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analysis:rhythms [2016/03/29 16:03]
mvdm [Resources]
analysis:rhythms [2020/01/08 15:19]
mvdm [Resources]
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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) ​2020 edition of the "​Rhythmic Brain" course.
  
-==== Contents ​====+==== Getting started with Emotiv headsets ==== 
 + 
 +  * Using the course laptops, launch the Emotiv Xavier Control Panel using the Desktop icon. 
 +  * Click "​Continue without Cloud Services"​ 
 +  * Type an username ("​TestUser"​ works fine) 
 +  * Follow the instructions on the screen. 
 + 
 + 
 +==== Analysis modules ​====
  
   * [[analysis:​rhythms:​step1|Module 1: Setting up, loading and plotting Emotiv data]]   * [[analysis:​rhythms:​step1|Module 1: Setting up, loading and plotting Emotiv data]]
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   * [[analysis:​rhythms:​step2|Module 3: Signal processing, Fourier analysis and power spectra]]   * [[analysis:​rhythms:​step2|Module 3: Signal processing, Fourier analysis and power spectra]]
  
-(more will be added as we go along)+(more advanced modules can be found [[analysis:​nsb2018|here]].) 
 === Getting started with MATLAB === === Getting started with MATLAB ===
  
 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:​ Emotiv documentation:​
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   * {{:​analysis:​epocusermanual2014.pdf|Manual}}   * {{:​analysis:​epocusermanual2014.pdf|Manual}}
   * {{:​analysis:​testbench_manual.pdf|TestBench (Emotiv software) manual}}   * {{:​analysis:​testbench_manual.pdf|TestBench (Emotiv software) manual}}
-  * [[https://​emotiv.com/​forum/​forum4/​topic2081/messages/|Cleaning instructions]]+  * [[https://www.emotiv.com/knowledge-base/electrode-oxidation/|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:
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   * Textbook: Dayan & Abbott, Theoretical Neuroscience   * Textbook: Dayan & Abbott, Theoretical Neuroscience
  
-These are selected modules from a graduate course I teach on neural data analysis: +Some tasks to try to generate specific brain rhythms:
- +
-   * [[analysis:​nsb2015:​week0|Principles of (neural) data analysis]] +
-   * [[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]] +
-   * [[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]] +
-   * [[analysis:​course-w16:​week5|Module 5: Fourier series, transforms, power spectra]] +
-   * [[analysis:​course-w16:​week6|Module 6: Filtering: filter design, use, caveats]] +
-   * [[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]] +
-   * [[analysis:​course-w16:​week12|Module 12: Time-frequency analysis II: cross-frequency coupling]]  +
-   * [[analysis:​course-w16:​week13|Module 13: Spike-field relationshipsspike-triggered average, phase locking, phase precession]] +
-=== Note for Linux users ===+
  
-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.+  * Occipital-parietal alpha (10 Hz): eyes-open vs eyes-closed contrast 
 +  * Frontal alpha: negative high arousal picture viewing, or mentally counting backwards from a large number in steps of 7 or 13 
 +  * Drawing a stick figure (see for yourself what happens, take care to avoid moving artifacts)
analysis/rhythms.txt · Last modified: 2020/01/15 15:00 by mvdm