Cited by 2,105EEG and Brain-Computer InterfacesNeural dynamics and brain functionUndergraduate Neuroscience Education and Research

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Analyzing Neural Time Series Data: Theory and Practice

Cohen, Mike X·2014·The MIT Press eBooks

DOI 10.7551/mitpress/9609.001.0001

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Abstract

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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Ding, J., Zhang, X., Liu, J., Hu, Z., Yang, Z., Tang, Y., & Ding, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-98548-1 · Cited by 8
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Prediction errors in surface segmentation are reflected in the visual mismatch negativity, independently of task and surface features
Oxner, M., Rosentreter, E. T., Hayward, W. G., & Corballis, P. M. (2019) · Journal of Vision · doi:10.1167/19.6.9 · Cited by 7
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Self-citation
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Authors: Cohen, M. X.
Venue: The MIT Press eBooks
Publisher: The MIT Press
Published: 2014-01-17
DOI: 10.7551/mitpress/9609.001.0001
OpenAlex: W4230797216
Cited by: 2,105
References: 0
Citations by year: 2026: 226 · 2025: 277 · 2024: 237 · 2023: 258 · 2022: 226 · 2021: 221 · 2020: 226 · 2019: 149 · 2018: 108 · 2017: 85 · 2016: 51 · 2015: 31 · 2014: 6
FWCI: 20.41
Type: book
Language: en
Open access: closed
Locations: The MIT Press eBooks (publishedVersion)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Social Sciences › Education › Undergraduate Neuroscience Education and Research
Keywords: magnetoencephalography, EEG, local field potentials, time-frequency analysis, synchronization analysis, Fourier transform, convolution, Euler's formula, group-level analysis, single-subject analysis, brain electrical signals

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