# MATLAB for Neuroscientists

## 1st Edition

### An Introduction to Scientific Computing in MATLAB

**Authors:**Pascal Wallisch Michael Lusignan Marc Benayoun Tanya Baker Adam Dickey Nicholas Hatsopoulos

**Hardcover ISBN:**9780123745514

**eBook ISBN:**9780080923284

**Imprint:**Academic Press

**Published Date:**29th October 2008

**Page Count:**400

## Description

This is the first comprehensive teaching resource and textbook for the teaching of MATLAB in the Neurosciences and in Psychology. MATLAB is unique in that it can be used to learn the entire empirical and experimental process, including stimulus generation, experimental control, data collection, data analysis and modeling. Thus a wide variety of computational problems can be addressed in a single programming environment. The idea is to empower advanced undergraduates and beginning graduate students by allowing them to design and implement their own analytical tools. As students advance in their research careers, they will have achieved the fluency required to understand and adapt more specialized tools as opposed to treating them as "black boxes".

Virtually all computational approaches in the book are covered by using genuine experimental data that are either collected as part of the lab project or were collected in the labs of the authors, providing the casual student with the look and feel of real data. In some cases, published data from classical papers are used to illustrate important concepts, giving students a computational understanding of critically important research.

## Key Features

- The first comprehensive textbook on MATLAB with a focus for its application in neuroscience
- Problem based educational approach with many examples from neuroscience and cognitive psychology using real data
- Authors 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
- About the Authors
- How to Use This Book
- Structural and Conceptual Considerations
- Layout and Style
- Companion Website

- Chapter 1. Introduction
- Publisher Summary

- Chapter 2. MATLAB Tutorial
- Publisher Summary
- 2.1 Goal of this Chapter
- 2.2 Basic Concepts
- 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. Visual Search and Pop Out
- Publisher Summary
- 3.1 GOALS OF THIS CHAPTER
- 3.2 BACKGROUND
- 3.3 EXERCISES
- 3.4 PROJECT
- MATLAB FUNCTIONS, COMMANDS, AND OPERATORS COVERED IN THIS CHAPTER

- Chapter 4. Attention
- Publisher Summary
- 4.1 GOALS OF THIS CHAPTER
- 4.2 BACKGROUND
- 4.3 EXERCISES
- 4.4 PROJECT
- MATLAB FUNCTIONS, COMMANDS, AND OPERATORS COVERED IN THIS CHAPTER

- Chapter 5. Psychophysics
- Publisher Summary
- 5.1 Goals of this Chapter
- 5.2 Background
- 5.3 Exercises
- 5.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 6. Signal Detection Theory
- Publisher Summary
- 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. Frequency Analysis Part I: Fourier Decomposition
- Publisher Summary
- 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. Frequency Analysis Part II: Nonstationary Signals and Spectrograms
- Publisher Summary
- 8.1 Goal of this Chapter
- 8.2 Background
- 8.3 Exercises
- 8.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 9. Wavelets
- Publisher Summary
- 9.1 Goals of this Chapter
- 9.2 Background
- 9.3 Exercises
- 9.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 10. Convolution
- Publisher Summary
- 10.1 Goals of this Chapter
- 10.2 Background
- 10.3 Exercises
- 10.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 11. Introduction to Phase Plane Analysis
- Publisher Summary
- 11.1 Goal of this Chapter
- 11.2 Background
- 11.3 Exercises
- 11.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 12. Exploring the Fitzhugh-Nagumo Model
- Publisher Summary
- 12.1 The Goal of this Chapter
- 12.2 Background
- 12.3 Exercises
- 12.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 13. Neural Data Analysis: Encoding
- Publisher Summary
- 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. Principal Components Analysis
- Publisher Summary
- 14.1 Goals of this Chapter
- 14.2 Background
- 14.3 Exercises
- 14.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 15. Information Theory
- Publisher Summary
- 15.1 Goals of this Chapter
- 15.2 Background
- 15.3 Exercises
- 15.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 16. Neural Decoding Part I: Discrete Variables
- Publisher Summary
- 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 Decoding Part II: Continuous Variables
- Publisher Summary
- 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. Functional Magnetic Imaging
- Publisher Summary
- 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. Voltage-Gated Ion Channels
- Publisher Summary
- 19.1 Goal of this Chapter
- 19.2 Background
- 19.3 Exercises
- 19.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 20. Models of a Single Neuron
- Publisher Summary
- 20.1 Goal of this Chapter
- 20.2 Background
- 20.3 Exercises
- 20.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 21. Models of the Retina
- Publisher Summary
- 21.1 Goal of this Chapter
- 21.2 Background
- 21.3 Exercises
- 21.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 22. Simplified Model of Spiking Neurons
- Publisher Summary
- 22.1 Goal of this Chapter
- 22.2 Background
- 22.3 Exercises
- 22.4 Project
- Matlab Functions, Commands, And Operators Covered in this Chapter

