Overview

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
Dimensions:   Width: 21.60cm , Height: 3.30cm , Length: 27.60cm
Weight:   1.600kg
ISBN:  

9780123748829

ISBN 10:   0123748828
Pages:   498
Publication Date:   16 September 2010
Audience:   Professional and scholarly ,  Professional & Vocational
Replaced By:   9780128018958
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   In Print  
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

1 Introduction 2 The Passive Isopotential Cell 3 Differential Equations 4 The Active Isopotential Cell 5 The Quasi-Active Isopotential Cell 6 The Passive Cable 7 Fourier Series and Transforms 8 The Passive Dendritic Tree9 The Active Dendritic Tree 10 Reduced Single Neuron Models 11 Probability and Random Variables 12 Synaptic Transmission and Quantal Release 13 Neuronal Calcium Signaling14 The Singular Value Decomposition and Applications15 Quantification of Spike Train Variability 16 Stochastic Processes 17 Membrane Noise18 Power and Cross Spectra 19 Natural Light Signals and Phototransduction 20 Firing Rate Codes and Early Vision21 Models of Simple and Complex Cells 22 Stochastic Estimation Theory 23 Reverse-Correlation and Spike Train Decoding 24 Signal Detection Theory 25 Relating Neuronal Responses and Psychophysics 26 Population Codes 27 Neuronal Networks 28 Solutions to Selected Exercises

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. <br>--Dr. Kevin Franks, research fellow, Richard Axel's laboratory Columbia University, NYC <br> The idea of presenting sufficient maths to understand the theoretical neuroscience, alongside the neuroscience itself, is appealing.&nbsp;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. <br>--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.

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