analysis:rhythms
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| ~~DISCUSSION~~ | ~~DISCUSSION~~ | ||
| - | Welcome! This is the home page for the optional hands-on (heads-on) 2016 edition of the "Rhythmic Brain" course. | + | Welcome! This is the home page for the optional hands-on (heads-on) 2017 edition of the "Rhythmic Brain" course. |
| ==== Contents ==== | ==== Contents ==== | ||
| - | * [[analysis:rhythms:step1|Step 1: from zero to loading and plotting Emotiv data]] | + | * [[analysis:rhythms:step1|Module 1: Setting up, loading and plotting Emotiv data]] |
| + | * [[analysis:rhythms:step3|Module 2: Signal processing, basics of sampling (aliasing, Nyquist)]] | ||
| + | * [[analysis:rhythms:step2|Module 3: Signal processing, Fourier analysis and power spectra]] | ||
| + | |||
| + | (more advanced modules follow below) | ||
| === Getting started with MATLAB === | === Getting started with MATLAB === | ||
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| Depending on your background and programming experience you might find the following resources helpful: | Depending on your background and programming experience you might find the following resources helpful: | ||
| - | * Textbook: {{:analysis:wallisch_matlabforneuro.pdf|Wallisch, MATLAB for Neuroscientists}} | + | * Textbook chapter: {{:analysis:wallisch_ch2.pdf|Wallisch, "MATLAB for Neuroscientists"}} |
| * [[http://www.mathworks.com/help/matlab/getting-started-with-matlab.html?s_cid=learn_doc|"Getting Started with MATLAB" Primer]]. | * [[http://www.mathworks.com/help/matlab/getting-started-with-matlab.html?s_cid=learn_doc|"Getting Started with MATLAB" Primer]]. | ||
| * [[http://www.mathworks.com/matlabcentral/about/cody/ | Cody]], a continually expanding set of problems with solutions to work through, with a points system to track your progress | * [[http://www.mathworks.com/matlabcentral/about/cody/ | Cody]], a continually expanding set of problems with solutions to work through, with a points system to track your progress | ||
| - | If you are unsure, take a look at the table of contents of the MATLAB Primer in the link above. If there are things you don't recognize, use the Primer itself, or Chapter 2 of the MATLAB for Neuroscientists book to get up to speed. If you've never used MATLAB, definitely start with the steps in the Primer. | + | If you are unsure, take a look at the table of contents of the MATLAB Primer in the link above. If there are things you don't recognize, use the Tutorials in the Primer itself, and/or Chapter 2 of the MATLAB for Neuroscientists book to get up to speed. If you've never used MATLAB, I recommend you start with the Tutorials in the Primer, and refer to the book chapter if you'd like a change of pace or a different way of explaining the same things. |
| Regardless of your MATLAB abilities, some great ways to keep learning are: | Regardless of your MATLAB abilities, some great ways to keep learning are: | ||
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| * [[http://stackoverflow.com/questions/tagged/matlab | MATLAB questions on StackOverflow]], a Q&A site where you can browse previous questions and add new ones | * [[http://stackoverflow.com/questions/tagged/matlab | MATLAB questions on StackOverflow]], a Q&A site where you can browse previous questions and add new ones | ||
| - | If you have no formal training in computer programming (i.e. you have never taken a "Intro to Computer Science" or "Introductory Programming" type course) a great introduction to the "Zen of programming" is to do the pen-and-paper exercises in this [[http://sites.tufts.edu/rodrego/files/2011/03/Secrets-of-Computer-Power-Revealed-2008.pdf | short chapter]] by Daniel Dennett ("The Secrets of Computer Power Revealed") before you embark on the MATLAB primer linked to above. Most people find it frustrating at first, but rewarding if they stick with it for a few hours. | + | If you have no training or experience in computer programming (i.e. you have never taken a "Intro to Computer Science" or "Introductory Programming" type course) a great introduction to the "Zen of programming" is to do the pen-and-paper exercises in this [[http://sites.tufts.edu/rodrego/files/2011/03/Secrets-of-Computer-Power-Revealed-2008.pdf | short chapter]] by Daniel Dennett ("The Secrets of Computer Power Revealed") before you embark on the MATLAB primer linked to above. Most people find it frustrating at first, but rewarding if they stick with it for a few hours. |
| === Resources === | === Resources === | ||
