Analyzing Neural Time Series Data: Theory and Practice (Issues in Clinical and Cognitive Neuropsychology),New

Analyzing Neural Time Series Data: Theory and Practice (Issues in Clinical and Cognitive Neuropsychology),New

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A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings.This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time, timefrequency and synchronizationbased analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists.Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform singlesubjectlevel and grouplevel analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the analyze now button.The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.

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We provide a 2-year limited warranty, from the date of purchase for all our products.

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Frequently Asked Questions

  • Q: What is the focus of 'Analyzing Neural Time Series Data'? A: The book focuses on the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings.
  • Q: Who is the author of this book? A: The author of the book is Mike X Cohen.
  • Q: What can readers expect to learn from this book? A: Readers can expect to learn how to analyze electrical brain signals, interpret results, and perform both single-subject-level and group-level analyses.
  • Q: Is prior knowledge in mathematics required to understand the content? A: No, the book is written in a way that is accessible to readers without extensive formal training in mathematics.
  • Q: Does the book include practical exercises? A: Yes, most chapters conclude with exercises that help reinforce the material covered.
  • Q: What programming language is used for examples in the book? A: The book uses Matlab programming for its examples and analyses.
  • Q: How many chapters are in the book? A: There are 38 chapters in the book, each covering a specific analysis topic.
  • Q: What topics are covered in the book? A: The book covers topics ranging from simple analyses to advanced methods, including convolution, Fourier transforms, and more.
  • Q: Is sample data and code provided? A: Yes, the book includes sample data and downloadable Matlab code for practical application.
  • Q: What is the publication date of the book? A: The book was published on January 17, 2014.