Overview
Mathematics for Neuroscientists, Second Edition, presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons, neural networks and their relation to behavior. The book contains more than 200 figures generated using Matlab code available to the student and scholar. Mathematical concepts are introduced hand in hand with neuroscience, emphasizing the connection between experimental results and theory.
Full Product Details
Author: Fabrizio Gabbiani (Baylor College of Medicine, Houston, TX, USA) ,
Steven James Cox (Computational and Applied Mathematics, Rice University, Houston, TX, USA)
Publisher: Elsevier Science Publishing Co Inc
Imprint: Academic Press Inc
Edition: 2nd edition
Weight: 1.950kg
ISBN: 9780128018958
ISBN 10: 012801895
Pages: 628
Publication Date: 27 February 2017
Audience:
College/higher education
,
Tertiary & Higher Education
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
I really think this book is very, very important. This is precisely what has been missing from the field and is badly needed. Non-physicists or non-mathematicians coming to neuroscience try hard to get up to speed in the basic maths needed to get by but give up because there is no clear explication of this. --Dr. Kevin Franks, research fellow, Richard Axel's laboratory Columbia University, NYC The idea of presenting sufficient maths to understand the theoretical neuroscience, alongside the neuroscience itself, is appealing. The inclusion of Matlab code for all examples and computational figures is an excellent idea. Many readers will want to use and explore the code, either to directly aid their understanding, or as the basis for their own ongoing research, and Matlab is a widely used tool in this area. --David Corney, research fellow, Institute of Ophthalmology, University College London
I really think this book is very, very important. This is precisely what has been missing from the field and is badly needed. Non-physicists or non-mathematicians coming to neuroscience try hard to get up to speed in the basic maths needed to get by but give up because there is no clear explication of this. --Dr. Kevin Franks, research fellow, Richard Axel's laboratory Columbia University, NYC The idea of presenting sufficient maths to understand the theoretical neuroscience, alongside the neuroscience itself, is appealing. The inclusion of Matlab code for all examples and computational figures is an excellent idea. Many readers will want to use and explore the code, either to directly aid their understanding, or as the basis for their own ongoing research, and Matlab is a widely used tool in this area. --David Corney, research fellow, Institute of Ophthalmology, University College London
Amazon Editorial Reviews for First Edition: I really think this book is very, very important. This is precisely what has been missing from the field and is badly needed. --Dr. Kevin Franks, research fellow, Richard Axel's laboratory Columbia University, NYC The idea of presenting sufficient maths to understand the theoretical neuroscience, alongside the neuroscience itself, is appealing. The inclusion of Matlab code for all examples and computational figures is an excellent idea. --David Corney, research fellow, Institute of Ophthalmology, University College London
Author Information
Dr. Gabbiani is Professor in the Department of Neuroscience at the Baylor College of Medicine. Having received the prestigious Alexander von Humboldt Foundation research prize in 2012, he just completed a one-year cross appointment at the Max Planck Institute of Neurobiology in Martinsried and has international experience in the computational neuroscience field. Together with Dr. Cox, Dr. Gabbiani co-authored the first edition of this bestselling book in 2010. Dr. Cox is Professor of Computational and Applied Mathematics at Rice University. Affiliated with the Center for Neuroscience, Cognitive Sciences Program, and the Ken Kennedy Institute for Information Technology, he is also Adjunct Professor of Neuroscience at the Baylor College of Medicine. In addition, Dr. Cox has served as Associate Editor for a number of mathematics journals, including the Mathematical Medicine and Biology and Inverse Problems. He previously authored the first edition of this title with Dr. Gabbiani.
