Development of statistical and computational methods to estimate functional connectivity and topology in large-scale neuronal assemblies

One of the most fundamental features of a neural circuit is its connectivity since the single neuron activity is not due only to its intrinsic properties but especially to the direct or indirect influence of other neurons1. It is fundamental to elaborate research strategies aimed at a comprehensive structural description of neuronal interconnections as well as the networks\u2019 elements forming the human connectome. The connectome will significantly increase our understanding of how functional brain states emerge from their underlying structural substrate, and will provide new mechanistic insights into how brain function is affected if this structural substrate is disrupted. The connectome is characterized by three different types of connectivity: structural, functional and effective connectivity. It is evident that the final goal of a connectivity analysis is the reconstruction of the human connectome, thus, the application of statistical measures to the in vivo model in both physiological and pathological states. Since the system under study (i.e. brain areas, cell assemblies) is highly complex, to achieve the purpose described above, it is useful to adopt a reductionist approach. During my PhD work, I focused on a reduced and simplified model, represented by neural networks chronically coupled to Micro Electrodes Arrays (MEAs). Large networks of cortical neurons developing in vitro and chronically coupled to MEAs2 represent a well-established experimental model for studying the neuronal dynamics at the network level3, and for understanding the basic principles of information coding4 learning and memory5. Thus, during my PhD work, I developed and optimized statistical methods to infer functional connectivity from spike train data. In particular, I worked on correlation-based methods: cross-correlation and partial correlation, and information-theory based methods: Transfer Entropy (TE) and Joint Entropy (JE). More in detail, my PhD\u2019s aim has been applying functional connectivity methods to neural networks coupled to high density resolution system, like the 3Brain active pixel sensor array with 4096 electrodes6. To fulfill such an aim, I re-adapted the computational logic operations of the aforementioned connectivity methods. Moreover, I worked on a new method based on the cross-correlogram, able to detect both inhibitory and excitatory links. I called such an algorithm Filtered Normalized Cross-Correlation Histogram (FNCCH). The FNCCH shows a very high precision in detecting both inhibitory and excitatory functional links when applied to our developed in silico model. I worked also on a temporal and pattern extension of the TE algorithm. In this way, I developed a Delayed TE (DTE) and a Delayed High Order TE (DHOTE) version of the TE algorithm. These two extension of the TE algorithm are able to consider different temporal bins at different temporal delays for the pattern recognition with respect to the basic TE. I worked also on algorithm for the JE computation. Starting from the mathematical definition in7, I developed a customized version of JE capable to detect the delay associated to a functional link, together with a dedicated shuffling based thresholding approach. Finally, I embedded all of these connectivity methods into a user-friendly open source software named SPICODYN8. SPICODYN allows the user to perform a complete analysis on data acquired from any acquisition system. I used a standard format for the input data, providing the user with the possibility to perform a complete set of operations on the input data, including: raw data viewing, spike and burst detection and analysis, functional connectivity analysis, graph theory and topological analysis. SPICODYN inherits the backbone structure from TOOLCONNECT, a previously published software that allowed to perform a functional connectivity analysis on spike trains dat

Proposal of an adaptive infotainment system depending on driving scenario complexity

