Coherent Behavior In Neuronal Networks PDF Download
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| Author | : Krešimir Josic |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 311 |
| Release | : 2009-08-22 |
| Genre | : Medical |
| ISBN | : 1441903895 |
Download Coherent Behavior in Neuronal Networks Book in PDF, ePub and Kindle
Recent experimental research advances have led to increasingly detailed descriptions of how networks of interacting neurons process information. With these developments, it has become clear that dynamic network behaviors underlie information processing, and that the observed activity patterns cannot be fully explained by simple concepts such as synchrony and phase locking. These new insights raise significant challenges and offer exciting opportunities for experimental and theoretical neuroscientists. Coherent Behavior in Neuronal Networks features a review of recent research in this area from some of the world’s foremost experts on systems neuroscience. The book presents novel methodologies and interdisciplinary perspectives, and will serve as an invaluable resource to the research community. Highlights include the results of interdisciplinary collaborations and approaches as well as topics, such as the interplay of intrinsic and synaptic dynamics in producing coherent neuronal network activity and the roles of globally coherent rhythms and oscillations in the coordination of distributed processing, that are of significant research interest but have been underrepresented in the review literature. With its cutting-edge mathematical, statistical, and computational techniques, this volume will be of interest to all researchers and students in the field of systems neuroscience.
| Author | : Carl Faingold |
| Publisher | : Academic Press |
| Total Pages | : 537 |
| Release | : 2013-12-26 |
| Genre | : Medical |
| ISBN | : 0124158641 |
Download Neuronal Networks in Brain Function, CNS Disorders, and Therapeutics Book in PDF, ePub and Kindle
Neuronal Networks in Brain Function, CNS Disorders, and Therapeutics, edited by two leaders in the field, offers a current and complete review of what we know about neural networks. How the brain accomplishes many of its more complex tasks can only be understood via study of neuronal network control and network interactions. Large networks can undergo major functional changes, resulting in substantially different brain function and affecting everything from learning to the potential for epilepsy. With chapters authored by experts in each topic, this book advances the understanding of: How the brain carries out important tasks via networks How these networks interact in normal brain function Major mechanisms that control network function The interaction of the normal networks to produce more complex behaviors How brain disorders can result from abnormal interactions How therapy of disorders can be advanced through this network approach This book will benefit neuroscience researchers and graduate students with an interest in networks, as well as clinicians in neuroscience, pharmacology, and psychiatry dealing with neurobiological disorders. Utilizes perspectives and tools from various neuroscience subdisciplines (cellular, systems, physiologic), making the volume broadly relevant Chapters explore normal network function and control mechanisms, with an eye to improving therapies for brain disorders Reflects predominant disciplinary shift from an anatomical to a functional perspective of the brain Edited work with chapters authored by leaders in the field around the globe – the broadest, most expert coverage available
| Author | : Paul S. G. Stein |
| Publisher | : MIT Press |
| Total Pages | : 330 |
| Release | : 1997 |
| Genre | : Locomotion |
| ISBN | : 9780262692274 |
Download Neurons, Networks, and Motor Behavior Book in PDF, ePub and Kindle
Recent advances in motor behavior research rely on detailed knowledge of the characteristics of the neurons and networks that generate motor behavior. At the cellular level, Neurons, Networks, and Motor Behavior describes the computational characteristics of individual neurons and how these characteristics are modified by neuromodulators. At the network and behavioral levels, the volume discusses how network structure is dynamically modulated to produce adaptive behavior. Comparisons of model systems throughout the animal kingdom provide insights into general principles of motor control. Contributors describe how networks generate such motor behaviors as walking, swimming, flying, scratching, reaching, breathing, feeding, and chewing. An emerging principle of organization is that nervous systems are remarkably efficient in constructing neural networks that control multiple tasks and dynamically adapt to change.The volume contains six sections: selection and initiation of motor patterns; generation and formation of motor patterns: cellular and systems properties; generation and formation of motor patterns: computational approaches; modulation and reconfiguration; short-term modulation of pattern generating circuits; and sensory modification of motor output to control whole body orientation.
| Author | : J.G. Taylor |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 378 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1447120019 |
Download Neural Network Dynamics Book in PDF, ePub and Kindle
Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.
| Author | : Eytan Domany |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 354 |
| Release | : 2013-11-11 |
| Genre | : Science |
| ISBN | : 1461243203 |
Download Models of Neural Networks Book in PDF, ePub and Kindle
Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregation. Feedback is a dominant feature of the structural organization of the brain. Recurrent neural networks have been studied extensively in the physical literature, starting with the ground breaking work of John Hop field (1982).
