Download or read book Development of a Bio inspired Computational Astrocyte Model for Spiking Neural Networks written by Jacob Kiggins and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The mammalian brain is the most capable and complex computing entity known today. For many years there has been research focused on reproducing the brain's processing capabilities. An early example of this endeavor was the perceptron which has become the core building block of neural network models in the deep learning era. Deep learning has had tremendous success in well-defined tasks like object detection, games like go and chess, and automatic speech recognition. In fact, some deep learning models can match and even outperform humans in specific situations. However, in general, they require much more training, have higher power consumption, are more susceptible to noise and adversarial perturbations, and have very different behavior than their biological counterparts. In contrast, spiking neural network models take a step closer to biology, and in some cases behave identically to measurements of real neurons. Though there has been advancement, spiking neural networks are far from reaching their full potential, in part because the full picture of their biological underpinnings is unclear. This work attempts to reduce that gap further by exploring a bio-inspired configuration of spiking neurons coupled with a computational astrocyte model. Astrocytes, initially thought to be passive support cells in the brain are now known to actively participate in neural processing. They are believed to be critical for some processes, such as neural synchronization, self-repair, and learning. The developed astrocyte model is geared towards synaptic plasticity and is shown to improve upon existing local learning rules, as well as create a generalized approach to local spike-timing-dependent plasticity. Beyond generalizing existing learning approaches, the astrocyte is able to leverage temporal and spatial integration to improve convergence, and tolerance to noise. The astrocyte model is expanded to influence multiple synapses and configured for a specific learning task. A single astrocyte paired with a single leaky integrate and fire neuron is shown to converge on a solution in 2, 3, and 4 synapse configurations. Beyond the more concrete improvements in plasticity, this work provides a foundation for exploring supervisory astrocyte-like elements in spiking neural networks, and a framework to implement and extend many three-factor learning rules. Overall, this work brings the field a bit closer to leveraging some of the distinct advantages of biological neural networks."--Abstract.
Download or read book Biophysically based Computational Models of Astrocyte Neuron Coupling and their Functional Significance written by John Wade and published by Frontiers E-books. This book was released on 2014-03-21 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuroscientists are increasingly becoming more interested in modelling brain functions where capturing the biophysical mechanisms underpinning these functions requires plausible models at the level of neuron cells. However, cell level models are still very much in the embryo stage and therefore there is a need to advance the level of biological realism at the level of neurons/synapses. Recent publications have highlighted that astrocytes continually exchange information with multiple synapses; if we are to fully appreciate this dynamic and coordinated interplay between these cells then more research on bidirectional signalling between astrocytes and neurons is required. A better understanding of astrocyte-neuron cell coupling would provide the building block for studying the regulatory capability of astrocytes networks on a large scale. For example, it is believed that local and global signalling via astrocytes underpins brain functions like synchrony, learning, memory and self repair. This Research Topic aims to report on current research work which focuses on understanding and modelling the interaction between astrocytes and neurons at the cellular level (Bottom up) and at network level (Top down). Understanding astrocytic regulation of neural activity is crucial if we are to capture how information is represented and processed across large neuronal ensembles in humans.
Download or read book Modeling of Neuron astrocyte Interaction written by Jhunlyn Lorenzo and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The introduction of the tripartite synapse and the discovery of calcium wave propagation motivated our research to explore the potential of astrocytes as active components in brain circuits. For decades, astrocytes have been considered passive cells whose primary function is metabolic and structural support to neurons; however, recent physiological measurements suggest that astrocytes modulate neural communication, strengthen synaptic efficacy, enhance synchronization, and promote homeostasis. Inspired by these biological functions, this research aimed to implement astrocytes in artificial spiking networks for deep learning applications. First, we modeled the biological interaction between neurons and astrocytes - from the tripartite connection to neuron-astrocyte networks. The results suggest that astrocytic connectivity and heterogeneity determine whether astrocytes would improve or impair neural activities. Then, we designed a spiking neuron-astrocyte network architecture for image recognition using simplified biologically inspired models. We trained the network to recognize features and classify handwritten digits using spike-timing-dependent plasticity and an unsupervised learning algorithm. Here, the astrocyte-mediated networks displayed advantages over neuron networks alone, such as faster learning, higher accuracy, and improved bias-variance tradeoff. One of the challenges in the study is the extended duration needed for training. Therefore, we proposed a dendritic abstraction supporting dendrite-specific computations for faster learning. We analyzed the signal propagation along a pyramidal neuron dendritic tree and determined that a single neuron performs more complex computations previously attributed only to neural networks by following a multilayer-multiplexer scheme. We proposed that dendritic abstractions connected in this scheme could promote faster synaptic updates independent of backpropagating signals from the soma. This research is one of the first attempts to implement astrocytes as computational elements in artificial networks.
Download or read book Advances in Neural Computation Machine Learning and Cognitive Research VI written by Boris Kryzhanovsky and published by Springer Nature. This book was released on 2022-10-18 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXIV International Conference on Neuroinformatics, held on October 17–21, 2022, in Moscow, Russia.
