Weakly Connected Neural Networks
By: by Frank C. Hoppensteadt, Eugene M. Izhikevich
Contributors: Izhikevich, Eugene M.
Series: Applied Mathematical Sciences, 0066-5452 -- 126; Applied mathematical sciences (Springer-Verlag New York Inc.) -- 126.
Publisher: Springer New York; Imprint; Springer
Published: 1997
Place of publication: New York, NY
Language: eng
Format: [electronic resource] /
Number of pages: 400
ISBN-13: 9781461218289
Subjects: Mathematics; Global analysis (Mathematics); Neurosciences
Description: This book is devoted to local and global analysis of weakly connected systems with applications to neurosciences. Using bifurcation theory and canonical models as the major tools of analysis, it presents systematic and well motivated development of both weakly connected system theory and mathematical neuroscience. Bifurcations in neuron and brain dynamics, synaptic organizations of the brain, and the nature of neural codes are among the many important issues addressed. The authors offer the reader classical results as well as some of the most recent developments in the field. The book will be useful to researchers and graduate students in various branches of mathematical neuroscience.
Table of contents: title: Dedication; title: Preface; title: Acknowledgment; title: Introduction; title: Models in Mathematical Biology; title: Ordinary Language Models; title: Qualifications; title: Dale's Principle; title: Weakness of Synaptic Connections; title: How small is E?- Size of PSP; title: A Common Misinterpretation; title: Spike Delays; title: Changes of Synaptic Efficacy; title: Empirical Models; title: Activities of Neurons.