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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

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script for MEG analysis of the readiness project

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