Biophysics of Computation

Author: Christof Koch
Publisher: Oxford University Press
ISBN: 0195181999
Format: PDF, ePub, Mobi
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Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

Grundlagen zur Neuroinformatik und Neurobiologie

Author: Patricia S. Churchland
Publisher: Springer-Verlag
ISBN: 3322868214
Format: PDF, Mobi
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The Computational Brain, das außergewöhnliche Buch über vergleichende Forschung in den Bereichen von menschlichem Gehirn und neuesten Möglichkeiten der Computertechnologie, liegt hiermit erstmals in deutscher Sprache vor. Geschrieben von einem führenden Forscherteam in den USA, ist es eine Fundgrube für alle, die wissen wollen, was der Stand der Wissenschaft auf diesem Gebiet ist. Die Autoren führen die Bereiche der Neuroinformatik und Neurobiologie mit gut ausgesuchten Beispielen und der gebotenen Hintergrundinformation gekonnt zusammen. Das Buch wird somit nicht nur dem Fachwissenschaftler sondern auch dem interdisziplinären Interesse des Informatikers und des Biologen auf eine hervorragende Weise gerecht. Übersetzt wurde das Buch von Prof. Dr. Steffen Hölldobler und Dipl.-Biol. Claudia Hölldobler, einem Informatiker und einer Biologin. Rezension in Spektrum der Wissenschaft nr. 10, S. 122 f. im Oktober 1997 (...) Die 1992 erschienene amerikanische Originalausgabe des vorliegenden Werkes ist so erfolgreich, daß man bereits von einem Klassiker reden kann. (...) (...) ....ist das Buch sehr zu empfehlen. In Verbindung von Neurobiologie und Neuroinformatik konkurrenzlos, vermittelt es einiges von der Faszination theoretischer Hirnforschung, die auch in Deutschland zunehmend mehr Wissenschaftler in ihren Bann schlägt. Rezension erschienen in: Computer Spektrum 3/1997, S. 2 (...)Das Buch wird somit nicht nur dem Fachwissenschaftler, sondern auch den interdisziplinären Interesse des Informatikers und des Biologen auf eine hervorragende Weise gerecht(...)

Stadtverkehrsplanung

Author: Gerd Steierwald
Publisher: Springer-Verlag
ISBN: 3662100037
Format: PDF, Mobi
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In einer Zeit des Umbruchs, des fortwährenden Wandels in den Wertvorstellungen, der Zu kunftsängste, aber auch der fortschreitenden Entwicklung der Technik und des planerischen Instrumentariums, in einer solchen Zeit ein Buch über die Grundlagen der Stadtverkehrsplanung herauszugeben, muß als Wagnis bezeichnet werden, das die Verfasser nicht leichtfertig auf sich genommen haben. Sie sind der Auffassung, daß jenseits der vielfältigen, emotional kritischen Diskussionen sowohl die methodischen Grundlagen als auch die praktischen Ansätze einen Standard erreicht haben, der in einem Überblick dargestellt werden sollte. Die Fülle des Stoffes erlaubt kein abschließendes Kompendium. Wichtig erschien den Her ausgebern, daß - neben den allgemeinen Beschreibungen und teilweise auch mit Wertungen ver bundenen zukunftsbezogenen Aussagen - die verschiedenen analytischen, prognostischen und konstruktiv-planerischen Schritte der Verkehrsplanung deutlich gemacht werden. Die Autoren können dabei auf eine umfangreiche Literatur verweisen. Der Praxis stehen zahlreiche Richtli nien und Empfehlungen anerkannter Institutionen (z.B. der Forschungsgesellschaft für Straßen und Verkehrswesen) zur Verfügung, deren flexible Handhabung gerade in Zeiten eines dynami schen Wandels an Bedeutung zunimmt. Die Darstellung beschränkt sich auf die Grundlagen der Planung und des Entwurfs städtischer Verkehrsanlagen und schließt die Behandlung von Themen der Verkehrstheorie, der Verkehrs leittechnik, des Verkehrsmanagements und der Informations- und Kommunikationssysteme aus, da sie den Rahmen dieses Handbuches sprengen würden.

Computational Neuroscience

Author: Eric L. Schwartz
Publisher: MIT Press
ISBN: 9780262691642
Format: PDF, Kindle
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The thirty original contributions in this book provide a working definition of"computational neuroscience" as the area in which problems lie simultaneously within computerscience and neuroscience. They review this emerging field in historical and philosophical overviewsand in stimulating summaries of recent results. Leading researchers address the structure of thebrain and the computational problems associated with describing and understanding this structure atthe synaptic, neural, map, and system levels.The overview chapters discuss the early days of thefield, provide a philosophical analysis of the problems associated with confusion between brainmetaphor and brain theory, and take up the scope and structure of computationalneuroscience.Synaptic-level structure is addressed in chapters that relate the properties ofdendritic branches, spines, and synapses to the biophysics of computation and provide a connectionbetween real neuron architectures and neural network simulations.The network-level chapters take upthe preattentive perception of 3-D forms, oscillation in neural networks, the neurobiologicalsignificance of new learning models, and the analysis of neural assemblies and local learningrides.Map-level structure is explored in chapters on the bat echolocation system, cat orientationmaps, primate stereo vision cortical cognitive maps, dynamic remapping in primate visual cortex, andcomputer-aided reconstruction of topographic and columnar maps in primates.The system-level chaptersfocus on the oculomotor system VLSI models of early vision, schemas for high-level vision,goal-directed movements, modular learning, effects of applied electric current fields on corticalneural activity neuropsychological studies of brain and mind, and an information-theoretic view ofanalog representation in striate cortex.Eric L. Schwartz is Professor of Brain Research and ResearchProfessor of Computer Science, Courant Institute of Mathematical Sciences, New York UniversityMedical Center. Computational Neuroscience is included in the System Development FoundationBenchmark Series.