Download or read book Computational Neuroscience Models at Different Levels of Abstraction for Synaptic Plasticity Astrocyte Modulation of Synchronization and Systems Memory Consolidation written by Lisa Blum Moyse and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, theoretical models with increasing levels of abstraction are developed to address questions arising from neuroscience experiments. They are studied using numerical and analytical approaches. With Laurent Venance's laboratory (Paris), we have developed an ITDP (input-timing-dependent plasticity) protocol model for the plasticity of cortico- and thalamo-striatal synapses. The model has been calibrated with ex vivo data and will be used to determine the presence of synaptic plasticity in vivo, in behavioral experiments aimed at determining the role of cortical and thalamic inputs in motor learning. At the level of neuronal populations, I have studied the modulation of neuronal collective behaviors by astrocytes, in particular Up-Down synchronization, a spontaneous alternation between periods of high collective activity and periods of silence. I have proposed rate and spiking neural network models of interconnected populations of neurons and astrocytes. They offer explanations of how astrocytes induce Up-Down transitions. Astrocytes are also probably involved in the generation of epileptic seizures, during which neuronal synchronization is impaired. Based on the above models, I have developed a neuron-astrocyte network with a cluster connectivity, showing the transition between Up-Down dynamics and events of very high activity mimicking an epileptic seizure. Finally, at the level of the brain itself, I studied the standard theory of consolidation, according to which short-term memory in the hippocampus enables the consolidation of long-term memory in the neocortex. I have sought to explain this phenomenon by integrating biological hypotheses - the size of the neocortex explaining the slowness of learning, and neurogenesis in the hippocampus explaining the erasure of its memory - into a model of interconnected neural fields that well reproduces the main features of the theory.
Download or read book Computational Vision and Bio Inspired Computing written by S. Smys and published by Springer Nature. This book was released on 2020-01-06 with total page 1435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book presents state-of-the-art research innovations in computational vision and bio-inspired techniques. Due to the rapid advances in the emerging information, communication and computing technologies, the Internet of Things, cloud and edge computing, and artificial intelligence play a significant role in the computational vision context. In recent years, computational vision has contributed to enhancing the methods of controlling the operations in biological systems, like ant colony optimization, neural networks, and immune systems. Moreover, the ability of computational vision to process a large number of data streams by implementing new computing paradigms has been demonstrated in numerous studies incorporating computational techniques in the emerging bio-inspired models. The book reveals the theoretical and practical aspects of bio-inspired computing techniques, like machine learning, sensor-based models, evolutionary optimization, and big data modeling and management, that make use of effectual computing processes in the bio-inspired systems. As such it contributes to the novel research that focuses on developing bio-inspired computing solutions for various domains, such as human–computer interaction, image processing, sensor-based single processing, recommender systems, and facial recognition, which play an indispensable part in smart agriculture, smart city, biomedical and business intelligence applications.
Download or read book Computational Glioscience written by Maurizio De Pittà and published by Springer. This book was released on 2019-01-21 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last two decades, the recognition that astrocytes - the predominant type of cortical glial cells - could sense neighboring neuronal activity and release neuroactive agents, has been instrumental in the uncovering of many roles that these cells could play in brain processing and the storage of information. These findings initiated a conceptual revolution that leads to rethinking how brain communication works since they imply that information travels and is processed not just in the neuronal circuitry but in an expanded neuron-glial network. On the other hand the physiological need for astrocyte signaling in brain information processing and the modes of action of these cells in computational tasks remain largely undefined. This is due, to a large extent, both to the lack of conclusive experimental evidence, and to a substantial lack of a theoretical framework to address modeling and characterization of the many possible astrocyte functions. This book that we propose aims at filling this gap, providing the first systematic computational approach to the complex, wide subject of neuron-glia interactions. The organization of the book is unique insofar as it considers a selection of “hot topics” in glia research that ideally brings together both the novelty of the recent experimental findings in the field and the modelling challenge that they bear. A chapter written by experimentalists, possibly in collaboration with theoreticians, will introduce each topic. The aim of this chapter, that we foresee less technical in its style than in conventional reviews, will be to provide a review as clear as possible, of what is “established” and what remains speculative (i.e. the open questions). Each topic will then be presented in its possible different aspects, by 2-3 chapters by theoreticians. These chapters will be edited in order to provide a “priming” reference for modeling neuron-glia interactions, suitable both for the graduate student and the professional researcher.
