In this first matab Lab, I will introduce the very basics of
its relevance to computational problems that we encounter when studing problems in NeuroScience.


In addition I'l show where and how to find relevant information.


















Quotes

“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



Contents

Preface

Part I: Fundamentals
Introduction
Tutorial

Part II: Data Collection with Matlab
Visual Search and Pop Out
Attention
Psychophysics
Signal Detection Theory 

Part III: Data Analysis with Matlab
Frequency Analysis Part I
Frequency Analysis Part II: Non-stationary Signals and Spectrograms
Wavelets
Convolution
Introduction to Phase Plane Analysis
Exploring the Fitzhugh-Nagumo Model
Neural Data Analysis: Encoding
Principal Components Analysis
Information Theory
Neural Decoding: Discrete variables
Neural Decoding: Continuous variables
Functional Magnetic Imaging

Part IV: Data Modeling with Matlab
Voltage-Gated Ion Channels
Models of a Single Neuron
Models of the Retina
Simplified Models of Spiking Neurons
Fitzhugh-Nagumo Model: Traveling Waves
Decision Theory
Markov Model
Modeling Spike Trains as a Poisson Process
Synaptic Transmission
Neural Networks: Unsupervised learning
Neural Network: Supervised Learning

Appendices
Appendix 1: Thinking in Matlab
Appendix 2: Linear Algebra Review