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.
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.
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