Neuro-informatics and Neural Modelling

Moss, F.; Gielen, S.

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Table of contents
  • Cover
  • Contents of Volume 4xiii
  • General Prefacev
  • Preface to Volume 4ix
  • Contributors to Volume 4xvii
  • SECTION 1: STATISTICAL AND NONLINEAR DYNAMICS IN NEUROSCIENCE1
  • Chapter 1. Electrical Stimulation of the Somatosensory System1
  • Chapter 2. Phase Synchronization: From Periodic to Chaotic and Noisy23
  • Chapter 3. Fluctuations in Neural Systems: From Subcellular to Network Levels83
  • Chapter 4. Chaos and the Detection of Unstable Periodic Orbits in Biological Systems131
  • Chapter 5. The Topology and Organization of Unstable Periodic Orbits in Hodgkin„Huxley Models of R155
  • Chapter 6. Controlling Cardiac Arrhythmias: The Relevance of Nonlinear Dynamics205
  • Chapter 7. Controlling the Dynamics of Cardiac Muscle Using Small Electrical Stimuli229
  • Chapter 8. Intrinsic Noise from Voltage-Gated Ion Channels: Effects on Dynamics and Reliability in I257
  • Chapter 9. Phase Synchronization: From Theory to Data Analysis279
  • Chapter 10. Statistical Analysis and Modeling of Calcium Waves in Healthy and Pathological Astrocyte323
  • SECTION 2: BIOLOGICAL PHYSICS OF NEURONS AND NEURAL NETWORKS353
  • Chapter 11. Neurones as Physical Objects: Structure, Dynamics and Function353
  • Chapter 12. A Framework for Spiking Neuron Models: The Spike Response Model469
  • Chapter 13. An Introduction to Stochastic Neural Networks517
  • Chapter 14. Statistical Mechanics of Recurrent Neural Networks I – Statics553
  • Chapter 15. Statistical Mechanics of Recurrent Neural Networks II – Dynamics619
  • Chapter 16. Topologically Ordered Neural Networks685
  • Chapter 17. Geometry of Neural Networks: Natural Gradient for Learning731
  • Chapter 18. Theory of Synaptic Plasticity771
  • Chapter 19. Information Coding in Higher Sensory and Memory Areas825
  • Chapter 20. Population Coding: Efficiency and Interpretation of Neuronal Activity853
  • Chapter 21. Mechanisms of Synchrony of Neural Activity in Large Networks887
  • Chapter 22. Emergence of Feature Selectivity from Lateral Interactions in the Visual Cortex969
  • Chapter 23. Information Transfer Between Sensory and Motor Networks1001
  • Epilogue to Volume 41043
  • Subject Index1045
Book details
  • Vendor Elsevier S & T
  • SKU 9780444502841
  • ISBN-13 9780080537429
  • Author Moss, F.; Gielen, S.
  • Category Social Science
  • Subject Physical

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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 from a collection of well-known authors is presented. One section focuses on computational aspects from single neurons to networks with a major emphasis on the latter. The second section highlights some insights that have recently developed out of the nonlinear systems approach.