ENIGMA MEG Working Group

UNDER CONSTRUCTION

Enigma Project - MEG working group

The enigma project is a large scale neuroimaging project to leverage data across multiple institutes to identify neuroimaging findings that are generally not possible at a single institute. http://enigma.ini.usc.edu/

Singularity Container

Singularity is a container technology (similar to Docker). We are using containers to allow for easy distribution of the analysis pipeline and analysis consistency. Singularity was chosen becuase it does not require administrative priveledges during runtime and can be run on an HPC system. Being a container, the analysis can be run on any platform (linux, mac, windows, ...). https://sylabs.io/singularity/

Resting State Analysis

The analysis routine has been implemented in MNE python (https://mne.tools/stable/index.html) and packaged into a singularity container. This guarantees that differences in software dependencies and operating system configurations have been eliminated.

The singularity def file can be found at:

 github.com/........ upload

The singularity container can be downloaded from:

 Under Construction

Anatomical Preprocessing:

 Surface models: Scalp, Outer Skull, Inner Skull, Pial Surface
 Coregistration of the MRI and MEG data
 Parcel extraction (freesurfer autorecon3)
 Subparcel calculation (mne ....)

The resting state analysis steps:

 Check data type and load data
 Downsample to 200Hz
 Split to 1 second epochs
 Reject sensor level data at a specific threshold
 Calculate broad band dSPM inverse solution
 Filter the data into bands (1-3, 3-6, 8-12, 13-35, 35-55)
 Project the data to parcels and create parcel time series
 Calculate relative power in each band and parcel

Outputs:

 The outputs of the analysis will result in a csv file
 A csv file for each subject will be created in the subfolder of the singularity directory
 A final command can be run to calculate the summary statistics
 

Submission of Results:

 After calculating the local institutes summary statistics, the group csv file will be uploaded to the NIMH.

Meta-Analysis:

 Statistics will be compiled across institutes