Meg information based connectivity coding session: Difference between revisions

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Output is a text file
Output is a text file
Must determine an embedding dimension (4 as default) - the higher the embedding the more data needed
Must determine an embedding dimension (4 as default) - the higher the embedding the more data needed
Minimal requirements (1Khz sampling rate and 300s of data)
Minimal requirements (>=1Khz sampling rate and >=300s of data)
The inputs do not need to be brain regions (for example can compare STE between audio track to brain region)
The inputs do not need to be brain regions (for example can compare STE between audio track to brain region)



Revision as of 09:22, 11 August 2022

!Under Construction - will be finalized by Friday!

We will be meeting virtually over Zoom from 1pm-3pm with breakout rooms for questions and collaboration
There will be a quick discussion/demo (10-20mins) and some example data on biowulf.

FRITES toolbox

Club MEG Presentation Recording

 Background
 Getting Started Scripts
 Example Scripts

Install in new environment (RECOMMENDED!):

 conda create -n frites conda-forge::mne conda-forge::jupyterlab pip -y 
 conda activate frites
 pip install frites
 git clone https://github.com/brainets/CookingFrites.git
 cd CookingFrites
 jupyter lab
 #Once jupyter is open, the notebooks are in the notebooks folder

Install in current environment (Better to use New environment as listed above!)-

 #Download getting started tutorials
 git clone https://github.com/brainets/CookingFrites.git
 pip install frites

SAM Symoblic Transfer Entropy Connectivity - (tutorial will be formalized by Friday)

Background

Club MEG SAM Connectivity Presentation Recording

Recommendations

 This process is a trigger-free process that estimates the symbolic transfer entropy (connectivity assessed by delayed propagation of signals) between two ROIs 
 70-185Hz has been tested and is recommended as a filter band
 Use an atlas based input for the bivariate connectivity assessment (AAL atlas, Desikan K., Destreux...)
 SAMwts or Patch_wts to create the beamformer
 Output is a text file
 Must determine an embedding dimension (4 as default) - the higher the embedding the more data needed
 Minimal requirements (>=1Khz sampling rate and >=300s of data)
 The inputs do not need to be brain regions (for example can compare STE between audio track to brain region)

Use on Biowulf

 #Log into biowulf
 sinteractive --mem=6G --cpus-per-task=4
 #Make sure modules are loadable -- this can also be added to ~/.bashrc file
 module use --append /data/MEGmodules/modulefiles
 module load SAMsrcDEV
 #This part is already done
 sam_cov ...
 sam_wts ...
 STEdelay ....  

cp ***TESTDATA*** (fix this part) Local folder

 Usage: STEdelay [options]	Version 5.0 (64-bit) rev-1, Aug 10 2022
 
 Options:
 If a parameter begins with '--', it is allowed on the command line,
 otherwise it is only allowed in a parameter file (see -m).
 All times are in seconds.
 
   -h, --help               show this help
   -r DSNAME, --DataSet DSNAME
                            MEG dataset name [env_var = ds]
   -m PFILE, --param PFILE  parameter file name (optionally ending
                            in ".param") [env_var = param]
   -v, --verbose            verbose output
   --CovType GLOBAL|SUM|ALL which covariance matrix to use for the analysis
   --CovBand LO HI          covariance bandwidth limits in Hz
   --ImageBand LO HI        imaging covariance bandwidth limits in Hz
   --OrientBand LO HI       band to use for orientation instead of Global (Hz)
   --SmoothBand LO HI       used to smooth Hilbert envelope, kurtosis, or RVE (Hz)
   --Notch                  apply a powerline notch
                            (including harmonics)
   --Hz HZ                  frequency for powerline (Hz, default 60)
   ImageMetric METRICSPEC   imaging metric
   --Extent DIST            radial extent from ROI voxels or centroid (mm)
   -t TARGETFILE, --TargetName TARGETFILE
                            file containing target coordinates
   -i MRIDIR, --MRIDirectory MRIDIR
                            MRI directory root [env_var = mridir]
   -o IMAGEDIR, --ImageDirectory IMAGEDIR
                            image output directory [env_var = imagedir]
   --PrefixLength N         DataSet prefix may be specified as a number
                            or as a prefix delimiter (default "_")