The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.
Sprache
Verlagsort
Zielgruppe
Illustrationen
170 s/w Abbildungen, 8 Tabellen
8 Tables, unspecified; 170 Line drawings, unspecified
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 30 mm
Gewicht
ISBN-13
978-0-521-84321-8 (9780521843218)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Nicholas T. Carnevale is Senior Research Scientist in the Department of Psychology at Yale University. He also directs the NEURON courses at the annual meetings of the Society of Neuroscience and the NEURON Summer Courses at the University of California, San Diego and University of Minnesota, Minneapolis. Michael L. Hines is Research Scientist in the Department of Computer Science at Yale University. His work is embodied in a program, NEURON, which enjoys wide use in the experimental and computational neuroscience community.
Autor*in
Yale University, Connecticut
Yale University, Connecticut
Preface; Acknowledgements; 1. A tour of the NEURON simulation environment; 2. The modeling perspective; 3. Expressing conceptual models in mathematical terms; 4. Essentials of numerical methods for neural modeling; 5. Representing neurons with a digital computer; 6. How to build and use models of individual cells; 7. How to control simulations; 8. How to initialize simulations; 9. How to expand NEURON's library of mechanisms; 10. Synaptic transmission and artificial spiking cells; 11. Modeling networks; 12. Hoc, NEURON's interpreter; 13. Object-oriented programming; 14. How to modify NEURON itself; Appendix 1. Mathematical analysis of IntFire4; Appendix 2. NEURON's built-in editor; References; Epilogue; Index.
