las evaluaciones cognitivas y su correlación anatómica con la modulación al dolor presente en patologías relacionadas con proteína FMRP. Utilizando técnicas biomédicas (funcionalestructural) para su caracterización. Para llevar a cabo esta tarea hemos utilizado el modelo animal de ratón. Nuestros resultados en este estudio multimodal demuestran que hay alteraciones en las vías de dolor en el modelo animal FMR1-KO, en concreto en la modulación encefálica (dolor neuropático), los datos se basan en los resultados del estudio estructural (imagen histología), funcional (EEG) y en pruebas de comportamiento (Laberinto de Barnes). En la Histología se muestra una clara asimetría estructural en el modelo FMR1 KO con respecto al control WT, donde el hemisferio Izquierdo tiene mayor densidad de masa neuronal en KO hembras 56.7%-60.8%, machos 58.3%-61%, en WT hembras 62.7%-62.4%, machos 55%-56.2%, hemisferio derecho-izquierdo respectivamente, esto refleja una correlación entre hemisferios muy baja en los sujetos KO (~50%) con respecto a los control WT (~90%). Se encontró correlación significativa entre las pruebas de memoria a largo plazo con respecto a la asimetría hemisférica (r = -0.48, corregido <0,05). En el estudio de comportamiento también hay diferencias, los sujetos WT tuvieron 22% un de rendimiento en la memoria a largo plazo, mientras que en los machos hay deterioro de memoria de un 28% que se corresponden con la patología en humanos. En los resultados de EEG estudiados en el hemisferio izquierdo, en el área de la corteza insular, encuentran que la latencia de la respuesta al potencial evocado es menor (22vs32 15vs96seg), la intensidad de la señal es mayor para los sujetos experimentales FMR1 KO frente a los sujetos control, esto es muy significativo dados los resultados en la histología (140vs129 145vs142 mv). Este estudio multimodal corrobora que las manifestaciones clínicas del SXF son variables dependientes de la edad y el sexo. Hemos podido corroborar en el modelo animal que en la etapa de adulto, los varones con SXF comienzan a desarrollar problemas en el desempeño de tareas que requieren la puesta en marcha de la función ejecutiva central de la memoria de trabajo (almacenamiento temporal). En el análisis del comportamiento es difícil llegar a una conclusión objetiva, se necesitan más estudios en diferentes etapas de la vida corroborados con resultados histológicos. Los avances logrados en los últimos años en su estudio han sido muy positivos, de tal modo que se están abriendo nuevas vías de investigación en un conjunto de procesos que representan un gran desafío a problemas médicos, asistenciales, sociales y económicos a los que se enfrentan los principales países desarrollados, con un aumento masivo de las expectativas de vida y de calidad. Las herramientas utilizadas en el campo de las neurociencias nos ofrecen grandes posibilidades para el desarrollo de estrategias que permitan ser utilizadas en el área de la educación, investigación y desarrollo. La genética determina la estructura del cerebro y nuestra investigación comprueba que la ausencia de FMRP también podría estar implicada en la modulación del dolor como parte de su expresión patológica siendo el modelo animal un punto importante en la investigación científica fundamental para entender el desarrollo de anormalidades en el cerebro. ABSTRACT Pain is a common symptom in medical practice. In Spain, a study conducted in 2000 each medical professional treats an average of 181 patients with pain per month, most of them with chronic moderate pain. 7% -8% of the European population is affected and up to 5% can be serious, it is estimated to affect more than two million people in Spain. In Primary Care, patients with neuropathic pain have much higher rates of depression. Neuropathic pain is caused by damage or disease affecting the somatosensory system, is a public health problem with high labor costs, there are relatively unfamiliar with the peculiarities in diagnosis and treatment, failing that, the pain is perpetuated and becomes rebellious to treat, in most cases becomes chronic. The pathophysiological mechanisms are evolutionary, its a progressive, if untreated, causing severe impact on the quality of life of affected patients. According to Prusiner (Nobel Prize for Medicine 1997), all neurodegenerative diseases there is some abnormal process of neuronal function. Neurodegenerative diseases are the result of abnormalities in the process of certain proteins involved in the cell cycle, reducing or canceling its features such as Alzheimer's disease and FXS. FMRP (Fragile Mental Retardation Protein), is essential for normal cognitive development, and has been linked to the pyramidal tract pain. Fragile X Syndrome (FXS), is due to mutation of the gene (FMR-1). As a consequence of the mutation, the gene is inactivated and can not perform the function of FMRP synthesize. For its incidence is considered the leading cause of Mental Deficiency Hereditary second only to Down Syndrome. Electroencephalography (EEG) is the recording of bioelectrical brain activity, is a advancement of clinical and experimental studies for the detection, diagnosis and treatment of many neurological and physiological abnormalities of the brain and the central nervous system, including pain. The objective of this research is a multimodal study, is the development of new forms of presentation using advanced diagnostic techniques of signal processing and image, to determine the links between cognitive evaluations and anatomic correlation with pain modulation to this protein FMRP-related pathologies. To accomplish this task have used the mouse model. Our results in this study show alterations in multimodal pain pathways in FMR1-KO in brain modulation (neuropathic pain), the data are based on the results of the structural study (histology image), functional (EEG) testing and behavior (Barnes maze). Histology In structural asymmetry shown in FMR1 KO model versus WT control, the left hemisphere is greater density of neuronal mass (KO females 56.7% -60.8%, 58.3% -61% males, females 62.7% -62.4 WT %, males 55% -56.2%), respectively right-left hemisphere, this reflects a very low correlation between hemispheres in KO (~ 50%) subjects compared to WT (~ 90%) control. Significant correlation was found between tests of long-term memory with respect to hemispheric asymmetry (r = -0.48, corrected <0.05). In the memory test there are differences too, the WT subjects had 22% yield in long-term memory, in males there memory impairment 28% corresponding to the condition in humans. The results of EEG studied in the left hemisphere, in insular cortex area, we found that the latency of the response evoked potential is lower (22vs32 15vs96seg), the signal strength is higher for the experimental subjects versus FMR1 KO control subjects, this is very significant given the results on histology (140vs129 145vs142 mv). This multimodal study confirms that the clinical manifestations of FXS are dependent variables of age and sex. We have been able to corroborate in the animal model in the adult stage, males with FXS begin developing problems in the performance of tasks that require the implementation of the central executive function of working memory (temporary storage). In behavior analysis is difficult to reach an objective conclusion, more studies are needed in different life stages corroborated with histologic findings. Advances in recent years were very positive, being opened new lines of research that represent a great challenge to physicians, health care, social and economic problems facing the major developed countries, with a massive increase in life expectancy and quality. The tools used in the field of neuroscience offer us great opportunities for the development of strategies to be used in the area of education, research and development. Genetics determines the structure of the brain and our research found that the absence of FMRP might also be involved in the modulation of pain as part of their pathological expression being an important animal model in basic scientific research to understand the development of abnormalities in brain.

