MEG_workshop_2023

Day 1 (09/27/2023)

Time	Topic	Presenter
9:00 - 9:15	Bagel Config + Coffee Download + Computer Setup
9:15 - 9:30	Course Intro + MEGcore Intro	MEGcore
9:30 - 10:30	Intro to MEG and general overview of source localization	Fred
10:30 - 11:00	MEG Hardware and Signal Generation / Collection	Stephen
11:00 - 11:15	Break
11:15 - 12:15	Stimuli, trigger processing, epochs, evoked data, bad chans	Tom + Anna
	bad epochs, filtering, abberant signals
12:15 - 1:30	Lab 1 + Lunch
1:30 - 2:30	Filtering Data, Frequency Analysis, Hilbert, Brain Rythms, and Artifacts	Allison
2:30 - 3:00	Lab 2
3:00 - 4:00	MRI Processing, placing fiducials, coreg, source model (volume + surface)	Anna + Jeff
	BEM, Forward Model
4:00 - 4:30	Lab 3

Day 2 (10/04/2023)

Time	Topic	Presenter
9:30-10:30	Source Localization (Dipoles, multiple dipoles, MNE, dSPM, Beamformer)	Fred + Jeff
10:30 - 11:30	Lab 4
11:30 - 12:00	Beamformer Specifics - Covariance, filtering, data rank, regularization	Tom
12:00 - 1:30	Lab 5 + Lunch
1:30 - 2:00	Single subject to group data	Jeff
2:00 - 2:30	Lab 6
2:30 - 3:30	Statistics (parametric / log transform / resampling stats / clusters )	Fred + Allison
3:30 - 4:00	Code
4:00 - 4:20	Course Review	Allison
4:20 - 5:00	Additional Techniques: OPMs, Connectivity	Amaia + Lucrezia
	Additional Techniques: Decoding, Dynamic Causal Modeling	Shruti + Jess

Biowulf users (must be NIH associated)

Log into biowulf: ssh -Y USERNAME@biowulf.nih.gov

#You can type tmux before starting sinteractive to have a persistent session between disconnecting wifi
#Allocate resources for processing
sinteractive --mem=16G --cpus-per-task=12 --gres=lscratch:10 --tunnel --time=08:00:00

You will see a line like the below. Follow the instructions (start a new terminal into biowulf), then return to original terminal for the rest of the commands.

Copy notebooks to your local folder. Change directories first if you don't want the code/data in your home folder.

module use --append /data/MEGmodules/modulefiles  #You can add this to your .bashrc for convenience
module load meg_workshop

get_code   #Copy the code to your current directory
get_data   #Copy and untar the data to your /data/${USER}/meg_data_workshop

cd MEG_workshop_2023
./start_notebook_Day1.sh  #Start the notebook for Day1 - allows for time series scrolling
#OR use for Day2 material  -- ./start_notebook_Day2.sh - Visualize the 3D brain renderings

Enter this into the address bar of your web browser localhost:<PORT>

NOTE:If you get something about a token: Copy it from the commandline

Install (not required for biowulf users)

The following software is required to run all parts of the coding sections: afni + freesurfer + git + miniconda(/conda)
To run the majority of the code: miniconda/conda + git are required

Miniconda will provide the minimum features for the installation:
https://docs.conda.io/projects/miniconda/en/latest/
In a terminal, find your Download folder (typically cd /home/<USERNAME>/Downloads or cd /Users/<USERNAME>/Downloads).

chmod +x Miniconda3-latest.....sh   #Make this file executable - Fill in the rest of name (it will be Linux / Mac/ or Windows)
./Miniconda3-latest...sh  #Run the installer.  Open a new terminal after finishing the installation directions

Mamba is not required, but will install faster than conda (functionally they are the same)
To install mamba - conda install --channel=conda-forge --name=base mamba

Install (version1) - requires make, mamba, git

git clone https://github.com/nih-megcore/MEG_workshop_2023.git
cd MEG_workshop_2023
make install 

Install (version2)

#Clone this repository - If you don't have git, just download the zip file from the green button at the top of page
git clone https://github.com/nih-megcore/MEG_workshop_2023.git

#Install MNE - Substitute conda for mamba if any errors
mamba create --override-channels --channel=conda-forge --name=MEG_workshop mne pip jupyterlab -y
conda activate MEG_workshop
pip install h5io pymatreader

#Install the Workshop files
cd MEG_workshop_2023
pip install -e .    #Install this code
pip install git+https://github.com/nih-megcore/nih_to_mne.git  #Install some auxilliary NIH code

Install dataset - if you want to create from scratch. Use the link provided by email if you want to download

mamba create -n datalad -c conda-forge datalad gdown -y
conda activate datalad

This will pull the NIMH_hv OpenNeuro repository and associated files.
This will download the freesurfer processed MRI files as well

 ./extras/datalad_pull.sh

Install auxiliary code - (not necessary for course Day1)

Install freesurfer: https://surfer.nmr.mgh.harvard.edu/fswiki/rel7downloads
Install Afni: https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/background_install/main_toc.html

Check installs

Run ./check_requirements.sh to check for freesurfer / afni / mne / jupyter installation.

Data Format for code

Input data is in BIDS format from the NIH HV protocol.
Data should be located in /data/${USER}/meg_workshop_data
   This will automatically be performed on biowulf with the get_data command.
Derivatives data will be in /data/${USER}/meg_workshop_data/{Day1,Day2}/${bids_id}/ses-01/meg/
   Day2 derivatives will have pre-calculated bem, fwd, trans, src files