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Library | Item Barcode | Call Number | Material Type | Item Category 1 | Status |
|---|---|---|---|---|---|
Searching... | 30000010230539 | QP356 G33 2010 f | Open Access Book | Book | Searching... |
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Summary
Summary
Virtually all scientific problems in neuroscience require mathematical analysis, and all neuroscientists are increasingly required to have a significant understanding of mathematical methods. There is currently no comprehensive, integrated introductory book on the use of mathematics in neuroscience; existing books either concentrate solely on theoretical modeling or discuss mathematical concepts for the treatment of very specific problems. This book fills this need by systematically introducing mathematical and computational tools in precisely the contexts that first established their importance for neuroscience. All mathematical concepts will be introduced from the simple to complex using the most widely used computing environment, Matlab.
This book will provide a grounded introduction to the fundamental concepts of mathematics, neuroscience and their combined use, thus providing the reader with a springboard to cutting-edge research topics and fostering a tighter integration of mathematics and neuroscience for future generations of students.
Author Notes
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.
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 Tree |
| 9 The Active Dendritic Tree |
| 10 Reduced Single Neuron Models |
| 11 Probability and Random Variables |
| 12 Synaptic Transmission and Quantal Release |
| 13 Neuronal Calcium Signaling |
| 14 The Singular Value Decomposition and Applications |
| 15 Quantification of Spike Train Variability |
| 16 Stochastic Processes |
| 17 Membrane Noise |
| 18 Power and Cross Spectra |
| 19 Natural Light Signals and Phototransduction |
| 20 Firing Rate Codes and Early Vision |
| 21 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 |