A real case of a cognitive multiplayer game: design and development of the iOS client in Swift and its cloud architecture

as tecnologías emergentes como el cloud computing y los dispositivos móviles están creando una oportunidad sin precedentes para mejorar el sistema educativo, permitiendo tanto a los educadores personalizar y mejorar la experiencia de aprendizaje, como facilitar a los estudiantes que adquieran conocimientos sin importar dónde estén. Por otra parte, a través de técnicas de gamificacion será posible promover y motivar a los estudiantes a que aprendan materias arduas haciendo que la experiencia sea más motivadora. Los juegos móviles pueden ser el camino correcto para dar soporte a esta experiencia de aprendizaje mejorada. Este proyecto integra el diseño y desarrollo de una arquitectura en la nube altamente escalable y con alto rendimiento, así como el propio cliente de iOS, para dar soporte a una nueva version de Temporis, un juego móvil multijugador orientado a reordenar eventos históricos en una línea temporal (e.j. historia, arte, deportes, entretenimiento y literatura). Temporis actualmente está disponible en Google Play. Esta memoria describe el desarrollo de la nueva versión de Temporis (Temporis v.2.0) proporcionando detalles acerca de la mejora y adaptación basados en el Temporis original. En particular se describe el nuevo backend hecho en Go sobre Google App Engine creado para soportar miles de usuarios, asó como otras características por ejemplo como conseguir enviar noticaciones push desde la propia plataforma. Por último, el cliente de iOS en Temporis v.2.0 se ha desarrollado utilizando las últimas y más relevantes tecnologías, prestando especial atención a Swift (el lenguaje de programación nuevo de Apple, que es seguro y rápido), el Paradigma Funcional Reactivo (que ayuda a construir aplicaciones altamente interactivas además de a minimizar errores) y la arquitectura VIPER (una arquitectura que sigue los principios SOLID, se centra en la separación de asuntos y favorece la reutilización de código en otras plataformas). ABSTRACT Emerging technologies such as cloud computing and mobile devices are creating an unprecedented opportunity for enhancing the educational system, letting both educators customize and improve the learning experience, and students acquire knowledge regardless of where they are. Moreover, through gamification techniques it would be possible to encourage and motivate students to learn arduous subjects by making the experience more motivating. Mobile games can be a perfect vehicle to support this enhanced learning experience. This project integrates the design and development of a highly scalable and performant cloud architecture, as well as the iOS client that uses it, in order to provide support to a new version of Temporis, a mobile multiplayer game focused on ordering time-based (e.g. history, art, sports, entertainment and literature) in a timeline that currently is available on Google Play. This work describes the development of the new Temporis version (Temporis v.2.0), providing details about improvements and details on the adaptation of the original Temporis. In particular, the new Google App Engine backend is described, which was created to support thousand of users developed in Go language are provided, in addition to other features like how to achieve push notications in this platform. Finally, the mobile iOS client developed using the latest and more relevant technologies is explained paying special attention to Swift (Apple's new programming language, that is safe and fast), the Functional Reactive Paradigm (that helps building highly interactive apps while minimizing bugs) and the VIPER architecture (a SOLID architecture that enforces separation of concerns and makes it easy to reuse code for other platforms).

