UID:
almafu_9960073254202883
Umfang:
1 online resource (1081 p.)
ISBN:
1-281-03871-7
,
9786611038717
,
0-08-053742-1
Serie:
Handbook of biological physics, v. 4
Inhalt:
How do sensory neurons transmit information about environmental stimuli to the central nervous system? How do networks of neurons in the CNS decode that information, thus leading to perception and consciousness? These questions are among the oldest in neuroscience. Quite recently, new approaches to exploration of these questions have arisen, often from interdisciplinary approaches combining traditional computational neuroscience with dynamical systems theory, including nonlinear dynamics and stochastic processes. In this volume in two sections a selection of contributions about these topics fr
Anmerkung:
Description based upon print version of record.
,
Front Cover; Neuro-Informatics and Neural Modelling; Copyright Page; Contents of Volume 4; General Preface; Preface to Volume 4; Contributors to Volume 4; SECTION 1: STATISTICAL AND NONLINEAR DYNAMICS IN NEUROSCIENCE; Chapter 1. Electrical Stimulation of the Somatosensory System; Chapter 2. Phase Synchronization: From Periodic to Chaotic and Noisy; Chapter 3. Fluctuations in Neural Systems: From Subcellular to Network Levels; Chapter 4. Chaos and the Detection of Unstable Periodic Orbits in Biological Systems
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Chapter 5. The Topology and Organization of Unstable Periodic Orbits in Hodgkin-Huxley Models of Receptors with Subthreshold OscillationsChapter 6. Controlling Cardiac Arrhythmias: The Relevance of Nonlinear Dynamics; Chapter 7. Controlling the Dynamics of Cardiac Muscle Using Small Electrical Stimuli; Chapter 8. Intrinsic Noise from Voltage-Gated Ion Channels: Effects on Dynamics and Reliability in Intrinsically Oscillatory Neurons; Chapter 9. Phase Synchronization: From Theory to Data Analysis
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Chapter 10. Statistical Analysis and Modeling of Calcium Waves in Healthy and Pathological Astrocyte SyncytiaSECTION 2: BIOLOGICAL PHYSICS OF NEURONS AND NEURAL NETWORKS; Chapter 11. Neurones as Physical Objects: Structure, Dynamics and Function; Chapter 12. A Framework for Spiking Neuron Models: The Spike Response Model; Chapter 13. An Introduction to Stochastic Neural Networks; Chapter 14. Statistical Mechanics of Recurrent Neural Networks I - Statics; Chapter 15. Statistical Mechanics of Recurrent Neural Networks II - Dynamics; Chapter 16. Topologically Ordered Neural Networks
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Chapter 17. Geometry of Neural Networks: Natural Gradient for LearningChapter 18. Theory of Synaptic Plasticity; Chapter 19. Information Coding in Higher Sensory and Memory Areas; Chapter 20. Population Coding: Efficiency and Interpretation of Neuronal Activity; Chapter 21. Mechanisms of Synchrony of Neural Activity in Large Networks; Chapter 22. Emergence of Feature Selectivity from Lateral Interactions in the Visual Cortex; Chapter 23. Information Transfer Between Sensory and Motor Networks; Epilogue to Volume 4; Subject Index
,
English
Weitere Ausg.:
ISBN 0-444-50284-X
Sprache:
Englisch
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