
Brain Dynamics
Synchronization and Activity Patterns in Pulse-Coupled Neural Nets with Delays and Noise
Hermann Haken(Author)
Springer (Publisher)
1st Edition
Published on 5. September 2002
Book
Hardback
XII, 249 pages
978-3-540-43076-6 (ISBN)
Article exhausted; check for reprint
Description
This book addresses a large variety of models in mathematical and computational neuroscience. It is written for the experts as well as for graduate students wishing to enter this fascinating field of research. The author studies the behaviour of large neural networks composed of many neurons coupled by spike trains. An analysis of phase locking via sinusoidal couplings leading to various kinds of movement coordination is included.
Reviews / Votes
From the reviews:
"This book focuses on synchronization of coupled systems of neuronal phase models the author calls 'lighthouse models.' . the book is an interesting read, and it will be of interest to computational neuroscientists working in synchrony and maybe mean-field models." (Andrea K. Barreiro, SIAM Review, Vol. 52 (2), 2010)More details
Series
Language
English
Place of publication
Heidelberg
Germany
Publishing group
Springer Berlin
Target group
Research
Illustrations
82
82 s/w Abbildungen
82 illus.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Thickness: 17 mm
Weight
503 gr
ISBN-13
978-3-540-43076-6 (9783540430766)
DOI
10.1007/978-3-540-46284-2
Schweitzer Classification
Other editions
New editions

Book
01/2008
2nd Edition
Springer
€53.49
Shipment within 10-15 days
Additional editions

Hermann Haken
Brain Dynamics
Synchronization and Activity Patterns in Pulse-Coupled Neural Nets with Delays and Noise
Book
10/2006
Springer
€53.45
Article exhausted; check for reprint
Content
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.- Phase Locking, Coordination and Spatio-Temporal Patterns.- Phase Locking via Sinusoidal Couplings.- Pulse-Averaged Equations.- Conclusion.- The Single Neuron.- Conclusion and Outlook.