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MORE ABOUT THIS BOOK
Main description:
This is an excellent introduction for graduate students and nonspecialists to the field of mathematical and computational neurosciences. The book approaches the subject via pulsed-coupled neural networks, which have at their core the lighthouse and integrate-and-fire models. These allow for highly flexible modeling of realistic synaptic activity, synchronization and spatio-temporal pattern formation. The more advanced pulse-averaged equations are discussed.
Contents:
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.
PRODUCT DETAILS
Publisher: Springer (Springer-Verlag Berlin and Heidelberg GmbH & Co. K)
Publication date: November, 2010
Pages: 348
Weight: 534g
Availability: Available
Subcategories: Neuroscience, Radiology
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