Dynamics Days Latin America and the Caribbean 2018

This book contains various works presented at the Dynamics Days Latin America and the Caribbean (DDays LAC) 2018. Since its beginnings, a key goal of the DDays LAC has been to promote cross-fertilization of ideas from different areas within nonlinear dynamics. On this occasion, the contributions range from experimental to theoretical research, including (but not limited to) chaos, control theory, synchronization, statistical physics, stochastic processes, complex systems and networks, nonlinear time-series analysis, computational methods, fluid dynamics, nonlinear waves, pattern formation, population dynamics, ecological modeling, neural dynamics, and systems biology. The interested reader will find this book to be a useful reference in identifying ground-breaking problems in Physics, Mathematics, Engineering, and Interdisciplinary Sciences, with innovative models and methods that provide insightful solutions. This book is a must-read for anyone looking for new developments of Applied Mathematics and Physics in connection with complex systems, synchronization, neural dynamics, fluid dynamics, ecological networks, and epidemics

Advances in Primary Progressive Aphasia

Primary progressive aphasia is a clinical syndrome that includes a group of neurodegenerative disorders characterized by progressive language impairment. Our knowledge about this disorder has evolved significantly in recent years. Notably, correlations between clinical findings and pathology have improved, and main clinical, neuroimaging, and genetic features have been described. Furthermore, primary progressive aphasia is a good model for the study of brain–behavior relationships, and has contributed to the knowledge of the neural basis of language functioning. However, there are many open questions remaining. For instance, classification into three variants (non-fluent, semantic, and logopenic) is under debate; further data about epidemiology and natural history of the diseases are needed; and, as in other neurodegenerative disorders, successful therapies are lacking. The Guest Editors expect that this book can be very useful for scholars

SpiNNaker - A Spiking Neural Network Architecture

20 years in conception and 15 in construction, the SpiNNaker project has delivered the world’s largest neuromorphic computing platform incorporating over a million ARM mobile phone processors and capable of modelling spiking neural networks of the scale of a mouse brain in biological real time. This machine, hosted at the University of Manchester in the UK, is freely available under the auspices of the EU Flagship Human Brain Project. This book tells the story of the origins of the machine, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over. It also presents exemplar applications from ‘Talk’, a SpiNNaker-controlled robotic exhibit at the Manchester Art Gallery as part of ‘The Imitation Game’, a set of works commissioned in 2016 in honour of Alan Turing, through to a way to solve hard computing problems using stochastic neural networks. The book concludes with a look to the future, and the SpiNNaker-2 machine which is yet to come

Models for Parallel Computation in Multi-Core, Heterogeneous, and Ultra Wide-Word Architectures

Multi-core processors have become the dominant processor architecture with 2, 4, and 8 cores on a chip being widely available and an increasing number of cores predicted for the future. In addition, the decreasing costs and increasing programmability of Graphic Processing Units (GPUs) have made these an accessible source of parallel processing power in general purpose computing. Among the many research challenges that this scenario has raised are the fundamental problems related to theoretical modeling of computation in these architectures. In this thesis we study several aspects of computation in modern parallel architectures, from modeling of computation in multi-cores and heterogeneous platforms, to multi-core cache management strategies, through the proposal of an architecture that exploits bit-parallelism on thousands of bits. Observing that in practice multi-cores have a small number of cores, we propose a model for low-degree parallelism for these architectures. We argue that assuming a small number of processors (logarithmic in a problem's input size) simplifies the design of parallel algorithms. We show that in this model a large class of divide-and-conquer and dynamic programming algorithms can be parallelized with simple modifications to sequential programs, while achieving optimal parallel speedups. We further explore low-degree-parallelism in computation, providing evidence of fundamental differences in practice and theory between systems with a sublinear and linear number of processors, and suggesting a sharp theoretical gap between the classes of problems that are efficiently parallelizable in each case. Efficient strategies to manage shared caches play a crucial role in multi-core performance. We propose a model for paging in multi-core shared caches, which extends classical paging to a setting in which several threads share the cache. We show that in this setting traditional cache management policies perform poorly, and that any effective strategy must partition the cache among threads, with a partition that adapts dynamically to the demands of each thread. Inspired by the shared cache setting, we introduce the minimum cache usage problem, an extension to classical sequential paging in which algorithms must account for the amount of cache they use. This cache-aware model seeks algorithms with good performance in terms of faults and the amount of cache used, and has applications in energy efficient caching and in shared cache scenarios. The wide availability of GPUs has added to the parallel power of multi-cores, however, most applications underutilize the available resources. We propose a model for hybrid computation in heterogeneous systems with multi-cores and GPU, and describe strategies for generic parallelization and efficient scheduling of a large class of divide-and-conquer algorithms. Lastly, we introduce the Ultra-Wide Word architecture and model, an extension of the word-RAM model, that allows for constant time operations on thousands of bits in parallel. We show that a large class of existing algorithms can be implemented in the Ultra-Wide Word model, achieving speedups comparable to those of multi-threaded computations, while avoiding the more difficult aspects of parallel programming