Development and implementation of a virtual laboratory for training process improvement in the mechanics of continuous media

The project arises from the need to develop improved teaching methodologies in field of the mechanics of continuous media. The objective is to offer the student a learning process to acquire the necessary theoretical knowledge, cognitive skills and the responsibility and autonomy to professional development in this area. Traditionally the teaching of the concepts of these subjects was performed through lectures and laboratory practice. During these lessons the students attitude was usually passive, and therefore their effectiveness was poor. The proposed methodology has already been successfully employed in universities like University Bochum, Germany, University the South Australia and aims to improve the effectiveness of knowledge acquisition through use by the student of a virtual laboratory. This laboratory allows to adapt the curricula and learning techniques to the European Higher Education and improve current learning processes in the University School of Public Works Engineers -EUITOP- of the Technical University of Madrid -UPM-, due there are not laboratories in this specialization. The virtual space is created using a software platform built on OpenSim, manages 3D virtual worlds, and, language LSL -Linden Scripting Language-, which imprints specific powers to objects. The student or user can access this virtual world through their avatar -your character in the virtual world- and can perform practices within the space created for the purpose, at any time, just with computer with internet access and viewfinder. The virtual laboratory has three partitions. The virtual meeting rooms, where the avatar can interact with peers, solve problems and exchange existing documentation in the virtual library. The interactive game room, where the avatar is has to resolve a number of issues in time. And the video room where students can watch instructional videos and receive group lessons. Each audiovisual interactive element is accompanied by explanations framing it within the area of knowledge and enables students to begin to acquire a vocabulary and practice of the profession for which they are being formed. Plane elasticity concepts are introduced from the tension and compression testing of test pieces of steel and concrete. The behavior of reticulated and articulated structures is reinforced by some interactive games and concepts of tension, compression, local and global buckling will by tests to break articulated structures. Pure bending concepts, simple and composite torsion will be studied by observing a flexible specimen. Earthquake resistant design of buildings will be checked by a laboratory test video.

Intelligent Therapy Assistant (ITA) for cognitive rehabilitation in patients with Acquired Brain Injury

This paper presents the design, development and first evaluation of an algorithm, named Intelligent Therapy Assistant (ITA), which automatically selects, configures and schedules rehabilitation tasks for patients with cognitive impairments after an episode of Acquired Brain Injury. The ITA is integrated in "Guttmann, Neuro Personal Trainer" (GNPT), a cognitive tele-rehabilitation platform that provides neuropsychological services.

Three-dimensional mapping of real environments for cognitive robots navigation

Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.

