MATLAB for Neuroscientists

MATLAB for Neuroscientists

An Introduction to Scientific Computing in MATLAB

2nd Edition - November 1, 2013

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  • Authors: Pascal Wallisch, Michael Lusignan, Marc Benayoun, Tanya Baker, Adam Dickey, Nicholas Hatsopoulos
  • Hardcover ISBN: 9780123838360
  • eBook ISBN: 9780123838377

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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.

Key Features

  • The first complete volume on MATLAB focusing on neuroscience and psychology applications
  • Problem-based approach with many examples from neuroscience and cognitive psychology using real data
  • Illustrated in full color throughout
  • Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Readership

Undergraduate and graduate students in systems, cognitive, and behavioral neuroscience, cognitive psychology, and related fields, as well as researchers in these fields who use MATLAB

Table of Contents

  • Preface to the Second Edition

    Preface to the First Edition

    About the Authors

    How to Use this Book

    Structural and Conceptual Considerations

    Layout and Style

    Companion Web Site

    Part I: Fundamentals

    Chapter 1. Introduction

    Chapter 2. MATLAB Tutorial

    2.1 Goal of this Chapter

    2.2 Purpose and Philosophy of MATLAB

    2.3 Graphics and Visualization

    2.4 Function and Scripts

    2.5 Data Analysis

    2.6 A Word on Function Handles

    2.7 The Function Browser

    2.8 Summary

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 3. Mathematics and Statistics Tutorial

    3.1 Introduction

    3.2 Linear Algebra

    3.3 Probability and Statistics

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 4. Programming Tutorial: Principles and Best Practices

    4.1 Goals of this Chapter

    4.2 Organizing Code

    4.3 Organizing More Code: Bigger Projects

    4.4 Taming Errors

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    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

    Part II: Data Collection with MATLAB

    Chapter 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

    Chapter 7. Collecting Reaction Times II: Attention

    7.1 Goals of this Chapter

    7.2 Background

    7.3 Exercises

    7.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    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

    Chapter 9. Psychophysics with GUIs

    Abstract

    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

    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

    Part III: Data Analysis with MATLAB

    Chapter 11. Frequency Analysis Part I: Fourier Decomposition

    11.1 Goals of this Chapter

    11.2 Background

    11.3 Exercises

    11.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 12. Frequency Analysis Part II: Nonstationary Signals and Spectrograms

    12.1 Goal of this Chapter

    12.2 Background

    12.3 Exercises

    12.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 13. Wavelets

    13.1 Goals of This Chapter

    13.2 Background

    13.3 Exercises

    13.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    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

    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

    Chapter 16. Convolution

    16.1 Goals of this Chapter

    16.2 Background

    16.3 Exercises

    16.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 17. Neural Data Analysis I: Encoding

    17.1 Goals of this Chapter

    17.2 Background

    17.3 Exercises

    17.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 18. Neural Data Analysis II: Binned Spike Data

    18.1 Goals of this Chapter

    18.2 Background

    18.3 Exercises

    18.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 19. Principal Components Analysis

    19.1 Goals of this Chapter

    19.2 Background

    19.3 Exercises

    19.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 20. Information Theory

    20.1 Goals of this Chapter

    20.2 Background

    20.3 Exercises

    20.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 21. Neural Decoding I: Discrete Variables

    21.1 Goals of this Chapter

    21.2 Background

    21.3 Exercises

    21.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 22. Neural Decoding II: Continuous Variables

    22.1 Goals of This Chapter

    22.2 Background

    22.3 Exercises

    22.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 23. Local Field Potentials

    23.1 Goals of This Chapter

    23.2 Background

    23.3 Exercises

    23.4 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 24. Functional Magnetic Resonance Imaging

    24.1 Goals of This Chapter

    24.2 Background

    24.3 Exercises

    24.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Part IV: Data Modeling with MATLAB

