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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

Prix conseillé : EUR 62,48 De quoi s'agit-il ?
Prix éditeur - format imprimé : EUR 62,46
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Descriptions du produit

Revue de presse

For years, I have wished for a comprehensive and pragmatic volume that really explained in plain English the many complex techniques that are so often used in electrophysiological research. Although there are chapters in handbooks, and even entire books on digital signal processing, none are as comprehensive, pragmatic, lucid, or entertaining as Analyzing Neural Time Series Data.
John J. B. Allen, University of Arizona

This impressive book is something I have been hoping for for years. It is meticulously organized to lead the knowledgeable novice to time series analyses from concept to actual implementation. Importantly, it is written to assume little advance knowledge of the topic, but to result in actionable understanding. Michael X Cohen has done the community a great service.
George R. Mangun, University of California, Davis

This book provides a technically rigorous, practical, and thorough survey of the major computational and statistical methods used in the time-frequency analysis of electrophysiological signals. Written in a lucid and engaging manner, Cohen s treatment will prove essential reading for both students and seasoned scholars, offering the former a clear roadmap into this exciting area of research and offering the latter an invaluable reference for nearly all of the major techniques. In putting this treatise together Cohen has done a great service for the burgeoning field of cognitive electrophysiology.

--Michael J. Kahana, University of Pennsylvania

Présentation de l'éditeur

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.

Détails sur le produit

  • Format : Format Kindle
  • Taille du fichier : 11838 KB
  • Nombre de pages de l'édition imprimée : 600 pages
  • Editeur : The MIT Press; Édition : 1 (17 janvier 2014)
  • Vendu par : Amazon Media EU S.à r.l.
  • Langue : Anglais
  • ASIN: B00HZDIY26
  • Synthèse vocale : Activée
  • X-Ray :
  • Word Wise: Non activé
  • Composition améliorée: Non activé
  • Classement des meilleures ventes d'Amazon: n°274.827 dans la Boutique Kindle (Voir le Top 100 dans la Boutique Kindle)

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Commentaires en ligne

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Commentaires client les plus utiles sur Amazon.com (beta)
Amazon.com: 4.6 étoiles sur 5  12 commentaires
5 internautes sur 5 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).
4 internautes sur 4 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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