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Analyzing Neural Time Series Data: Theory and Practice (Issues in Clinical and Cognitive Neuropsychology) (English Edition) [Format Kindle]

Mike X Cohen

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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.

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Amazon.com: 4.5 étoiles sur 5  11 commentaires
4 internautes sur 4 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 This is a wonderful book. It covers not only the mathematical aspects ... 20 décembre 2014
Par J. M. Almira - Publié sur Amazon.com
This is a wonderful book. It covers not only the mathematical aspects of EEG signal processing but also the physiological bases of it, and the author makes this using a language which is understandable by non-mathematicians and it is also precise and clear.
I am a mathematician starting to work on the topic and I am completely sure that this work will increase and reinforce both my understanding of this subject, and my increasing love for it! I strongly recommend this book to everybody interested on EEGs. I just would like to add that this book has a very good complement in another one, published by the very same author and entitled "Fundamentals of Time-Frequency Analyses in Matlab/Octave" (Sinc press, 2014, there exists only Kindle version of it).
3 internautes sur 3 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 A conclusive review 21 mars 2014
Par Ali Mohebi - Publié sur Amazon.com
Format:Relié|Achat vérifié
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.
1 internautes sur 1 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Great guidebook, definitely recommended for graduate students 12 juillet 2014
Par Zack - Publié sur Amazon.com
Format:Relié|Achat vérifié
I'm a grad student and this book is absolutely perfect for someone in my position. Many of the issues I've come across when looking at neurological data are covered here with great explanations at how to solve them and why these solutions are used. It's fairly easy to read, I feel like it is concise without being imprecise and has plenty of useful illustrations. I appreciate that it is written with actual application of the techniques kept in mind, it feels like a very good guidebook to practical analysis. I wish I had picked up this book at the start of my grad school experience rather than the middle, as this would've made things much more smooth.
1 internautes sur 1 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 a great book for resaerchers who conduct EEG/MEG stduies 6 mars 2014
Par Yihui Hung - Publié sur Amazon.com
Format:Format Kindle|Achat vérifié
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.
1 internautes sur 1 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 great book!! 2 mai 2014
Par Raffaele - Publié sur Amazon.com
Format:Relié|Achat vérifié
the first part is great, clear and easy to understand [it gives a lot of insights].
The second part is more cryptic, but overall I liked it.

The matlab code is a bit chaotic and with few comments, is not ever easy to follow, in particular in the second half of the book.
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