DUBLIN--(BUSINESS WIRE)--Research and Markets (http://www.researchandmarkets.com/research/74c436/mathematics_for_ne) has announced the addition of Elsevier Science and Technology's new report "Mathematics for Neuroscientists" to their offering.
This book provides 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. The book alternates between mathematical chapters, introducing important concepts and numerical methods, and neurobiological chapters, applying these concepts and methods to specific topics. It covers topics ranging from classical cellular biophysics and proceeding up to systems level neuroscience. Starting at an introductory mathematical level, presuming no more than calculus through elementary differential equations, the level will build up as increasingly complex techniques are introduced and combined with earlier ones. Each chapter includes a comprehensive series of exercises with solutions, taken from the set developed by the authors in their course lectures. MATLAB code is included for each computational figure, to allow the reader to reproduce them. Biographical notes referring the reader to more specialized literature and additional mathematical material that may be needed either to deepen the reader's understanding or to introduce basic concepts for less mathematically inclined readers completes each chapter.
- A very didactic and systematic introduction to mathematical concepts of importance for the analysis of data and the formulation of concepts based on experimental data in neuroscience
- Provides introductions to linear algebra, ordinary and partial differential equations, Fourier transforms, probabilities and stochastic processes
- Introduces numerical methods used to implement algorithms related to each mathematical concept
- Illustrates numerical methods by applying them to specific topics in neuroscience, including Hodgkin-Huxley equations, probabilities to describe stochastic release, stochastic processes to describe noise in neurons, Fourier transforms to describe the receptive fields of visual neurons
- Provides implementation examples in MATLAB code, also included for download on the accompanying support website (which will be updated with additional code and in line with major MATLAB releases)
- Allows the mathematical novice to analyze their results in more sophisticated ways, and consider them in a broader theoretical framework
Key Topics Covered:
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
For more information visit http://www.researchandmarkets.com/research/74c436/mathematics_for_ne