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Analyzing Neural Time Series Data - Theory and Practice (Hardcover)
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Analyzing Neural Time Series Data - Theory and Practice (Hardcover)
Series: The MIT Press
Expected to ship within 9 - 15 working days
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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-,
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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