Book description
MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment.
This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners.
 The first complete volume on MATLAB focusing on neuroscience and psychology applications
 Problembased approach with many examples from neuroscience and cognitive psychology using real data
 Illustrated in full color throughout
 Careful tutorial approach, by authors who are awardwinning educators with strong teaching experience
Table of contents
 Cover image
 Title page
 Table of Contents
 Copyright
 Preface to the Second Edition
 Preface to the First Edition
 About the Authors
 How to Use this Book
 Part I: Fundamentals
 Part II: Data Collection with MATLAB

Part III: Data Analysis with MATLAB
 Chapter 11. Frequency Analysis Part I: Fourier Decomposition
 Chapter 12. Frequency Analysis Part II: Nonstationary Signals and Spectrograms
 Chapter 13. Wavelets
 Chapter 14. Introduction to Phase Plane Analysis
 Chapter 15. Exploring the FitzhughNagumo Model
 Chapter 16. Convolution
 Chapter 17. Neural Data Analysis I: Encoding
 Chapter 18. Neural Data Analysis II: Binned Spike Data
 Chapter 19. Principal Components Analysis
 Chapter 20. Information Theory
 Chapter 21. Neural Decoding I: Discrete Variables
 Chapter 22. Neural Decoding II: Continuous Variables
 Chapter 23. Local Field Potentials
 Chapter 24. Functional Magnetic Resonance Imaging

Part IV: Data Modeling with MATLAB
 Chapter 25. VoltageGated Ion Channels
 Chapter 26. Synaptic Transmission
 Chapter 27. Modeling a Single Neuron
 Chapter 28. Models of the Retina
 Chapter 29. Simplified Model of Spiking Neurons
 Chapter 30. FitzhughNagumo Model: Traveling Waves
 Chapter 31. Decision Theory
 Chapter 32. Markov Models

Chapter 33. Modeling Spike Trains as a Poisson Process
 33.1 Goals of this Chapter
 33.2 Background
 33.3 The Bernoulli Process: Events in Discrete Time
 33.4 The Poisson Process: Events in Continuous Time
 33.5 Picking Random Variables Without the Statistics Toolbox
 33.6 NonHomogeneous Poisson Processes: TimeVarying Rates of Activity
 33.7 Project
 MATLAB Functions, Commands, and Operators Covered in This Chapter
 Chapter 34. Exploring the WilsonCowan Equations
 Chapter 35. Neural Networks as Forest Fires: Stochastic Neurodynamics
 Chapter 36. Neural Networks Part I: Unsupervised Learning
 Chapter 37. Neural Networks Part II: Supervised Learning
 Appendix A. Creating PublicationQuality Figures

Appendix B. Relevant Toolboxes
 B.1 The Concept of Toolboxes
 B.2 Neural Network Toolbox
 B.3 Parallel Computing Toolbox
 B.4 Statistics Toolbox
 B.5 MATLAB Compiler
 B.6 Database Toolbox
 B.7 Signal Processing Toolbox
 B.8 Data Acquisition Toolbox
 B.9 Image Processing Toolbox
 B.10 Psychophysics Toolbox and MGL
 B.11 Chronux
 B.12 Mathworks File Exchange
 References
 Index
Product information
 Title: MATLAB for Neuroscientists, 2nd Edition
 Author(s):
 Release date: January 2014
 Publisher(s): Academic Press
 ISBN: 9780123838377
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