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analysis:rhythms [2016/03/29 16:09]
mvdm [Getting started with MATLAB]
analysis:rhythms [2020/01/15 15:00] (current)
mvdm
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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:
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 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. 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.1459282198.txt.gz · Last modified: 2018/07/07 10:19 (external edit)