The NEURON Book

Книга NEURON
Nicholas T. Carnevale, Michael L. Hines
2006-01-12

NEURON simulation environmentbiological neuron modelingbiophysical neuron modelscomputational neuroscienceneural network modeling
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.
1
A problem-solving approach with numerous executable examples supports learning and independent experimentation.
2
It explains how to construct and apply empirically based neural models, covering both software mechanisms and model specification.
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The book is designed for neuroscience investigators, teachers, and students without prior programming or numerical-methods training.
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The book provides an authoritative reference for NEURON, a widely used environment for simulating biological neurons and neural networks.
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The material addresses practical representation of neuronal anatomy and biophysical properties in computational models.

NEURON simulation environment for modeling biological neurons and neural networks

Construction and application of empirically based neuron and neural-network models, including specification of their anatomical and biophysical properties

Publication Details
Publication Date
2006-01-12
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Authors
Nicholas T. Carnevale
Michael L. Hines
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