Details

Subject(s)

• Computational neuroscience [Browse]

Summary note

Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.

Bibliographic references

Includes bibliographical references (pages 307-312) and index.

Source of description

Print version record.

Contents

• Cover
• Foreword
• Preface
• Acknowledgments
• Contents
• 1. Introduction
• 2. Computational Neuroscience and You
• 3. Basic Neuroscience
• 4. Computer Representations
• 5. The Soul of an Old Machine
• 6. Concept Neurons
• 7. Neural Coding
• 8. Our Friend the Limulus
• 9. Supervised Learning:Delta Rule and Back-Propagation
• 10. Associative Memory Networks
• 11. From Soap to Volts
• 12. Hodgkin-Huxley Model
• 13. Compartment Modeling
• 14. From Artificial Neural Network to Realistic Neural Network
• 15. Neural Circuits
• 16. The Basics
• References
• Glossary.

Show 20 more Contents items

Other title(s)

Springer book archives.

ISBN

• 0387227334 ((electronic bk.))
• 9780387227337 ((electronic bk.))
• 1280009942
• 9781280009945

OCLC

70720661

Statement on language in description

Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage. Read more...