Basic Experimental Facts and Theoretical Tools -- The Neuron - Building Block of the Brain -- Neuronal Cooperativity -- Spikes, Phases, Noise: How to Describe Them Mathematically? We Learn a Few Tricks and Some Important Concepts -- Spiking in Neural Nets -- The Lighthouse Model. Two Coupled Neurons -- The Lighthouse Model. Many Coupled Neurons -- Integrate and Fire Models (IFM) -- Many Neurons, General Case, Connection with Integrate and Fire Model -- Pattern Recognition Versus Synchronization: Pattern Recognition -- Pattern Recognition Versus Synchronization: Synchronization and Phase Locking -- Phase Locking, Coordination and Spatio-Temporal Patterns -- Phase Locking via Sinusoidal Couplings -- Pulse-Averaged Equations -- Conclusion -- The Single Neuron -- Conclusion and Outlook -- Solutions to Exercises
Summary
Introduces graduate students and nonspecialists from various backgrounds to the field of mathematical and computational neurosciences. This book includes topics such as pulse-averaged equations and their application to movement coordination. It also provides an analysis of models versus the real neurophysiological system
Bibliography
Includes bibliographical references (pages 317-328) and index
