AnalysisGuidelines

UNDER CONSTRUCTION
Analysis Introduction
1) Anatomical Processing
2) MEG Trigger Configuration
3) MEG Inverse Solution (SAM software)
4) Statistical Analysis

Data collection: Exact timing of the experiment can be provided in the data acquisition or a set of smaller trials can be provided

CTF Software: DataEditor -data $DATA

thresholdDetect - Detect changes in the analog inputs to determine onset of stimulus addmarkers - necessary to embed the stimulus timing into the CTF dataset

parsemarks - Combines markers (i.e optical and parallel port)

newDs -f -filter processing.cfg

Anatomy Processing: The MRI processing starts with anat+orig.BRIK and anat+orig.HEAD format. The datasets are opened using AFNI

fiddist.py fiddist2.py - wrapper that accepts two inputs and provides the difference in distance (e.g. MRI and dataset)

Jupyter Notebook Over a Remote Connection
1) Run one terminal to start the notebook:

 ssh -Y $USER@$REMOTE_HOST
 cd $FOLDER_WITH_CODE
 #If necessary: conda activate $CONDA_ENV
 jupyter notebook --no-browser --port=8887

2) Run another terminal to forward the port to your local machine
(Replace User and Remote_Host with the appropriate username and ip-address)

 ssh -N -L localhost:8888:localhost:8887 $USER@$REMOTE_HOST

3) In Firefox/Chrome/Etc - Log into localhost:8888
This will prompt you for a token

4) In the password/token column, copy the token created in the first terminal
(It should look like the below - only copy the portion after the token= )

 http://localhost:8887/?token=####HERE_IS_THE_TOKEN_CODE---COPY_THIS_AND_PASTE_INTO_BROWSER

Version Control for Jupyter Notebook Nbdime for notebook version control (a jupyter interface for git)