Tesi en modalitat Doctorat industrialPla de Doctorat industrial de la Generalitat de CatalunyaThe PhD research project is framed within the plan of industrial doctorates of the “Generalitat de Catalunya”. During the investigation, most of the work was carried out at the facilities of the vehicle manufacturer SEAT, specifically at the information and entertainment (infotainment) department. In the same way, there was a continuous cooperation with the telematics department of the UPC. The main objective of the project consisted in the design and validation of an adaptive infotainment system dependent on the driving complexity. The system was created with the purpose of increasing driver’ experience while guaranteeing a proper level of road safety. Given the increasing number of application and services available in current infotainment systems, it becomes necessary to devise a system capable of balancing these two counterparts. The most relevant parameters that can be used for balancing these metrics while driving are: type of services offered, interfaces available for interacting with the services, the complexity of driving and the profile of the driver. The present study can be divided into two main development phases, each phase had as outcome a real physical block that came to be part of the final system. The final system was integrated in a vehicle and validated in real driving conditions. The first phase consisted in the creation of a model capable of estimating the driving complexity based on a set of variables related to driving. The model was built by employing machine learning methods and the dataset necessary to create it was collected from several driving routes carried out by different participants. This phase allowed to create a model capable of estimating, with a satisfactory accuracy, the complexity of the road using easily extractable variables in any modern vehicle. This approach simplify the implementation of this algorithm in current vehicles. The second phase consisted in the classification of a set of principles that allow the design of the adaptive infotainment system based on the complexity of the road. These principles are defined based on previous researches undertaken in the field of usability and user experience of graphical interfaces. According to these of principles, a real adaptive infotainment system with the most commonly used functionalities; navigation, radio and media was designed and integrated in a real vehicle. The developed system was able to adapt the presentation of the content according to the estimation of the driving complexity given by the block developed in phase one. The adaptive system was validated in real driving scenarios by several participants and results showed a high level of acceptance and satisfaction towards this adaptive infotainment. As a starting point for future research, a proof of concept was carried out to integrate new interfaces into a vehicle. The interface used as reference was a Head Mounted screen that offered redundant information in relation to the instrument cluster. Tests with participants served to understand how users perceive the introduction of new technologies and how objective benefits could be blurred by initial biases.El proyecto de investigación de doctorado se enmarca dentro del plan de doctorados industriales de la Generalitat de Catalunya. Durante la investigación, la mayor parte del trabajo se llevó a cabo en las instalaciones del fabricante de vehículos SEAT, específicamente en el departamento de información y entretenimiento (infotainment). Del mismo modo, hubo una cooperación continua con el departamento de telemática de la UPC. El objetivo principal del proyecto consistió en el diseño y la validación de un sistema de información y entretenimiento adaptativo que se ajustaba de acuerdo a la complejidad de la conducción. El sistema fue creado con el propósito de aumentar la experiencia del conductor y garantizar un nivel adecuado en la seguridad vial. El proyecto surge dado el número creciente de aplicaciones y servicios disponibles en los sistemas actuales de información y entretenimiento; es por ello que se hace necesario contar con un sistema capaz de equilibrar estas dos contrapartes. Los parámetros más relevantes que se pueden usar para equilibrar estas métricas durante la conducción son: el tipo de servicios ofrecidos, las interfaces disponibles para interactuar con los servicios, la complejidad de la conducción y el perfil del conductor. El presente estudio se puede dividir en dos fases principales de desarrollo, cada fase tuvo como resultado un componente que se convirtió en parte del sistema final. El sistema final fue integrado en un vehículo y validado en condiciones reales de conducción. La primera fase consistió en la creación de un modelo capaz de estimar la complejidad de la conducción en base a un conjunto de variables relacionadas con la conducción. El modelo se construyó empleando "Machine Learning Methods" y el conjunto de datos necesario para crearlo se recopiló a partir de varias rutas de conducción realizadas por diferentes participantes. Esta fase permitió crear un modelo capaz de estimar, con una precisión satisfactoria, la complejidad de la carretera utilizando variables fácilmente extraíbles en cualquier vehículo moderno. Este enfoque simplifica la implementación de este algoritmo en los vehículos actuales. La segunda fase consistió en la clasificación de un conjunto de principios que permiten el diseño del sistema de información y entretenimiento adaptativo basado en la complejidad de la carretera. Estos principios se definen en base a investigaciones anteriores realizadas en el campo de usabilidad y experiencia del usuario con interfaces gráficas. De acuerdo con estos principios, un sistema de entretenimiento y entretenimiento real integrando las funcionalidades más utilizadas; navegación, radio y audio fue diseñado e integrado en un vehículo real. El sistema desarrollado pudo adaptar la presentación del contenido según la estimación de la complejidad de conducción dada por el bloque desarrollado en la primera fase. El sistema adaptativo fue validado en escenarios de conducción reales por varios participantes y los resultados mostraron un alto nivel de aceptación y satisfacción hacia este entretenimiento informativo adaptativo. Como punto de partida para futuras investigaciones, se llevó a cabo una prueba de concepto para integrar nuevas interfaces en un vehículo. La interfaz utilizada como referencia era una pantalla a la altura de los ojos (Head Mounted Display) que ofrecía información redundante en relación con el grupo de instrumentos. Las pruebas con los participantes sirvieron para comprender cómo perciben los usuarios la introducción de nuevas tecnologías y cómo los sesgos iniciales podrían difuminar los beneficios.Postprint (published version

Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project

In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site

Proposal of an adaptive infotainment system depending on driving scenario complexity

The PhD research project is framed within the plan of industrial doctorates of the “Generalitat de Catalunya”. During the investigation, most of the work was carried out at the facilities of the vehicle manufacturer SEAT, specifically at the information and entertainment (infotainment) department. In the same way, there was a continuous cooperation with the telematics department of the UPC. The main objective of the project consisted in the design and validation of an adaptive infotainment system dependent on the driving complexity. The system was created with the purpose of increasing driver’ experience while guaranteeing a proper level of road safety. Given the increasing number of application and services available in current infotainment systems, it becomes necessary to devise a system capable of balancing these two counterparts. The most relevant parameters that can be used for balancing these metrics while driving are: type of services offered, interfaces available for interacting with the services, the complexity of driving and the profile of the driver. The present study can be divided into two main development phases, each phase had as outcome a real physical block that came to be part of the final system. The final system was integrated in a vehicle and validated in real driving conditions. The first phase consisted in the creation of a model capable of estimating the driving complexity based on a set of variables related to driving. The model was built by employing machine learning methods and the dataset necessary to create it was collected from several driving routes carried out by different participants. This phase allowed to create a model capable of estimating, with a satisfactory accuracy, the complexity of the road using easily extractable variables in any modern vehicle. This approach simplify the implementation of this algorithm in current vehicles. The second phase consisted in the classification of a set of principles that allow the design of the adaptive infotainment system based on the complexity of the road. These principles are defined based on previous researches undertaken in the field of usability and user experience of graphical interfaces. According to these of principles, a real adaptive infotainment system with the most commonly used functionalities; navigation, radio and media was designed and integrated in a real vehicle. The developed system was able to adapt the presentation of the content according to the estimation of the driving complexity given by the block developed in phase one. The adaptive system was validated in real driving scenarios by several participants and results showed a high level of acceptance and satisfaction towards this adaptive infotainment. As a starting point for future research, a proof of concept was carried out to integrate new interfaces into a vehicle. The interface used as reference was a Head Mounted screen that offered redundant information in relation to the instrument cluster. Tests with participants served to understand how users perceive the introduction of new technologies and how objective benefits could be blurred by initial biases.El proyecto de investigación de doctorado se enmarca dentro del plan de doctorados industriales de la Generalitat de Catalunya. Durante la investigación, la mayor parte del trabajo se llevó a cabo en las instalaciones del fabricante de vehículos SEAT, específicamente en el departamento de información y entretenimiento (infotainment). Del mismo modo, hubo una cooperación continua con el departamento de telemática de la UPC. El objetivo principal del proyecto consistió en el diseño y la validación de un sistema de información y entretenimiento adaptativo que se ajustaba de acuerdo a la complejidad de la conducción. El sistema fue creado con el propósito de aumentar la experiencia del conductor y garantizar un nivel adecuado en la seguridad vial. El proyecto surge dado el número creciente de aplicaciones y servicios disponibles en los sistemas actuales de información y entretenimiento; es por ello que se hace necesario contar con un sistema capaz de equilibrar estas dos contrapartes. Los parámetros más relevantes que se pueden usar para equilibrar estas métricas durante la conducción son: el tipo de servicios ofrecidos, las interfaces disponibles para interactuar con los servicios, la complejidad de la conducción y el perfil del conductor. El presente estudio se puede dividir en dos fases principales de desarrollo, cada fase tuvo como resultado un componente que se convirtió en parte del sistema final. El sistema final fue integrado en un vehículo y validado en condiciones reales de conducción. La primera fase consistió en la creación de un modelo capaz de estimar la complejidad de la conducción en base a un conjunto de variables relacionadas con la conducción. El modelo se construyó empleando "Machine Learning Methods" y el conjunto de datos necesario para crearlo se recopiló a partir de varias rutas de conducción realizadas por diferentes participantes. Esta fase permitió crear un modelo capaz de estimar, con una precisión satisfactoria, la complejidad de la carretera utilizando variables fácilmente extraíbles en cualquier vehículo moderno. Este enfoque simplifica la implementación de este algoritmo en los vehículos actuales. La segunda fase consistió en la clasificación de un conjunto de principios que permiten el diseño del sistema de información y entretenimiento adaptativo basado en la complejidad de la carretera. Estos principios se definen en base a investigaciones anteriores realizadas en el campo de usabilidad y experiencia del usuario con interfaces gráficas. De acuerdo con estos principios, un sistema de entretenimiento y entretenimiento real integrando las funcionalidades más utilizadas; navegación, radio y audio fue diseñado e integrado en un vehículo real. El sistema desarrollado pudo adaptar la presentación del contenido según la estimación de la complejidad de conducción dada por el bloque desarrollado en la primera fase. El sistema adaptativo fue validado en escenarios de conducción reales por varios participantes y los resultados mostraron un alto nivel de aceptación y satisfacción hacia este entretenimiento informativo adaptativo. Como punto de partida para futuras investigaciones, se llevó a cabo una prueba de concepto para integrar nuevas interfaces en un vehículo. La interfaz utilizada como referencia era una pantalla a la altura de los ojos (Head Mounted Display) que ofrecía información redundante en relación con el grupo de instrumentos. Las pruebas con los participantes sirvieron para comprender cómo perciben los usuarios la introducción de nuevas tecnologías y cómo los sesgos iniciales podrían difuminar los beneficios