- Chapter 23. Fitzhugh-Nagumo Model: Traveling Waves
- Publisher Summary
- 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. Decision Theory
- Publisher Summary
- 24.1 Goals of this Chapter
- 24.2 Background
- 24.3 Exercises
- 24.4 Project
- MATLAB functions, commands, and Operators Covered in this Chapter

- Chapter 25. Markov Models
- Publisher Summary
- 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. Modeling Spike Trains as a Poisson Process
- Publisher Summary
- 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. Synaptic Transmission
- Publisher Summary
- 27.1 Goals of this Chapter
- 27.2 Background
- 27.3 Exercises
- 27.4 Project: Combining Vesicular Release with Diffusion
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 28. Neural Networks Part I: Unsupervised Learning
- Publisher Summary
- 28.1 Goals of this Chapter
- 28.2 Background
- 28.3 Trying out a neural network
- 28.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Chapter 29. Neural Network Part II: Supervised Learning
- Publisher Summary
- 29.1 Goals of this Chapter
- 29.2 Background
- 29.3 Exercises
- 29.4 Project
- MATLAB Functions, Commands, and Operators Covered in this Chapter

- Appendix A. Thinking in MATLAB
- A.1 Alternatives to MATLAB
- A.2 A Few Words about Precision

- Appendix B. Linear Algebra Review
- B.1 Matrix Dimensions
- B.2 Multiplication
- B.3 Addition
- B.4 Transpose
- B.5 Geometrical Interpretation of Matrix Multiplication
- B.6 Determinant
- B.7 Inverse
- B.8 Eigenvalues and Eigenvectors
- B.9 Eigendecomposition of a Matrix

- Appendix C. Master Equation List
- Chapter 6
- Chapter 7
- Chapter 8
- Chapter 9
- Chapter 10
- Chapter 11
- Chapter 12
- Chapter 14
- Chapter 15
- Chapter 16
- Chapter 17
- Chapter 18
- Chapter 19
- Chapter 20
- Chapter 21
- Chapter 22
- Chapter 23
- Chapter 24
- Chapter 26
- Chapter 27
- Chapter 28
- Chapter 29

- References
- Preface References
- Chapter 1 References
- Chapter 2 References
- Chapter 3 References
- Chapter 4 References
- Chapter 5 References
- Chapter 6 References
- Chapter 7 References
- Chapter 8 References
- Chapter 9 References
- Chapter 10 References
- Chapter 11 References
- Chapter 12 References
- Chapter 13 References
- Chapter 14 References
- Chapter 15 References
- Chapter 16 References
- Chapter 17 References
- Chapter 18 References
- Chapter 19 References
- Chapter 20 References
- Chapter 21 References
- Chapter 22 References
- Chapter 23 References
- Chapter 24 References
- Chapter 25 References
- Chapter 26 References
- Chapter 27 References
- Chapter 28 References
- Chapter 29 References

- Index

## Details

- No. of pages:
- 400

- Language:
- English

- Copyright:
- © Academic Press 2009

- Published:
- 29th October 2008

- Imprint:
- Academic Press

- eBook ISBN:
- 9780080923284

- Hardcover ISBN:
- 9780123745514

## About the Author

### 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

### Affiliations and Expertise

The University of Chicago, IL, USA

## Reviews

“The book is clear, cogent, and systematic. It provides much more than the essential nuts-and-bolts—it also leads the reader to learn to think about the empirical enterprise writ large...This book should be given a privileged spot on the bookshelf of every teacher, student, and researcher in the behavioral and cognitive sciences.” — Stephen M. Kosslyn, John Lindsley Professor of Psychology, Dean of Social Science, Harvard University, Cambridge, MA, USA “This is an excellent book that should be on the desk of any neuroscientist or psychologist who wants to analyze and understand his or her own data by using MATLAB...Several books with MATLAB toolboxes exist; I find this one special both for its clarity and its focus on problems related to neuroscience and cognitive psychology.” — Nikos Logothetis, Director, Max Planck Institute for Biological Cybernetics, Tübingen, Germany “MATLAB for Neuroscientists provides a unique and relatively comprehensive introduction to the MATLAB programming language in the context of brain sciences...The book would work well as a supplementary source for an introductory coursein computational analysis and modeling in visual neuroscience, for graduate students or advanced undergraduates.” — Eero P. Simoncelli, Investigator, Howard Hughes Medical Institute; Professor, Neural Science, Mathematics, and Psychology, New York University, New York, USA