Front Cover -- MATLAB® for Neuroscientists -- Copyright Page -- Contents -- Preface to the First Edition -- Preface to the Second Edition -- About the Authors -- How to Use this Book -- Structural and Conceptual Considerations -- Layout and Style -- Companion Web Site -- I: Fundamentals -- 1 Introduction -- 2 MATLAB Tutorial -- 2.1 Goal of this Chapter -- 2.2 Purpose and Philosophy of MATLAB -- 2.2.1 Getting Started -- 2.2.2 MATLAB as a Calculator -- 2.2.3 Defining Matrices -- 2.2.4 Basic Matrix Algebra -- 2.2.5 Indexing -- 2.3 Graphics and Visualization -- 2.3.1 Basic Visualization -- 2.4 Function and Scripts -- 2.4.1 Scripts -- 2.4.2 Functions -- 2.4.3 Control Structures -- 2.4.4 Advanced Plotting -- 2.4.5 Interactive Programs -- 2.5 Data Analysis -- 2.5.1 Importing and Storing Data -- 2.6 A Word on Function Handles -- 2.7 The Function Browser -- 2.8 Summary -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 3 Mathematics and Statistics Tutorial -- 3.1 Introduction -- 3.2 Linear Algebra -- 3.2.1 Matrices, Vectors, and Arrays -- 3.2.2 Transposition -- 3.2.3 Addition -- 3.2.4 Scalar Multiplication -- 3.2.5 Matrix Multiplication -- 3.2.6 Geometrical Interpretation of Matrix Multiplication -- 3.2.7 The Determinant -- 3.2.8 Eigenvalues and Eigenvectors -- 3.2.9 Applications of Eigenvectors: Eigendecomposition -- 3.2.10 Applications of Eigenvectors: PCA -- 3.3 Probability and Statistics -- 3.3.1 Introduction -- 3.3.2 Random Variables -- 3.3.2.1 Sample Estimates of Population Parameters -- 3.3.2.2 Joint and Conditional Probabilities -- 3.3.3 The Poisson Distribution -- 3.3.4 Normal Distribution -- 3.3.5 Confidence Values -- 3.3.6 Significance Testing -- 3.3.6.1 Student's t Distribution -- 3.3.6.2 ANOVA Testing -- 3.3.7 Linear Regression -- 3.3.8 Introduction to Bayesian Reasoning -- 3.3.9 Outlook.

MATLAB Functions, Commands, and Operators Covered in This Chapter -- 4 Programming Tutorial: Principles and Best Practices -- 4.1 Goals of this Chapter -- 4.2 Organizing Code -- 4.2.1 A Few Words about Maintenance -- 4.2.2 Variables and How to Name Them -- 4.2.3 Understanding Scope -- 4.2.4 Script or Function? -- 4.2.5 The Art of Commenting -- 4.3 Organizing More Code: Bigger Projects -- 4.3.1 Why Reuse Code? -- 4.3.2 Coupling and Cohesion -- 4.3.3 Separation of Concerns -- 4.3.4 Limiting Side Effects, or the Perils of Global State -- 4.3.5 Objects -- 4.3.5.1 Creating Objects -- 4.3.5.2 Inheritance -- 4.3.5.3 Passing Objects Around: The Handle Class -- 4.3.5.4 Summary -- 4.4 Taming Errors -- 4.4.1 An Introduction to the Debugger -- 4.4.2 Logging -- 4.4.3 Edge Cases and Unit Testing -- 4.4.4 A Few Words about Precision -- 4.4.5 Suggestions for Optimization -- 4.4.5.1 Vectorizing Matrix Operations -- 4.4.5.2 Conditional Expressions -- 4.4.5.3 Extracting Subsets from Arrays -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 5 Visualization and Documentation Tutorial -- 5.1 Goals of This Chapter -- 5.2 Visualization -- 5.3 Documentation -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- II: Data Collection with MATLAB -- 6 Collecting Reaction Times I:Visual Search and Pop Out -- 6.1 Goals of this Chapter -- 6.2 Background -- 6.3 Exercises -- 6.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 7 Collecting Reaction Times II: Attention -- 7.1 Goals of this Chapter -- 7.2 Background -- 7.2.1 So What is the Posner Paradigm? -- 7.3 Exercises -- 7.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 8 Psychophysics -- 8.1 Goals of this Chapter -- 8.2 Background -- 8.3 Exercises -- 8.4 Project.