A Method to Reduce the Cost of Resilience Benchmarking of SelfAdaptive Systems

Ensuring the resilience of self-adaptive systems used in critical infrastructure systems is a concern as their failure has severe societal and financial consequences. The current trends in the growth of the scale and complexity of society\u27s workload demands and the systems built to cope with these demands increases the anxiety surrounding service disruptions. Self-adaptive mechanisms instill dynamic behavior to systems in an effort to improve their resilience to runtime changes that would otherwise result in service disruption or failure, such as faults, errors, and attacks. Thus, the evaluation of a self-adaptive system\u27s resilience is critical to ensure expected operational qualities and elicit trust in their services. However, resilience benchmarking is often overlooked or avoided due to the high cost associated with evaluating the runtime behavior of large and complex self-adaptive systems against an almost infinite number of possible runtime changes. Researchers have focused on techniques to reduce the overall costs of benchmarking while ensuring the comprehensiveness of the evaluation as testing costs have been found to account for 50 to 80% of total system costs. These test suite minimization techniques include the removal of irrelevant, redundant, and repetitive test cases to ensure that only relevant tests that adequately elicit the expected system responses are enumerated. However, these approaches require an exhaustive test suite be defined first and then the irrelevant tests are filtered out, potentially negating any cost savings. This dissertation provides a new approach of defining a resilience changeload for self-adaptive systems by incorporating goal-oriented requirements engineering techniques to extract system information and guide the identification of relevant runtime changes. The approach constructs a goal refinement graph consisting of the system\u27s refined goals, runtime actions, self-adaptive agents, and underlying runtime assumptions that is used to identify obstructing conditions to runtime goal attainment. Graph theory is then used to gauge the impact of obstacles on runtime goal attainment and those that exceed the relevance requirement are included in the resilience changeload for enumeration. The use of system knowledge to guide the changeload definition process increased the relevance of the resilience changeload while minimizing the test suite, resulting in a reduction of overall benchmarking costs. Analysis of case study results confirmed that the new approach was more cost effective on the same subject system over previous work. The new approach was shown to reduce the overall costs by 79.65%, increase the relevance of the defined test suite, reduce the amount of wasted effort, and provide a greater return on investment over previous work by a factor of two

Technology Trends and Opportunities for Construction Industry and Lifecycle Management