Single Neuron Computation

Author: Thomas M. McKenna
Publisher:
ISBN:
Format: PDF, Kindle
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This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs. The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.

High Performance Computing on Complex Environments

Author: Emmanuel Jeannot
Publisher: John Wiley & Sons
ISBN: 1118712072
Format: PDF
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With recent changes in multicore and general-purpose computing on graphics processing units, the way parallel computers are used and programmed has drastically changed. It is important to provide a comprehensive study on how to use such machines written by specialists of the domain. The book provides recent research results in high-performance computing on complex environments, information on how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems, detailed studies on the impact of applying heterogeneous computing practices to real problems, and applications varying from remote sensing to tomography. The content spans topics such as Numerical Analysis for Heterogeneous and Multicore Systems; Optimization of Communication for High Performance Heterogeneous and Hierarchical Platforms; Efficient Exploitation of Heterogeneous Architectures, Hybrid CPU+GPU, and Distributed Systems; Energy Awareness in High-Performance Computing; and Applications of Heterogeneous High-Performance Computing. • Covers cutting-edge research in HPC on complex environments, following an international collaboration of members of the ComplexHPC • Explains how to efficiently exploit heterogeneous and hierarchical architectures and distributed systems • Twenty-three chapters and over 100 illustrations cover domains such as numerical analysis, communication and storage, applications, GPUs and accelerators, and energy efficiency

Cognitive Neuroscience

Author: Michael D. Rugg
Publisher: MIT Press
ISBN: 9780262680943
Format: PDF
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""Cognitive Neuroscience" is a very nice volume, with excellent contributors and timely topics. The chapters are, without exception, well-written and do an excellent job of surveying their field. The authors themselves are an impressive set of scientists. This is a superb collection that will be widely read." -- Martha Farah, Professor of Psychology, University of Pennsylvania Researchers in the new discipline of cognitive neuroscience combine the concepts and methods of cognitive psychology, neuropsychology, and neurophysiology in an attempt to understand the brains role in cognitive functions. The nine chapters of this book, written by leading authorities in their fields, cover major topics in cognitive neuroscience, including noninvasive measurement of human brain activity, neural information coding, neural mechanisms of memory and movement, working memory, language, and consciousness. Contributors: Anders Dale, Howard Eichenbaum, David Fotheringhame, Karl Friston, Chris Frith, Apostolos Georgopoulos, David Howard, John Ionides, Stefan Kohler, Marta Kutas, Morris Moscovitch, Bill Phillips, Matthew Shapiro, Edward Smith, Malcolm Young

Kompendium Systembiologie

Author: Andreas Kremling
Publisher: Springer-Verlag
ISBN: 3834886076
Format: PDF, ePub
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Das Buch beschreibt die Grundlagen der mathematischen Modellierung zellulärer Systeme. Nach einer Klassifikation von Modellen wird schwerpunktmäßig auf deterministische Modelle eingegangen und für alle relevanten zellulären Prozesse entsprechende Gleichungen angegeben. Anschließend werden eine Reihe von Verfahren zur Modellanalyse vorgestellt. Etwas kürzer werden Verfahren zum Reverse Engineering und zur Analyse von Netzwerkgraphen abgehandelt. Am Ende werden noch Verfahren der Parameteridentifikation besprochen.

Self Organizing Neural Networks

Author: Udo Seiffert
Publisher: Springer Science & Business Media
ISBN: 9783790814170
Format: PDF, Mobi
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The Self-Organizing Map (SOM) is one of the most frequently used architectures for unsupervised artificial neural networks. Introduced by Teuvo Kohonen in the 1980s, SOMs have been developed as a very powerful method for visualization and unsupervised classification tasks by an active and innovative community of interna tional researchers. A number of extensions and modifications have been developed during the last two decades. The reason is surely not that the original algorithm was imperfect or inad equate. It is rather the universal applicability and easy handling of the SOM. Com pared to many other network paradigms, only a few parameters need to be arranged and thus also for a beginner the network leads to useful and reliable results. Never theless there is scope for improvements and sophisticated new developments as this book impressively demonstrates. The number of published applications utilizing the SOM appears to be unending. As the title of this book indicates, the reader will benefit from some of the latest the oretical developments and will become acquainted with a number of challenging real-world applications. Our aim in producing this book has been to provide an up to-date treatment of the field of self-organizing neural networks, which will be ac cessible to researchers, practitioners and graduated students from diverse disciplines in academics and industry. We are very grateful to the father of the SOMs, Professor Teuvo Kohonen for sup porting this book and contributing the first chapter.