EEG-based investigation of cortical activity during Postural Control

The postural control system regulates the ability to maintain a stable upright stance and to react to changes in the external environment. Although once believed to be dominated by low-level reflexive mechanisms, mounting evidence has highlighted a prominent role of the cortex in this process. Nevertheless, the high-level cortical mechanisms involved in postural control are still largely unexplored. The aim of this thesis is to use electroencephalography, a widely used and non-invasive neuroimaging tool, to shed light on the cortical mechanisms which regulate postural control and allow balance to be preserved in the wake of external disruptions to one’s quiet stance. EEG activity has been initially analysed during a well-established postural task - a sequence of proprioceptive stimulations applied to the calf muscles to induce postural instability – traditionally used to examine the posturographic response. Preliminary results, obtained through a spectral power analysis of the data, highlighted an increased activation in several cortical areas, as well as different activation patterns in the two tested experimental conditions: open and closed eyes. An improved experimental protocol has then been developed, allowing a more advanced data analysis based on source reconstruction and brain network analysis techniques. Using this new approach, it was possible to characterise with greater detail the topological structure of cortical functional connections during the postural task, as well as to draw a connection between quantitative network metrics and measures of postural performance. Finally, with the integration of electromyography in the experimental protocol, we were able to gain new insights into the cortico-muscular interactions which direct the muscular response to a postural challenge. Overall, the findings presented in this thesis provide further evidence of the prominent role played by the cortex in postural control. They also prove how novel EEG-based brain network analysis techniques can be a valid tool in postural research and offer promising perspectives for the integration of quantitative cortical network metrics into clinical evaluation of postural impairment.Kerfi stöðustjórnunar er afturvirkt stýrikerfi sem vinnur stöðugt að því að viðhalda uppréttri stöðu líkamans og bregðast við ójafnvægi. Vaxandi þekking á undanförnum árum hefur lýst því að úrvinnsla þessara upplýsinga á sér stað á öllum stigum miðtaugakerfisins, þá sérstaklega barkarsvæði heilahvela. Engu að síður, er nákvæmu hlutverk heilabarkar við stöðustjórnun enn óljóst að mörgu leyti. Tilgangur þessa verkefnis var að rannsaka nánar hlutverk heilabarkar við truflun og áreiti á kerfi stöðustjórnarinnar, með notkun hágæða heilarafrits (EEG). Við byrjuðum á því að mæla heilarit einstaklinga meðan á þekktri líkamsstöðu-æfingu stóð, til þess að skoða svörun líkamans við röð titringsáreita sem beitt var á kálfavöðvana til að framkalla óstöðugleika. Bráðabirgðaniðurstöður fengnar með PSD-aðferð (power spectral analysis) leiddu í ljós aukna virkni á ákveðnum svæðum í heilaberki og sérstakt viðbragðsmynstur við að framkvæma æfinguna, annars vegar með lokuð augu og hins vegar opin augu. Rannsókn okkar hélt áfram með nýrri og þróaðari tækni sem gerði okkur kleift að framkvæma fullkomnari greiningaraðferðir til að túlka, greina og skilja merki frá heilaritnu. Með fullkomnari greiningaraðferðum var hægt að lýsa með nákvæmari hætti staðfræðilega uppbyggingu starfrænna tenginga í heilaberki meðan á líkamsstöðu æfingunni stóð, sem og að draga tengsl á milli megindlegra netmælinga og mælinga á líkamsstöðu. Að lokum bætist við vöðvarafritsmæling við aðferðafræðina, sem gaf okkur innsýn inn í samskipti heilabarka og vöðvana sem stýra vöðvaviðbrögðum og viðhalda líkamsstöðu við utanaðkomandi áreiti. Á heildina litið gefa niðurstöðurnar sem settar eru fram í þessari ritgerð enn sterkari vísbendingar um það áberandi hlutverk sem heilabörkurinn gegnir við stjórnun líkamsstöðu. Niðurstöðurnar sanna einnig hvernig ný aðferð á greiningu á tengslaneti heilans sem byggir á heilariti getur verið gilt tæki í líkamsstöðu rannsóknum og er nytsamlegt tól fyrir mælingar á heilakerfisneti í klínískt mat á skerðingu líkamsstöðu