    Chapter 25. Voltage-Gated Ion Channels

    25.1 Goal of This Chapter

    25.2 Background

    25.3 Exercises

    25.4 Project

    Matlab Functions, Commands, and Operators Covered in This Chapter

    Chapter 26. Synaptic Transmission

    26.1 Goals of This Chapter

    26.2 Background

    26.3 Exercises

    26.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 27. Modeling a Single Neuron

    27.1 Goal of This Chapter

    27.2 Background

    27.3 Exercises

    27.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 28. Models of the Retina

    28.1 Goal of This Chapter

    28.2 Background

    28.3 Exercises

    28.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 29. Simplified Model of Spiking Neurons

    29.1 Goal of This Chapter

    29.2 Background

    29.3 Exercises

    29.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 30. Fitzhugh-Nagumo Model: Traveling Waves

    30.1 Goals of This Chapter

    30.2 Background

    30.3 Exercises

    30.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 31. Decision Theory

    31.1 Goals of this Chapter

    31.2 Background

    31.3 Simple Accumulation of Evidence

    31.4 Free Response Tasks

    31.5 Multiple Iterators: The Race Model

    31.6 Cortical Models

    31.7 Project

    MATLAB Functions, Commands, and Operators Covered in this Chapter

    Chapter 32. Markov Models

    32.1 Goal of this Chapter

    32.2 Introduction

    32.3 Finding the Most Probable Path: The Viterbi Algorithm

    32.4 Hidden Markov Models

    32.5 Training an HMM: The Baum-Welch Algorithm

    32.6 A Simple Example

    32.7 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    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 Non-Homogeneous Poisson Processes: Time-Varying Rates of Activity

    33.7 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 34. Exploring the Wilson-Cowan Equations

    34.1 Goal of This Chapter

    34.2 Background

    34.3 The Model

    34.4 Exercises

    34.5 Projects

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 35. Neural Networks as Forest Fires: Stochastic Neurodynamics

    35.1 Goals of This Chapter

    35.2 Background

    35.3 Exercises

    35.4 Projects

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 36. Neural Networks Part I: Unsupervised Learning

    36.1 Goals of This Chapter

    36.2 Background

    36.3 Exercises

    36.4 Project

    MATLAB Functions, Commands, and Operators Covered in This Chapter

    Chapter 37. Neural Networks Part II: Supervised Learning

    37.1 Goals of This Chapter

    37.2 Background

    37.3 Exercises

    37.4 Project

    MATLAB Functions, Commands, and Operators covered in This Chapter

    Appendix A. Creating Publication-Quality Figures

    A.1 Introduction

    A.2 Figure Makeovers

    A.3 Saving Figures in the Desired Format

    A.4 How to Make Animated GIFs

    MATLAB Functions, Commands, and Operators Covered in This Appendix

    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 details

  • No. of pages: 570
  • Language: English
  • Copyright: © Academic Press 2013
  • Published: November 1, 2013
  • Imprint: Academic Press
  • Hardcover ISBN: 9780123838360
  • eBook ISBN: 9780123838377

About the Authors

Pascal Wallisch

Pascal Wallisch
Pascal Wallisch received his PhD from the University of Chicago, did postdoctoral work at the Center for Neural Science at New York University, and currently serves as a clinical assistant professor of Psychology at New York University. His research interests are at the intersection of Psychology and Neuroscience, specifically Cognitive and Computational Neuroscience. His current work focuses on motion perception, autism and the appraisal of film.

Affiliations and Expertise

New York University, NY, USA

Michael Lusignan

Affiliations and Expertise

The University of Chicago, IL, USA

Marc Benayoun

Affiliations and Expertise

The University of Chicago, IL, USA

Tanya Baker

Affiliations and Expertise

The Salk Institute for Biological Studies, La Jolla, CA, USA

Adam Dickey

Affiliations and Expertise

The University of Chicago, IL, USA

Nicholas Hatsopoulos

Nicholas Hatsopoulos

Affiliations and Expertise

The University of Chicago, IL, USA

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