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

By:

Cohen, Mike X

Material type: Text

TextSeries: Issues in clinical and cognitive neuropsychologyPublication details: Cambridge : MIT Press, c2014.Description: xviii, 578 p., 16 unnumbered pages of plates : illustrations ; 24 cmISBN:

9780262019873 (hardcover : alk. paper)

Subject(s):

DDC classification:

23 C678 612.82339

Contents:

Part 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-- Part 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-- Part 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-- Part IV: spatial filters-- 22. Surface laplacian-- 23. Principal components analysis-- 24. Basics of single-dipole and distributed-source imaging-- Part 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-- Part VI: statistical analyses-- 32. Advantages and limitation 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-- Part VII: Conclusions and future directions-- 37. Recurring themes in this book and some personal advice-- 38. The future of cognitive electrophysiology-- References-- Index.

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."--

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Books	ISI Library, Kolkata	612.82339 C678 (Browse shelf(Opens below))	Available		135565

Total holds: 0

Includes bibliographical references (pages 549-572) and index.

Part 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--

Part 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--

Part 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--

Part IV: spatial filters--
22. Surface laplacian--
23. Principal components analysis--
24. Basics of single-dipole and distributed-source imaging--

Part 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--

Part VI: statistical analyses--
32. Advantages and limitation 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--

Part VII: Conclusions and future directions--
37. Recurring themes in this book and some personal advice--
38. The future of cognitive electrophysiology--
References--
Index.

"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."--

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