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Analyzing neural time series data : theory and practice / Mike X. Cohen.

EBSCOhost Academic eBook Collection (North America) Available online

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Ebook Central University Press Available online

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MIT Press Direct (eBooks) Available online

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Format:
Book
Author/Creator:
Cohen, Mike X., 1979- author.
Series:
Issues in clinical and cognitive neuropsychology
Language:
English
Subjects (All):
Neural networks (Neurobiology).
Neural networks (Computer science).
Computational neuroscience.
Artificial intelligence--Biological applications.
Artificial intelligence.
Physical Description:
1 online resource (xviii, 578 p.) : ill.
Place of Publication:
Cambridge, Massachusetts : The MIT Press, [2014]
Summary:
"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."-- Publisher's Web site.
Contents:
I Introduction
1 The Purpose of This Book, Who Should Read It, and How to Use It
2 Advantages and Limitations of Time- and Time-Frequency-Domain Analyses
3 Interpreting and Asking Questions about Time-Frequency Results
4 Introduction to Matlab Programming
5 Introduction to the Physiological Bases of EEG
6 Practicalities of EEG Measurement and Experiment Design
II Preprocessing and Time-Domain Analyses
7 Preprocessing Steps Necessary and Useful for Advanced Data Analysis
8 EEG Artifacts: Their Detection, Influence, and Removal
9 Overview of Time-Domain EEG Analyses
III Frequency and Time-Frequency Domains Analyses
10 The Dot Product and Convolution
11 The Discrete Time Fourier Transform, the FFT, and the Convolution Theorem
12 Morlet Wavelets and Wavelet Convolution
13 Complex Morlet Wavelets and Extracting Power and Phase
14 Bandpass Filtering and the Hilbert Transform
15 Short-Time FFT
16 Multitapers
17 Less Commonly Used Time-Frequency Decomposition Methods
18 Time-Frequency Power and Baseline Normalizations
19 Intertrial Phase Clustering
20 Differences among Total, Phase-Locked, and Non-Phase-Locked Power and Intertrial Phase Consistency
21 Interpretations and Limitations of Time-Frequency Power and ITPC Analyses
IV Spatial Filters
22 Surface Laplacian
23 Principal Components Analyses
24 Basics of Single-Dipole and Distributed-Source Imaging
V Connectivity
25 Introduction to the Various Connectivity Analyses
26 Phase-Based Connectivity
27 Power-Based Connectivity
28 Granger Prediction
29 Mutual Information
30 Cross-Frequency Coupling
31 Graph Theory
VI Statistical Analyses
32 Advantages and Limitations of Different Statistical Procedures
33 Nonparametric Permutation Testing
34 Within-Subject Statistical Analyses
35 Group-Level Analyses
36 Recommendations for Reporting Results in Figures, Tables, and Text
VII Conclusions and Future Directions
37 Recurring Themes in This Book and Some Personal Advice
38 The Future of Cognitive Electrophysiology
References
Index
Color Plates.
Notes:
Includes bibliographical references and index.
OCLC-licensed vendor bibliographic record.
ISBN:
9780262319553 (e-book)
9780262019873 (hbk.)
OCLC:
869520413

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