About this book
This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology.
Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity.
An extensive online collection of Matlab programs generating the figures accompanies the book.
- Book Title An Introduction to Modeling Neuronal Dynamics
- Series Title Texts in Applied Mathematics
- Series Abbreviated Title Texts in Applied Math.
- DOI https://doi.org/10.1007/978-3-319-51171-9
- Copyright Information Springer International Publishing AG 2017
- Publisher Name Springer, Cham
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Hardcover ISBN 978-3-319-51170-2
- Softcover ISBN 978-3-319-84585-2
- eBook ISBN 978-3-319-51171-9
- Series ISSN 0939-2475
- Series E-ISSN 2196-9949
- Edition Number 1
- Number of Pages XIII, 457
- Number of Illustrations 170 b/w illustrations, 186 illustrations in colour
Mathematical Models of Cognitive Processes and Neural Networks
Mathematical and Computational Biology
Statistical Physics and Dynamical Systems
Vibration, Dynamical Systems, Control
- Buy this book on publisher's site