| + | |||
| + | Emotiv documentation: | ||
| + | |||
| + | * {{:analysis:quickstartguide2014.pdf|Quick Start Guide}} | ||
| + | * {{:analysis:emotiv_epoc_specifications_2014.pdf|Specification Sheet}} | ||
| + | * {{:analysis:epocusermanual2014.pdf|Manual}} | ||
| + | * {{:analysis:testbench_manual.pdf|TestBench (Emotiv software) manual}} | ||
| + | * [[https://emotiv.com/forum/forum4/topic2081/messages/|Cleaning instructions]] | ||
| The following textbooks provide more in-depth treatment of some of the topics we touch on in the course: | The following textbooks provide more in-depth treatment of some of the topics we touch on in the course: | ||
| - | * Textbook: {{:analysis:leis_dspusingmatlab.pdf|Leis, Digital Signal Processing using MATLAB for Students and Researchers}} | + | * Textbook: Leis, Digital Signal Processing using MATLAB for Students and Researchers |
| - | * Textbook: {{:analysis:johnstonwu.pdf|Johnston and Wu, Foundations of Cellular Neurophysiology}} | + | * Textbook: Johnston and Wu, Foundations of Cellular Neurophysiology |
| - | * Textbook: {{:analysis:dayanabbott_theoneuro.pdf|Dayan & Abbott, Theoretical Neuroscience}} | + | * Textbook: Dayan & Abbott, Theoretical Neuroscience |
| These are selected modules from a graduate course I teach on neural data analysis: | These are selected modules from a graduate course I teach on neural data analysis: | ||
| * [[analysis:nsb2015:week0|Principles of (neural) data analysis]] | * [[analysis:nsb2015:week0|Principles of (neural) data analysis]] | ||
| - | * [[analysis:course-w16:week1|Module 1: Setting up (MATLAB, paths, GitHub, accessing data; Week 1)]] | + | * [[analysis:course-w16:week1|Module 1: Setting up (MATLAB, paths, GitHub, accessing data)]] |
| - | * [[analysis:course-w16:week2|Module 2: Introduction to neural data formats and preprocessing (Week 2)]] | + | * [[analysis:course-w16:week2|Module 2: Introduction to neural data formats and preprocessing]] |
| - | * [[analysis:course-w16:week3long|Module 3: Visualizing raw neural data in MATLAB (Week 3)]] | + | * [[analysis:course-w16:week3long|Module 3: Visualizing raw neural data in MATLAB]] |
| - | * [[analysis:course-w16:week4|Module 4: Anatomy of time series data, sampling theory (Week 4)]] | + | * [[analysis:course-w16:week4|Module 4: Anatomy of time series data, sampling theory]] |
| - | * [[analysis:course-w16:week5|Module 5: Fourier series, transforms, power spectra (Week 4)]] | + | * [[analysis:course-w16:week5|Module 5: Fourier series, transforms, power spectra]] |
| - | * [[analysis:course-w16:week6|Module 6: Filtering: filter design, use, caveats (Week 5)]] | + | * [[analysis:course-w16:week6|Module 6: Filtering: filter design, use, caveats]] |
| - | * [[analysis:course-w16:week7|Module 7: Time-frequency analysis: spectrograms (Week 5)]] | + | * [[analysis:course-w16:week7|Module 7: Time-frequency analysis: spectrograms]] |
| - | * [[analysis:course-w16:week11|Module 11: Interactions between multiple signals: coherence, Granger causality, and phase-slope index (Week 8)]] | + | * [[analysis:course-w16:week11|Module 11: Interactions between multiple signals: coherence, Granger causality, and phase-slope index]] |
| - | * [[analysis:course-w16:week12|Module 12: Time-frequency analysis II: cross-frequency coupling (Week 9)]] | + | * [[analysis:course-w16:week12|Module 12: Time-frequency analysis II: cross-frequency coupling]] |
| - | * [[analysis:course-w16:week13|Module 13: Spike-field relationships: spike-triggered average, phase locking, phase precession (Week 10)]] | + | * [[analysis:course-w16:week13|Module 13: Spike-field relationships: spike-triggered average, phase locking, phase precession]] |
| === Note for Linux users === | === Note for Linux users === | ||
| - | The lab codebase is set up for machines running 64-bit Windows 7 or Mac %%OS%% X. If you want to use Linux or some other %%OS%% you will probably need to compile some of the low-level loading functions yourself. Some pointers for this are provided in subsequent modules when loading is introduced. | + | The tutorials provided here are set up for machines running 64-bit Windows 7 or Mac %%OS%% X. If you want to use Linux or some other %%OS%% you will probably need to compile some of the low-level loading functions yourself. Some pointers for this are provided in subsequent modules when loading is introduced. |
analysis/rhythms.1459274612.txt.gz · Last modified: 2018/04/17 15:21 (external edit)
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