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 many 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. This book will aid researchers and students in achieving the fluency required to meet the computational needs of neuroscience practitioners. Completely revised and expanded second edition keeps up with developments within neuroscience as well as MATLABAll computational approaches explained by using genuine experimental data, providing the unique look and feel of real empirical dataThe first comprehensive textbook on MATLAB with a focus on its applications in neuroscience and psychologyCareful didactic approach focused on problem solving Authors are award-winning educators with strong teaching experienceCompanion website with image bank, executable code, examples, and solutions available INDICE: Part I: Fundamentals1. Introduction2. MATLAB Tutorial3. Mathematics and Statistics Tutorial4. Programming Tutorial - Principles and Best Practices5. Visualization and Documentation TutorialPart II: Data Collection with MATLAB6. Collecting Reaction Times I: Visual Search7. Collecting Reaction Times II: Attention8. Elementary Psychophysics9. Advanced Psychophysics10. Signal Detection Theory Part III: Data Analysis with MATLAB11. Frequency Analysis I: Fourier Decomposition12. Frequency Analysis II: Nonstationary Signals and Spectrograms13. Frequency Analysis III: Wavelets14. Introduction to Phase Plane Analysis15. Exploring the Fitzhugh-Nagumo Model16. Convolution17. Principal Components Analysis18. Information Theory19. Neural Data Analysis I: Encoding20. Neural Data Analysis II: Binned spike data21. Neural Decoding Part I: Discrete Variables22. Neural Decoding Part II: Continuous Variables23. Local Field Potentials24. Functional Magnetic ImagingPart IV: Data Modeling with MATLAB25. Voltage-Gated Ion Channels26. Synaptic Transmission27. Models of a Single Neuron28. Models of the Retina29. Simplified Models of Spiking Neurons30. Fitzhugh-Nagumo Model: Traveling Waves31. Decision Theory32. Markov Models33. Modeling Spike Trains as a Poisson Process34. Exploring the Wilson-Cowan Equations35. Forest Fire Lab36. Neural Networks Part I: Unsupervised Learning37. Neural Networks Part II: Supervised LearningAppendix A: Creating Publication-Quality FiguresAppendix B: Overview of Relevant ToolboxesAppendix C: Master Equation List

• ISBN: 978-0-12-383836-0
• Editorial: Academic Press
• Encuadernacion: Cartoné
• Páginas: 570
• Fecha Publicación: 30/12/2013
• Nº Volúmenes: 1
• Idioma: Inglés