MATLAB for Neuroscientists: An Introduction to Scientific Computing in MATLAB

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 applicationsProblem-based approach with many examples from neuroscience and cognitive psychology using real dataIllustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

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