MATLAB Functions, Commands, and Operators Covered in this Chapter -- 9 Psychophysics with GUIs -- 9.1 Goals of This Chapter -- 9.2 Introduction and Background -- 9.3 GUI Basics -- 9.4 Using a GUI to Track an IP Address -- 9.5 Using a GUI for Psychophysics -- 9.6 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 10 Signal Detection Theory -- 10.1 Goals of This Chapter -- 10.2 Background -- 10.3 Exercises -- 10.4 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- III: Data Analysis with MATLAB -- 11 Frequency Analysis Part I: Fourier Decomposition -- 11.1 Goals of this Chapter -- 11.2 Background -- 11.2.1 Real Fourier Series -- 11.3 Exercises -- 11.3.1 Complex Fourier Transform -- 11.3.2 Fast Fourier Transform -- 11.3.3 The Inverse DFT -- 11.3.4 Amplitude Spectrum -- 11.3.5 Power -- 11.3.6 Phase Analysis and Coherence -- 11.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 12 Frequency Analysis Part II: Nonstationary Signals and Spectrograms -- 12.1 Goal of this Chapter -- 12.2 Background -- 12.2.1 The Fourier Transform: Stationary and Ergodic -- 12.2.2 Windows -- 12.3 Exercises -- 12.3.1 Limitations of the STFT -- 12.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 13 Wavelets -- 13.1 Goals of This Chapter -- 13.2 Background -- 13.2.1 What is a Wavelet? -- 13.2.2 The Continuous Wavelet Transform -- 13.2.3 Choosing a Wavelet -- 13.2.4 Scalograms -- 13.2.5 The Discrete Wavelet Transform -- 13.2.6 Wavelet Toolbox -- 13.3 Exercises -- 13.4 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 14 Introduction to Phase Plane Analysis -- 14.1 Goal of this Chapter -- 14.2 Background -- 14.3 Exercises -- 14.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter.

15 Exploring the Fitzhugh-Nagumo Model -- 15.1 Goal of this Chapter -- 15.2 Background -- 15.3 Exercises -- 15.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 16 Convolution -- 16.1 Goals of this Chapter -- 16.2 Background -- 16.2.1 The Visual System and Receptive Fields -- 16.2.2 The Mach Band Illusion -- 16.3 Exercises -- 16.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 17 Neural Data Analysis I: Encoding -- 17.1 Goals of this Chapter -- 17.2 Background -- 17.3 Exercises -- 17.3.1 Raster Plot -- 17.3.2 Peri-Event Time Histogram -- 17.3.3 Tuning Curves -- 17.3.4 Curve Fitting -- 17.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 18 Neural Data Analysis II: Binned Spike Data -- 18.1 Goals of this Chapter -- 18.2 Background -- 18.2.1 Exponential Function -- 18.2.2 Poisson Distribution -- 18.2.3 Log-Linear Models -- 18.2.4 Predicting the PETH -- 18.3 Exercises -- 18.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 19 Principal Components Analysis -- 19.1 Goals of this Chapter -- 19.2 Background -- 19.2.1 Covariance Matrices -- 19.2.2 Principal Components -- 19.2.3 Spike Sorting -- 19.3 Exercises -- 19.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 20 Information Theory -- 20.1 Goals of this Chapter -- 20.2 Background -- 20.2.1 Motor Cortical Data -- 20.2.2 Spike Density Functions -- 20.2.3 Joint, Marginal, and Conditional Distributions -- 20.2.4 Information Theory -- 20.2.5 Understanding Bias -- 20.2.6 Shuffle Correction -- 20.3 Exercises -- 20.4 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 21 Neural Decoding I: Discrete Variables -- 21.1 Goals of this Chapter -- 21.2 Background -- 21.2.1 Population Vector -- 21.2.2 Maximum Likelihood -- 21.2.3 Data.

21.3 Exercises -- 21.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 22 Neural Decoding II: Continuous Variables -- 22.1 Goals of This Chapter -- 22.2 Background -- 22.2.1 Linear Filter -- 22.2.2 Maximum a Posteriori (MAP) Estimation -- 22.2.3 Recursive Bayesian Estimation -- 22.3 Exercises -- 22.4 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 23 Local Field Potentials -- 23.1 Goals of This Chapter -- 23.2 Background -- 23.2.1 Evoked Potentials -- 23.2.2 Directional tuning -- 23.2.3 Spectrograms -- 23.3 Exercises -- 23.4 Project -- MATLAB Functions, Commands, and Operators Covered in this Chapter -- 24 Functional Magnetic Resonance Imaging -- 24.1 Goals of This Chapter -- 24.2 Background -- 24.2.1 Basic Physics of the MRI Signal -- 24.2.2 BOLD Signal (fMRI) -- 24.2.3 Preprocessing of the BOLD Signal -- 24.2.4 Experimental Designs -- 24.2.5 Analysis Methods -- 24.2.6 Multiple Comparisons -- 24.2.7 Caveats and Limitations -- 24.3 Exercises -- 24.4 Project -- 24.4.1 Methods Used to Collect fMRI Data -- 24.4.2 Group Analysis -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- IV: Data Modeling with MATLAB -- 25 Voltage-Gated Ion Channels -- 25.1 Goal of This Chapter -- 25.2 Background -- 25.2.1 The Model -- 25.2.2 Kv Channel -- 25.2.3 The Nav Channel -- 25.2.4 Solving Differential Equations Numerically -- 25.3 Exercises -- 25.4 Project -- Matlab Functions, Commands, and Operators Covered in This Chapter -- 26 Synaptic Transmission -- 26.1 Goals of This Chapter -- 26.2 Background -- 26.3 Exercises -- 26.3.1 Modeling Neurotransmitter Release -- 26.3.2 Modeling Random Variables -- 26.3.3 Modeling the Motion of a Single Molecule -- 26.3.4 Modeling Diffusion -- 26.4 Project -- MATLAB Functions, Commands, and Operators Covered in This Chapter -- 27 Modeling a Single Neuron.

27.1 Goal of This Chapter.