Meg information based connectivity coding session: Difference between revisions
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!Under Construction - will be finalized by Friday! |
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We will be meeting virtually over Zoom from 1pm-3pm with breakout rooms for questions and collaboration <br> |
We will be meeting virtually over Zoom from 1pm-3pm with breakout rooms for questions and collaboration <br> |
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There will be a quick discussion |
There will be a quick discussion and some example data on biowulf. <br> |
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==FRITES toolbox== |
==FRITES toolbox== |
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Revision as of 10:08, 12 August 2022
We will be meeting virtually over Zoom from 1pm-3pm with breakout rooms for questions and collaboration
There will be a quick discussion 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
#Make the SAM beamformers and apply the symbolic transfer entropy sam_cov ... sam_wts ... STEdelay ....
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 "_")