readiness_scripts

Script for MEG analysis of the readiness project

This file will include a description of the files and directories and the thougts behind them

General remarks

Badchannels (directory)

• this will include a csv file for each subject with the fro the badchannels to be used in the maxfilter script.

• these file are made with saveBadChans.py, which extracts the channel names that are marked as bad the corresponding fif-file

my_configs.py

• this file has general purpose settings, e.g. paths to data directory.
• this file can be used to import settings into python scripts,
  • from my_configs.py import *

Preprocessing

Preprocessing the raw data

• maxfilter_function.py: a function to call the maxfilter for a subject
  • missing: able to select conditions
• find_fifs.txt
  • the find/grep commands to make symbolic-links from fifs in raw to scratch

Preprocessing the maxfiltered data

• preproc_func.m

  • uses Fieldtrip to:
    • Segment data, from -3.5 to 0.5 related to button press.
    • Low-pass filter @ 128Hz
    • Band-pass filter @ 49 & 51, 99 & 101
    • Downsample to 256Hz

• auto_artifact_remove.m

  • uses Fieldtrip to automatically remove trials based on muscle and squid jumps

• ica_process.m

  • uses Fieldtrip to:
    • reduce with PCA to 64 dimensions
    • find ICA component

• ica_viz.m

  • vizualising the ica components ica_remove_comp.m
  • uses Fieldtrip to remove the components from the data

• combine_planar

  • function to return a RMS conbimed data structure of the gradiometors

warpper_ft_pipeline.m

• wrapper function to run preprocessing pipeline, from preproc_func to ica_process
• ica components have to visually identified for each subject and sessions
  • use ica_viz.m for that
  • use ica_remove_comp.m to remove identified components