Improving brain injury cognitive rehabilitation by personalized telerehabilitation services: Guttmann neuropersonal trainer

Cognitive rehabilitation aims to remediate or alleviate the cognitive deficits appearing after an episode of acquired brain injury (ABI). The purpose of this work is to describe the telerehabilitation platform called Guttmann Neuropersonal Trainer (GNPT) which provides new strategies for cognitive rehabilitation, improving efficiency and access to treatments, and to increase knowledge generation from the process. A cognitive rehabilitation process has been modeled to design and develop the system, which allows neuropsychologists to configure and schedule rehabilitation sessions, consisting of set of personalized computerized cognitive exercises grounded on neuroscience and plasticity principles. It provides remote continuous monitoring of patient's performance, by an asynchronous communication strategy. An automatic knowledge extraction method has been used to implement a decision support system, improving treatment customization. GNPT has been implemented in 27 rehabilitation centers and in 83 patients' homes, facilitating the access to the treatment. In total, 1660 patients have been treated. Usability and cost analysis methodologies have been applied to measure the efficiency in real clinical environments. The usability evaluation reveals a system usability score higher than 70 for all target users. The cost efficiency study results show a relation of 1-20 compared to face-to-face rehabilitation. GNPT enables brain-damaged patients to continue and further extend rehabilitation beyond the hospital, improving the efficiency of the rehabilitation process. It allows customized therapeutic plans, providing information to further development of clinical practice guidelines.

Cognitive wireless sensor network platform for cooperative communications

Nowadays, Wireless Ad Hoc Sensor Networks (WAHSNs), specially limited in energy and resources, are subject to development constraints and difficulties such as the increasing RF spectrum saturation at the unlicensed bands. Cognitive Wireless Sensor Networks (CWSNs), leaning on a cooperative communication model, develop new strategies to mitigate the inefficient use of the spectrum that WAHSNs face. However, few and poorly featured platforms allow their study due to their early research stage. This paper presents a versatile platform that brings together cognitive properties into WAHSNs. It combines hardware and software modules as an entire instrument to investigate CWSNs. The hardware fits WAHSN requirements in terms of size, cost, features, and energy. It allows communication over three different RF bands, becoming the only cognitive platform for WAHSNs with this capability. In addition, its modular and scalable design is widely adaptable to almost any WAHSN application. Significant features such as radio interface (RI) agility or energy consumption have been proven throughout different performance tests.

A game theory based strategy for reducing energy consumption in cognitive WSN

Wireless sensor networks (WSNs) are one of the most important users of wireless communication technologies in the coming years and some challenges in this area must be addressed for their complete development. Energy consumption and spectrum availability are two of the most severe constraints of WSNs due to their intrinsic nature. The introduction of cognitive capabilities into these networks has arisen to face the issue of spectrum scarcity but could be used to face energy challenges too due to their new range of communication possibilities. In this paper a new strategy based on game theory for cognitive WSNs is discussed. The presented strategy improves energy consumption by taking advantage of the new change-communication-channel capability. Based on game theory, the strategy decides when to change the transmission channel depending on the behavior of the rest of the network nodes. The strategy presented is lightweight but still has higher energy saving rates as compared to noncognitive networks and even to other strategies based on scheduled spectrum sensing. Simulations are presented for several scenarios that demonstrate energy saving rates of around 65% as compared to WSNs without cognitive techniques.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Cognitive Surveillance Architecture for Scenario Understanding