Master's thesis in for Offshore Technology: Industrial Asset ManagementThe purpose of the report is to highlight methods that can make it easier for the construction industry and industry in general to benefit from new technology. The report is intended as a reference to technological solutions that along with some techniques, can streamline workflow for multiple tasks in planning, design, and operation and maintenance management. The problems focused on is how to: • Simplify the procurement and tracing of documentation • Optimize building stages, design, and Life Cycle Management (LCM) • Provide interactions between disciplines and employees using different software Scientific Platform are based on literature within technology trends. Some history and trends in digital technology are presented. Definition of roles and general terms related to documentation is derived from Norsk Standard and is interpreted on this basis. The report charts the use of individual software and technical setup of digital tools within CAD-engineering (Computer Aided Design), HDS-technology (High Definition Surveying), and gaming technology. This technology combined with cloud-services to support planning, design and management of building stages. Later to support LCM of facilities and businesses' ERP-systems (Enterprise Resource Planning). Use of Robotic Process Automation (RPA) and Artificial Intelligence (AI), for document control tasks. The result of the report is that several suppliers provide services and products accessible through web. Setup and implementation will require some work and knowledge for business and organizations, but the gain largely seems to justify the use of resources for this purpose. Particularly through IOT-interactions (Internet of Things), cloud-services and free downloadable applications that may be considered as a paradigm shift related to the issues in the report. Also, presenting new platforms for engineering phases to support Building Information Modeling processes (BIM). With the use of Algorithmic Editors for encoding between computer programs without the need of data programmer expertise. To streamline workflows, reduce recreation of data, interactions between different software of various user level, and support of AI to optimize designing by adds-on for CAD-engineering (Computer Aided Design). Mobile devices like phones and tablets to support several of solutions and products presented is very accessible. It seems naturally to assume that the vast majority of people are familiar with technology related to smartphone applications for daily use. The use of resources for implementing the presented solutions have not been considered in this report. Some of the equipment presented can be interpreted as relatively expensive. Investment analysis would be sensible. The trend however, shows continues price drops and increased availability. At the same time as the user interface is being improved for both software and digital equipment. The conclusion, is that the construction industry, as well as Facility Management (FM). Within both, public, and private sector, can have much to gain using the technology and techniques presented in the report

Lidar-based scale recovery dense SLAM for UAV navigation

Imagine of having an autonomous agent (drone, robot, car, ..) that wants to navigate inside an unknown environment. The first question that it needs to answer for accomplish such task is: where Am I? Where are the objects that are surrounding me? The SLAM algorithm can answer to both questions simultaneously, in an on-line manner. This thesis focus on the implementation of a monocular SLAM algorithm on the UAV framework, where the classical obtained sparsity map is densified by means of a Convolutional Neural Network, properly scaled through 2D lidar measurements.Imagine of having an autonomous agent (drone, robot, car, ..) that wants to navigate inside an unknown environment. The first question that it needs to answer for accomplish such task is: where Am I? Where are the objects that are surrounding me? The SLAM algorithm can answer to both questions simultaneously, in an on-line manner. This thesis focus on the implementation of a monocular SLAM algorithm on the UAV framework, where the classical obtained sparsity map is densified by means of a Convolutional Neural Network, properly scaled through 2D lidar measurements

The time-course of perceptual decision-making: temporal and spatial dynamics of scalp-recorded oscillatory phase and amplitude

Thesis (Ph.D.) - Indiana University, Psychological & Brain Sciences, 2014In natural conditions the brain has to actively integrate information about the current percept with information about past/present behavioral demands and cognitive states of the observer along with future outcomes related to a decision. Despite of somewhat extensive research, we still know little about the neuro-cognitive mechanisms and temporal dynamics allowing an observer to perceive an object and rapidly make a decision about it. This dissertation is based on previous research suggesting that there must be at least two cognitive processes underlying a task such as perceptual decision-making. An early mechanism related to the perception of information and a later one related to the subsequent decision-making process. Evidence has led to the proposal of the match-and-utilization model, stating that early synchronization in the gamma band is the result of a match between the current percept and memory/attentional processes. In contrast, later synchronization would reflect the utilization/readout of the early matching process; updating or influencing future processes. Evidence for this two-stage process, comes mainly from the classic event-related potential literature and, in lesser degree, from newer measures such as oscillatory amplitude. Moreover, the exploration of multivariate nonlinear techniques derived from the study of synchronization between and within neural systems, has been largely neglected in the literature. Thus, explorations of a more complete electrophysiological picture than the one provided by ERP or ERSP analyses alone, can provide us more information about the relation between neural oscillations and ERP components as electrophysiological markers of cognitive events. This is important because differential roles for frequency, phase, and amplitude as different information coding strategies in neural systems have been theoretically suggested and empirically shown. The present work presents for the first time, concomitant analyses of phase and amplitude dynamics in the context of perceptual decision-making. In this dissertation I present a parametrical task that can effectively separate the visual properties of the stimuli from the decision regarding the task at hand. Results indicate that the experimental design effectively separated stimulus properties from task demands. Additionally, I suggest distinct roles for the temporal dynamics of gamma-band oscillations. Finally, a central role for alpha oscillations is suggested