Download e-book for kindle: Analyzing Neural Time Series Data: Theory and Practice by Mike X Cohen

By Mike X Cohen

ISBN-10: 0262019876

ISBN-13: 9780262019873

This booklet bargains a entire advisor to the idea and perform of interpreting electric mind indications. It explains the conceptual, mathematical, and implementational (via Matlab programming) points of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and native box strength (LFP) recordings from people and nonhuman animals. it's the in basic terms publication at the subject that covers either the theoretical historical past and the implementation in language that may be understood by way of readers with no wide formal education in arithmetic, together with cognitive scientists, neuroscientists, and psychologists.

Readers who pass in the course of the booklet bankruptcy by means of bankruptcy and enforce the examples in Matlab will boost an realizing of why and the way analyses are played, tips to interpret effects, what the methodological concerns are, and the way to accomplish single-subject-level and group-level analyses. Researchers who're conversant in utilizing automatic courses to accomplish complicated analyses will examine what occurs once they click on the "analyze now" button. The e-book offers pattern information and downloadable Matlab code. all of the 38 chapters covers one research subject, and those themes growth from uncomplicated to complicated. such a lot chapters finish with workouts that extra strengthen the cloth lined within the bankruptcy. a number of the equipment awarded (including convolution, the Fourier remodel, and Euler's formulation) are primary and shape the foundation for different complicated information research tools. Readers who grasp the equipment within the booklet might be prepared to profit different methods.

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

This booklet deals a entire consultant to the speculation and perform of interpreting electric mind indications. It explains the conceptual, mathematical, and implementational (via Matlab programming) features of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and native box power (LFP) recordings from people and nonhuman animals.

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

Example text

But new EEG equipment with improved signal quality and high spatial resolution can lead to similarly high costs compared to MEG and MRI. If you are starting a research lab and considering an equipment budget, you should focus on which method will be best for your research questions, not on what method will be the cheapest. 3 Interpreting and Asking Questions about Time-Frequency Results The purpose of this chapter is to provide an introduction to time-frequency-based approaches of EEG data analyses to people who are new to EEG or who have some experience with ERPs but are new to time-frequency-based analyses.

Running the code as you follow the book will not only reproduce the figures but will also help you to understand each step of each analysis and will facilitate further exploration and development of the methods. Note that in many cases the code for one figure relies on variables that were created when previous figures from that chapter were made. 6, Matlab might crash because of undefined variables. 2, and so on. I checked all the code for each chapter using Matlab versions 2011a and 2012 on 64-bit Windows and on 64-bit Mac.

5 Hz. 234 Hz activity differs between conditions starting at 200 versus 230 ms. This is not a problem of EEG data analyses but, rather, a problem of detecting time-varying oscillating signals. Consider another periodic signal: your heartbeat. You cannot measure your resting heart rate by pressing against an artery for less than 1 s (unless your resting heart rate is over 120 bpm, in which case you might have more important things to worry about than temporal vs. frequency precision). On the other hand, if you want to measure changes in heart rate in 5-s steps, you have to accept some uncertainty in the precise rate in order to measure changes over time.

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


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