Training issues and learning algorithms for feedforward and recurrent neural networks

Ph.DDOCTOR OF PHILOSOPH

Data Science, Data Visualization, and Digital Twins

Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development

SpiNNaker - A Spiking Neural Network Architecture

20 years in conception and 15 in construction, the SpiNNaker project has delivered the world’s largest neuromorphic computing platform incorporating over a million ARM mobile phone processors and capable of modelling spiking neural networks of the scale of a mouse brain in biological real time. This machine, hosted at the University of Manchester in the UK, is freely available under the auspices of the EU Flagship Human Brain Project. This book tells the story of the origins of the machine, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over. It also presents exemplar applications from ‘Talk’, a SpiNNaker-controlled robotic exhibit at the Manchester Art Gallery as part of ‘The Imitation Game’, a set of works commissioned in 2016 in honour of Alan Turing, through to a way to solve hard computing problems using stochastic neural networks. The book concludes with a look to the future, and the SpiNNaker-2 machine which is yet to come

EEG-based investigation of cortical activity during Postural Control

The postural control system regulates the ability to maintain a stable upright stance and to react to changes in the external environment. Although once believed to be dominated by low-level reflexive mechanisms, mounting evidence has highlighted a prominent role of the cortex in this process. Nevertheless, the high-level cortical mechanisms involved in postural control are still largely unexplored. The aim of this thesis is to use electroencephalography, a widely used and non-invasive neuroimaging tool, to shed light on the cortical mechanisms which regulate postural control and allow balance to be preserved in the wake of external disruptions to one’s quiet stance. EEG activity has been initially analysed during a well-established postural task - a sequence of proprioceptive stimulations applied to the calf muscles to induce postural instability – traditionally used to examine the posturographic response. Preliminary results, obtained through a spectral power analysis of the data, highlighted an increased activation in several cortical areas, as well as different activation patterns in the two tested experimental conditions: open and closed eyes. An improved experimental protocol has then been developed, allowing a more advanced data analysis based on source reconstruction and brain network analysis techniques. Using this new approach, it was possible to characterise with greater detail the topological structure of cortical functional connections during the postural task, as well as to draw a connection between quantitative network metrics and measures of postural performance. Finally, with the integration of electromyography in the experimental protocol, we were able to gain new insights into the cortico-muscular interactions which direct the muscular response to a postural challenge. Overall, the findings presented in this thesis provide further evidence of the prominent role played by the cortex in postural control. They also prove how novel EEG-based brain network analysis techniques can be a valid tool in postural research and offer promising perspectives for the integration of quantitative cortical network metrics into clinical evaluation of postural impairment

Proceedings, MSVSCC 2014

Proceedings of the 8th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 17, 2014 at VMASC in Suffolk, Virginia