Uno de los mayores retos para la comunidad científica es conseguir que las máquinas posean en un futuro la capacidad del sistema visual y cognitivo humanos, de forma que, por ejemplo, en entornos de video vigilancia, puedan llegar a proporcionar de manera automática una descripción fiable de lo que está ocurriendo en la escena. En la presente tesis, mediante la propuesta de un marco de trabajo de referencia, se discuten y plantean los pasos necesarios para el desarrollo de sistemas más inteligentes capaces de extraer y analizar, a diferentes niveles de abstracción y mediante distintos módulos de procesamiento independientes, la información necesaria para comprender qué está sucediendo en un conjunto amplio de escenarios de distinta naturaleza. Se parte de un análisis de requisitos y se identifican los retos para este tipo de sistemas en la actualidad, lo que constituye en sí mismo los objetivos de esta tesis, contribuyendo así a un modelo de datos basado en el conocimiento que permitirá analizar distintas situaciones en las que personas y vehículos son los actores principales, dejando no obstante la puerta abierta a la adaptación a otros dominios. Así mismo, se estudian los distintos procesos que se pueden lanzar a nivel interno así como la necesidad de integrar mecanismos de realimentación a distintos niveles que permitan al sistema adaptarse mejor a cambios en el entorno. Como resultado, se propone un marco de referencia jerárquico que integra las capacidades de percepción, interpretación y aprendizaje para superar los retos identificados en este ámbito; y así poder desarrollar sistemas de vigilancia más robustos, flexibles e inteligentes, capaces de operar en una variedad de entornos. Resultados experimentales ejecutados sobre distintas muestras de datos (secuencias de vídeo principalmente) demuestran la efectividad del marco de trabajo propuesto respecto a otros propuestos en el pasado. Un primer caso de estudio, permite demostrar la creación de un sistema de monitorización de entornos de parking en exteriores para la detección de vehículos y el análisis de plazas libres de aparcamiento. Un segundo caso de estudio, permite demostrar la flexibilidad del marco de referencia propuesto para adaptarse a los requisitos de un entorno de vigilancia completamente distinto, como es un hogar inteligente donde el análisis automático de actividades de la vida cotidiana centra la atención del estudio. ABSTRACT One of the most ambitious objectives for the Computer Vision and Pattern Recognition research community is that machines can achieve similar capacities to the human's visual and cognitive system, and thus provide a trustworthy description of what is happening in the scene under surveillance. Thus, a number of well-established scenario understanding architectural frameworks to develop applications working on a variety of environments can be found in the literature. In this Thesis, a highly descriptive methodology for the development of scene understanding applications is presented. It consists of a set of formal guidelines to let machines extract and analyse, at different levels of abstraction and by means of independent processing modules that interact with each other, the necessary information to understand a broad set of different real World surveillance scenarios. Taking into account the challenges that working at both low and high levels offer, we contribute with a highly descriptive knowledge-based data model for the analysis of different situations in which people and vehicles are the main actors, leaving the door open for the development of interesting applications in diverse smart domains. Recommendations to let systems achieve high-level behaviour understanding will be also provided. Furthermore, feedback mechanisms are proposed to be integrated in order to let any system to understand better the environment and the logical context around, reducing thus the uncertainty and noise, and increasing its robustness and precision in front of low-level or high-level errors. As a result, a hierarchical cognitive architecture of reference which integrates the necessary perception, interpretation, attention and learning capabilities to overcome main challenges identified in this area of research is proposed; thus allowing to develop more robust, flexible and smart surveillance systems to cope with the different requirements of a variety of environments. Once crucial issues that should be treated explicitly in the design of this kind of systems have been formulated and discussed, experimental results shows the effectiveness of the proposed framework compared with other proposed in the past. Two case studies were implemented to test the capabilities of the framework. The first case study presents how the proposed framework can be used to create intelligent parking monitoring systems. The second case study demonstrates the flexibility of the system to cope with the requirements of a completely different environment, a smart home where activities of daily living are performed. Finally, general conclusions and future work lines to further enhancing the capabilities of the proposed framework are presented.

Alternative neural circuitry that might be impaired in the development of Alzheimer disease

It is well established that some individuals with normal cognitive capacity have abundant senile plaques in their brains. It has been proposed that those individuals are resilient or have compensation factors to prevent cognitive decline. In this comment, we explore an alternative mechanism through which cognitive capacity is maintained. This mechanism could involve the impairment of alternative neural circuitry. Also, the proportion of molecules such as A? or tau protein present in different areas of the brain could be important.

Development of a sensorimotor algorithm able to deal with unforeseen pushes and its implementation based on VHDL

Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL is the title of my thesis which concludes my Bachelor Degree in the Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación of the Universidad Politécnica de Madrid. It encloses the overall work I did in the Neurorobotics Research Laboratory from the Beuth Hochschule für Technik Berlin during my ERASMUS year in 2015. This thesis is focused on the field of robotics, specifically an electronic circuit called Cognitive Sensorimotor Loop (CSL) and its control algorithm based on VHDL hardware description language. The reason that makes the CSL special resides in its ability to operate a motor both as a sensor and an actuator. This way, it is possible to achieve a balanced position in any of the robot joints (e.g. the robot manages to stand) without needing any conventional sensor. In other words, the back electromotive force (EMF) induced by the motor coils is measured and the control algorithm responds depending on its magnitude. The CSL circuit contains mainly an analog-to-digital converter (ADC) and a driver. The ADC consists on a delta-sigma modulation which generates a series of bits with a certain percentage of 1's and 0's, proportional to the back EMF. The control algorithm, running in a FPGA, processes the bit frame and outputs a signal for the driver. This driver, which has an H bridge topology, gives the motor the ability to rotate in both directions while it's supplied with the power needed. The objective of this thesis is to document the experiments and overall work done on push ignoring contractive sensorimotor algorithms, meaning sensorimotor algorithms that ignore large magnitude forces (compared to gravity) applied in a short time interval on a pendulum system. This main objective is divided in two sub-objectives: (1) developing a system based on parameterized thresholds and (2) developing a system based on a push bypassing filter. System (1) contains a module that outputs a signal which blocks the main Sensorimotor algorithm when a push is detected. This module has several different parameters as inputs e.g. the back EMF increment to consider a force as a push or the time interval between samples. System (2) consists on a low-pass Infinite Impulse Response digital filter. It cuts any frequency considered faster than a certain push oscillation. This filter required an intensive study on how to implement some functions and data types (fixed or floating point data) not supported by standard VHDL packages. Once this was achieved, the next challenge was to simplify the solution as much as possible, without using non-official user made packages. Both systems behaved with a series of interesting advantages and disadvantages for the elaboration of the document. Stability, reaction time, simplicity or computational load are one of the many factors to be studied in the designed systems. RESUMEN. Development of a Sensorimotor Algorithm Able to Deal with Unforeseen Pushes and Its Implementation Based on VHDL es un Proyecto de Fin de Grado (PFG) que concluye mis estudios en la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid. En él se documenta el trabajo de investigación que realicé en el Neurorobotics Research Laboratory de la Beuth Hochschule für Technik Berlin durante el año 2015 mediante el programa de intercambio ERASMUS. Este PFG se centra en el campo de la robótica y en concreto en un circuito electrónico llamado Cognitive Sensorimotor Loop (CSL) y su algoritmo de control basado en lenguaje de modelado hardware VHDL. La particularidad del CSL reside en que se consigue que un motor haga las veces tanto de sensor como de actuador. De esta manera es posible que las articulaciones de un robot alcancen una posición de equilibrio (p.ej. el robot se coloca erguido) sin la necesidad de sensores en el sentido estricto de la palabra. Es decir, se mide la propia fuerza electromotriz (FEM) inducida sobre el motor y el algoritmo responde de acuerdo a su magnitud. El circuito CSL se compone de un convertidor analógico-digital (ADC) y un driver. El ADC consiste en un modulador sigma-delta, que genera una serie de bits con un porcentaje de 1's y 0's determinado, en proporción a la magnitud de la FEM inducida. El algoritmo de control, que se ejecuta en una FPGA, procesa esta cadena de bits y genera una señal para el driver. El driver, que posee una topología en puente H, provee al motor de la potencia necesaria y le otorga la capacidad de rotar en cualquiera de las dos direcciones. El objetivo de este PFG es documentar los experimentos y en general el trabajo realizado en algoritmos Sensorimotor que puedan ignorar fuerzas de gran magnitud (en comparación con la gravedad) y aplicadas en una corta ventana de tiempo. En otras palabras, ignorar empujones conservando el comportamiento original frente a la gravedad. Para ello se han desarrollado dos sistemas: uno basado en umbrales parametrizados (1) y otro basado en un filtro de corte ajustable (2). El sistema (1) contiene un módulo que, en el caso de detectar un empujón, genera una señal que bloquea el algoritmo Sensorimotor. Este módulo recibe diferentes parámetros como el incremento necesario de la FEM para que se considere un empujón o la ventana de tiempo para que se considere la existencia de un empujón. El sistema (2) consiste en un filtro digital paso-bajo de respuesta infinita que corta cualquier variación que considere un empujón. Para crear este filtro se requirió un estudio sobre como implementar ciertas funciones y tipos de datos (coma fija o flotante) no soportados por las librerías básicas de VHDL. Tras esto, el objetivo fue simplificar al máximo la solución del problema, sin utilizar paquetes de librerías añadidos. En ambos sistemas aparecen una serie de ventajas e inconvenientes de interés para el documento. La estabilidad, el tiempo de reacción, la simplicidad o la carga computacional son algunas de las muchos factores a estudiar en los sistemas diseñados. Para concluir, también han sido documentadas algunas incorporaciones a los sistemas: una interfaz visual en VGA, un módulo que compensa el offset del ADC o la implementación de una batería de faders MIDI entre otras.