Download or read book Glial Cells Maladaptive Plasticity and Neurodegeneration Mechanisms Targeted Therapies and Future Directions written by Giovanni Cirillo and published by Frontiers Media SA. This book was released on 2023-10-17 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Enterprise Digital Transformation written by Peter Augustine and published by CRC Press. This book was released on 2022-02-17 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital transformation (DT) has become a buzzword. Every industry segment across the globe is consciously jumping toward digital innovation and disruption to get ahead of their competitors. In other words, every aspect of running a business is being digitally empowered to reap all the benefits of the digital paradigm. All kinds of digitally enabled businesses across the globe are intrinsically capable of achieving bigger and better things for their constituents. Their consumers, clients, and customers will realize immense benefits with real digital transformation initiatives and implementations. The much-awaited business transformation can be easily and elegantly accomplished with a workable and winnable digital transformation strategy, plan, and execution. There are several enablers and accelerators for realizing the much-discussed digital transformation. There are a lot of digitization and digitalization technologies available to streamline and speed up the process of the required transformation. Industrial Internet of Things (IIoT) technologies in close association with decisive advancements in the artificial intelligence (AI) space can bring forth the desired transitions. The other prominent and dominant technologies toward forming digital organizations include cloud IT, edge/fog computing, real-time data analytics platforms, blockchain technology, digital twin paradigm, virtual and augmented reality (VR/AR) techniques, enterprise mobility, and 5G communication. These technological innovations are intrinsically competent and versatile enough to fulfill the varying requirements for establishing and sustaining digital enterprises. Enterprise Digital Transformation: Technology, Tools, and Use Cases features chapters on the evolving aspects of digital transformation and intelligence. It covers the unique competencies of digitally transformed enterprises, IIoT use cases, and applications. It explains promising technological solutions widely associated with digital innovation and disruption. The book focuses on setting up and sustaining smart factories that are fulfilling the Industry 4.0 vision that is realized through the IIoT and allied technologies.
Download or read book Dynamic Coordination in the Brain written by Christoph von der Malsburg and published by MIT Press. This book was released on 2010 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Nervous systems do not live by the rate code alone. The ceaseless activities of groups of neurons are choregraphed into waves, oscillations, synchronized rhythms, and transient coalitions; it is these that underlie behavior, memory, and conscious perception. This exuberant manifesto masterfully summarizes and reflects upon the relevant evidence of these patterns from all manner of brains, small and large." --
Download or read book Statistical Mechanics of Phase Transitions written by J. M. Yeomans and published by Clarendon Press. This book was released on 1992-05-07 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an introduction to the physics which underlies phase transitions and to the theoretical techniques currently at our disposal for understanding them. It will be useful for advanced undergraduates, for post-graduate students undertaking research in related fields, and for established researchers in experimental physics, chemistry, and metallurgy as an exposition of current theoretical understanding. - ;Recent developments have led to a good understanding of universality; why phase transitions in systems as diverse as magnets, fluids, liquid crystals, and superconductors can be brought under the same theoretical umbrella and well described by simple models. This book describes the physics underlying universality and then lays out the theoretical approaches now available for studying phase transitions. Traditional techniques, mean-field theory, series expansions, and the transfer matrix, are described; the Monte Carlo method is covered, and two chapters are devoted to the renormalization group, which led to a break-through in the field. The book will be useful as a textbook for a course in `Phase Transitions', as an introduction for graduate students undertaking research in related fields, and as an overview for scientists in other disciplines who work with phase transitions but who are not aware of the current tools in the armoury of the theoretical physicist. - ;Introduction; Statistical mechanics and thermodynamics; Models; Mean-field theories; The transfer matrix; Series expansions; Monte Carlo simulations; The renormalization group; Implementations of the renormalization group. -
Download or read book The Oxford Handbook of Membrane Computing written by Gheorghe Paun and published by OUP Oxford. This book was released on 2009-12-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Membrane Computing studies models of computation (called P systems) inspired by the structure and functioning of a living cell, in particular by the role of membranes in compartmentalization of living cells. This handbook provides the necessary biological and formal background, in a state-of-the-art review of current research.
Download or read book Biomimetics written by Maki K. Habib and published by BoD – Books on Demand. This book was released on 2021-06-09 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bioinspired systems, technologies and techniques known as “biomimetics” or the “mimicry of nature,” represent a ground-breaking method of scientific research based on innovation and a creative design approach of the ‘nature’ laboratory to be applied to any scientific discipline. This approach and the associated way of thinking facilitates the cross-fertilization of scientific fields, integrating biology and the interdisciplinary knowledge featuring the evolution of models that have refined in nature within any scientific discipline.
Download or read book The Computational Brain 25th Anniversary Edition written by Patricia S. Churchland and published by MIT Press. This book was released on 2016-11-04 with total page 569 pages. Available in PDF, EPUB and Kindle. Book excerpt: An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists. Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.
Download or read book Artificial Neural Networks and Machine Learning ICANN 2019 Theoretical Neural Computation written by Igor V. Tetko and published by Springer Nature. This book was released on 2019-09-09 with total page 839 pages. Available in PDF, EPUB and Kindle. Book excerpt: The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions.
Download or read book Artificial Neural Networks as Models of Neural Information Processing written by Marcel van Gerven and published by Frontiers Media SA. This book was released on 2018-02-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.
Download or read book Brain Computer Interfaces written by Jonathan Wolpaw and published by Oxford University Press. This book was released on 2012-01-24 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: A recognizable surge in the field of Brain Computer Interface (BCI) research and development has emerged in the past two decades. This book is intended to provide an introduction to and summary of essentially all major aspects of BCI research and development. Its goal is to be a comprehensive, balanced, and coordinated presentation of the field's key principles, current practice, and future prospects.