| Author | : Magnus Enquist |
| Publisher | : Princeton University Press |
| Total Pages | : 256 |
| Release | : 2013-12-03 |
| Genre | : Science |
| ISBN | : 1400850789 |
Download Neural Networks and Animal Behavior Book in PDF, ePub and Kindle
How can we make better sense of animal behavior by using what we know about the brain? This is the first book that attempts to answer this important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These networks mimic the architecture of a nervous system by connecting elementary neuron-like units into networks in which they stimulate or inhibit each other's activity in much the same way neurons do. This book shows how scientists can employ ANNs to analyze animal behavior, explore the general principles of the nervous systems, and test potential generalizations among species. The authors focus on simple neural networks to show how ANNs can be investigated by math and by computers. They demonstrate intuitive concepts that make the operation of neural networks more accessible to nonspecialists. The first chapter introduces various approaches to animal behavior and provides an informal introduction to neural networks, their history, and their potential advantages. The second chapter reviews artificial neural networks, including biological foundations, techniques, and applications. The following three chapters apply neural networks to such topics as learning and development, classical instrumental condition, and the role of genes in building brain networks. The book concludes by comparing neural networks to other approaches. It will appeal to students of animal behavior in many disciplines. It will also interest neurobiologists, cognitive scientists, and those from other fields who wish to learn more about animal behavior.
| Author | : Karl H. Pribram |
| Publisher | : Psychology Press |
| Total Pages | : 566 |
| Release | : 2014-04-08 |
| Genre | : Psychology |
| ISBN | : 1317780949 |
Download Rethinking Neural Networks Book in PDF, ePub and Kindle
The result of the first Appalachian Conference on neurodynamics, this volume focuses on processing in biological neural networks. How do brain processes become organized during decision making? That is, what are the neural antecedents that determine which course of action is to be pursued? Half of the contributions deal with modelling synapto-dendritic and neural ultrastructural processes; the remainder, with laboratory research findings, often cast in terms of the models. The interchanges at the conference and the ensuing publication also provide a foundation for further meetings. These will address how processes in different brain systems, coactive with the neural residues of experience and with sensory input, determine decisions.
| Author | : Alessandro Villa |
| Publisher | : Springer |
| Total Pages | : 763 |
| Release | : 2012-09-19 |
| Genre | : Computers |
| ISBN | : 3642332692 |
Download Artificial Neural Networks and Machine Learning -- ICANN 2012 Book in PDF, ePub and Kindle
The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.
| Author | : Ziye Zhang |
| Publisher | : Springer Nature |
| Total Pages | : 236 |
| Release | : 2022-11-05 |
| Genre | : Technology & Engineering |
| ISBN | : 981195450X |
Download Complex-Valued Neural Networks Systems with Time Delay Book in PDF, ePub and Kindle
This book provides up-to-date developments in the stability analysis and (anti-)synchronization control area for complex-valued neural networks systems with time delay. It brings out the characteristic systematism in them and points out further insight to solve relevant problems. It presents a comprehensive, up-to-date, and detailed treatment of dynamical behaviors including stability analysis and (anti-)synchronization control. The materials included in the book are mainly based on the recent research work carried on by the authors in this domain. The book is a useful reference for all those from senior undergraduates, graduate students, to senior researchers interested in or working with control theory, applied mathematics, system analysis and integration, automation, nonlinear science, computer and other related fields, especially those relevant scientific and technical workers in the research of complex-valued neural network systems, dynamic systems, and intelligent control theory.
| Author | : Akira Hirose |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 205 |
| Release | : 2012-03-23 |
| Genre | : Computers |
| ISBN | : 3642276318 |
Download Complex-Valued Neural Networks Book in PDF, ePub and Kindle
This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplinary studies to realize comfortable society. It is also helpful to those who carry out research and development regarding new products and services at companies. The author wrote this book hoping in particular that it provides the readers with meaningful hints to make good use of neural networks in fully practical applications. The book emphasizes basic ideas and ways of thinking. Why do we need to consider neural networks that deal with complex numbers? What advantages do the complex-valued neural networks have? What is the origin of the advantages? In what areas do they develop principal applications? This book answers these questions by describing details and examples, which will inspire the readers with new ideas. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplinary studies to realize comfortable society. It is also helpful to those who carry out research and development regarding new products and services at companies. The author wrote this book hoping in particular that it provides the readers with meaningful hints to make good use of neural networks in fully practical applications. The book emphasizes basic ideas and ways of thinking. Why do we need to consider neural networks that deal with complex numbers? What advantages do the complex-valued neural networks have? What is the origin of the advantages? In what areas do they develop principal applications? This book answers these questions by describing details and examples, which will inspire the readers with new ideas.
