Analyzing Neural Time Series Data: Theory and Practice (The MIT Press) 1st Edition

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.

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.

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.

Excellent primer to neural time series analysis. Good book for junior/senior undergrads and early graduate students interested in the topic -- really, any interested party with some basic signals analysis awareness, and that includes an hour or two watching YouTube videos on the topic.

I run a lab where we do EEG experiments. I'm having new undergrad RAs go through this in a reading group. It's a really useful and well-thought-out volume. It sits on the lab coffee table at all times! On-line content options and Matlab resources are really convenient too.

As a researcher in the field, this book gives you great practical advice on critical decision points (e.g. how to perform baseline correction, etc) that are not covered in traditional digital signal processing books. I highly recommend this quick read for anyone analyzing cognitive data from EEG or iEEG.

Very helpful book for signal processing in neuroscience. Very practical and easy to comprehend.

This book explains the mathematical basis of time series analysis for neuroscientists, not mathematicians. Material is presented informally - not a single proof to be found in the book. This is a plus for someone who wants to learn analysis techniques for neuroscience. Fully recommend for anyone who does or is interested in time-frequency analysis of MEG/EEG data. Excellent resource. Would absolutely buy again, a copy for everyone in my lab if I had the choice.

This book is extremely valuable for anyone attempting to perform EEG/MEG or LFP data analysis. It is clearly and accessibly written, and covers the most important pitfalls that you might encounter. I had prior knowledge about data analysis but I was missing a comprehensive summary of all the options one encounters during various analyses stages, especially all their benefits and drawbacks. Mike Cohen has seemingly provided all important aspects (and there are many of those) in one place and additionally provides very efficient MATLAB code. Even better, he also hosts a forum, to which readers can turn to if there are still open questions. I can highly recommend this book to anyonewho wants to get a thorough understanding of neural time series signal processing techniques.

I purchased this book just before embarking upon my first EEG analysis project. It literally saved me from hours of pain and misunderstandings. This book is a must buy for anyone working on EEG projects. Here Michael X Cohen covers the technical, computational and neuroscientific bases you will need in order to get your head around a complex topic. This book presents the neccessary info from the ground up in a way that is accessible to people of both technical and non-technical backgrounds. Furthermore code files are provided which can give you a serious leg-up in MATLAB and get you well on the way to analysing your data. EEG Analysis need not be a scary topic, armed with this book you will bring clarity to the darkest corners of time-series analysis!

One of the most comprehensive books in neural time series analysis. It is written in a simple, concise and clear way. Covers pretty much everything one needs to know (I'm working with EEG but the methods in the book are applicable to other types of neural data as well). The downloadable Matlab code that accompanies this publication is a big bonus as it helps to understand how to practically implement the mathematical concepts presented in the book. I absolutely love this book and will become a solid reference for all my data analysis from now on.

Very useful book, goes slowly over various time / frequency transformations for EEG and it includes a background on EEG / ERP analysis. Especially nice for those that would like to know how to implement time / frequency transformations at the "low level", for example without using matlab's fft function.

This book should be within easy reach of every student (or professor) from a Psychology background who is working with EEG data. It explains difficult concepts in a clear and straightforward way, and includes very useful examples and code which can be modified for bespoke analysis.