Download Analyzing Neural Time Series Data: Theory and Practice by Mike X Cohen PDF

By Mike X Cohen

This e-book deals a complete advisor to the idea and perform of interpreting electric mind signs. It explains the conceptual, mathematical, and implementational (via Matlab programming) elements of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and native box capability (LFP) recordings from people and nonhuman animals. it's the simply booklet at the subject that covers either the theoretical history and the implementation in language that may be understood via readers with out broad formal education in arithmetic, together with cognitive scientists, neuroscientists, and psychologists.

Readers who cross throughout the ebook bankruptcy by means of bankruptcy and enforce the examples in Matlab will improve an figuring out of why and the way analyses are played, how you can interpret effects, what the methodological concerns are, and the way to accomplish single-subject-level and group-level analyses. Researchers who're accustomed to utilizing computerized courses to accomplish complex analyses will examine what occurs after they click on the "analyze now" button. The booklet offers pattern info and downloadable Matlab code. all of the 38 chapters covers one research subject, and those issues growth from basic to complex. such a lot chapters finish with workouts that extra improve the cloth coated within the bankruptcy. a number of the equipment offered (including convolution, the Fourier remodel, and Euler's formulation) are basic and shape the foundation for different complex information research equipment. Readers who grasp the equipment within the ebook should be prepared to profit different methods.

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Additional info for Analyzing Neural Time Series Data: Theory and Practice

Example text

The position taken in this book is that analysis terms should be concise descriptions of the data analysis rather than interpretations of the results or hypothesized neural mechanisms. This argument is further developed in chapters 21 and 37. When many terms for the same analysis exist, I have tried to list all of them when introducing the method and then justify the term preferred in this book. 8 Exercises Many chapters contain exercises at the end. These exercises will reproduce and further develop the material covered in that chapter.

3 Some ERP components (particularly later ERP components) would not be affected if the sampling rate were much lower (in this case, 50 Hz). ERP data were low-pass filtered at 40 Hz. This limitation is exacerbated by the relatively small literature on linking time-frequency dynamics to cognitive processes compared to the literature linking ERPs to cognitive processes. 2), there are still many cognitive processes for which the time-frequency electrophysiological characteristics are not known or are understudied.

That said, by going through the methods in this book, you will be well prepared to learn and develop other analysis approaches that are not presented here or are not discussed in depth. Many of the basic methods detailed in this book (including convolution, the Fourier transform, Euler’s formula, wavelets, circular variance, and permutation testing) are fundamental and form the groundwork for other advanced data analysis methods. 10). Rather, this book explains in plain English, math, and Matlab how analyses that are commonly used in the literature can be performed, how the results can be interpreted, and what pitfalls and potential methodological concerns arise with the use of certain methods.

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