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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-, time-frequency- and synchronization-based 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 single-subject-level and group-level 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.
Books with free ebook downloads available Analyzing Neural Time Series Data: Theory and Practice (Issues in Clinical and Cognitive Neuropsychology) [Kindle Edition] Free PDF
I have had my training as a EE major specializing in signal processing and moved on to do experimental work in neuroscience. Having said that I feel confident in both signal processing and electrophysiology. Mike Cohen has done a great job collecting almost all the useful techniques needed for different types of neural signal processing. An amazing feature of the book as promised on the cover is how Mike has managed to masterfully merge theory and practice without losing accuracy in either. The book, in my opinion, is a must have on the bookshelf of every investigator/student who deals with one sort of neural data.
By Ali Mohebi
The book is clearly written for people with limited mathematical or engineer trainings to understand advanced EEG/MEG data analyses. As a non native English speaker, I have no problem to understand the content even though I never perform many of the analyses mentioned in the book. The book is well organized that readers could either read chapter by chapter or choose one of the chapters you are interested to read and will not by interfered by unknowing the preceding chapters. The book extends readers' horizon of the EEG/MEG data analyses and also provide enough depth by showing advantages and disadvantage between different methods.
By Yihui Hung