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Titlebook: Brain Dynamics; An Introduction to M Hermann Haken Book 2008Latest edition Springer-Verlag Berlin Heidelberg 2008 Computational Neuroscienc

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發(fā)表于 2025-3-21 16:26:37 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Brain Dynamics
期刊簡(jiǎn)稱An Introduction to M
影響因子2023Hermann Haken
視頻videohttp://file.papertrans.cn/191/190155/190155.mp4
發(fā)行地址Includes supplementary material:
學(xué)科分類Springer Series in Synergetics
圖書封面Titlebook: Brain Dynamics; An Introduction to M Hermann Haken Book 2008Latest edition Springer-Verlag Berlin Heidelberg 2008 Computational Neuroscienc
影響因子.Brain Dynamics. serves to introduce graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. Some of the advanced chapters will also be of interest to the specialists. The book approaches the subject through pulse-coupled neural networks, with at their core the lighthouse and integrate-and-fire models, which allow for the highly flexible modelling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. Topics also include pulse-averaged equations and their application to movement coordination. The book closes with a short analysis of models versus the real neurophysiological system..The second edition has been thoroughly updated and augmented by two extensive chapters that discuss the interplay between pattern recognition and synchronization. Further, to enhance the usefulness as textbook and for self-study, the detailed solutions for all 34 exercises throughout the text have been added..
Pindex Book 2008Latest edition
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The Neuron – Building Block of the Braine often form a treelike structure and the axon that, eventually, branches (Figs. 2.1 and 2.2). Information produced in other neurons is transferred to the neuron under consideration by means of localized contacts, the synapses, that are located on the dendrites and also on the cell body. Electrical
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Neuronal Cooperativity the visual system. Since a number of important experiments that concern the cooperation of neurons have been performed on this system, we will briefly describe it in this section. At the same time, we will see how this organization processes visual information. So let us follow up the individual st
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Spikes, Phases, Noise: How to Describe Them Mathematically? We Learn a Few Tricks and Some Importantis chapter. The speedy reader will read Sect. 4.1 that shows how to mathematically describe spikes (or short pulses). Section 4.4 deals with a simple model of how the conversion of axonal spikes into dendritic currents at a synapse can be modeled. Finally, we will need the fundamental concept of pha
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Many Neurons, General Case, Connection with Integrate and Fire ModelIn the present chapter we want to treat the more realistic model of Chap. 7 in detail. It connects the phase of the axonal pulses with the action potential . of the corresponding neuron and takes the damping of . into account. Furthermore, in accordance with other neuronal models, the response of th
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發(fā)表于 2025-3-22 17:50:27 | 只看該作者
Pattern Recognition Versus Synchronization: Pattern Recognitionon is, indeed, a well-established experimental fact. Occasionally, in Sects. 6.4 and 6.5 we had a look at the capability of such a network to recognize patterns. The network we studied could perform pattern recognition only to some extent, especially it was not able to fully distinguish between patt
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