Description
Book SynopsisOffers an introduction to Matlab[registered], the standard for scientific computing, written specifically for students and researchers in neuroscience and related fields. This book serves as the comprehensive study manual and teaching resource for the use of Matlab in the neurosciences and psychology.
Trade Review"...a handy resource for instructors of neuroscience, particularly those interested in more intense data analysis and/or neural modeling. 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 course in 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
Table of ContentsPrefacePart I: FundamentalsIntroductionTutorialPart II: Data Collection with MatlabVisual Search and Pop OutAttentionPsychophysicsSignal Detection Theory Part III: Data Analysis with MatlabFrequency Analysis Part IFrequency Analysis Part II: Non-stationary Signals and SpectrogramsWaveletsConvolutionIntroduction to Phase Plane AnalysisExploring the Fitzhugh-Nagumo ModelNeural Data Analysis: EncodingPrincipal Components AnalysisInformation TheoryNeural Decoding: Discrete variablesNeural Decoding: Continuous variablesFunctional Magnetic ImagingPart IV: Data Modeling with MatlabVoltage-Gated Ion ChannelsModels of a Single NeuronModels of the RetinaSimplified Models of Spiking NeuronsFitzhugh-Nagumo Model: Traveling WavesDecision TheoryMarkov ModelModeling Spike Trains as a Poisson ProcessSynaptic TransmissionNeural Networks: Unsupervised learningNeural Network: Supervised LearningAppendicesAppendix 1: Thinking in MatlabAppendix 2: Linear Algebra Review
