ICA-QC

Post-ICA QC visualization and manual correction tool.

Features

• Visualize the results of Independent Component Analysis (ICA) for MEG/EEG preprocessing.
• Perform manual quality checks and override ICA-derived components as needed.
• Optionally re-apply ICA on the data.

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Requirements

• MNE-python (1.3.0 and above)
• Numpy
• Matplotlib

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Installation

Clone this repository:

git clone https://github.com/neurosignal/ICA-QC.git
cd ICA-QC

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Get help

python ica_qc.py --help

This script is meant to check the quality of ICA and 
       override the ICA application with user's own selections.
USAGE:
    - Check ICA outputs:
        python ica_qc.py --results_dir <directory>
    - Apply ICA manually:
        python ica_qc.py --ica_file <xxx_0-ica_applied.fif>             --data_file <xxx_raw_tsss.fif>                 --apply_filter --block --apply_ica
    - Help:
        python ica_qc.py --help

usage: ica_qc.py [-h] [--results_dir RESULTS_DIR] [--ica_file ICA_FILE] [--data_file DATA_FILE] [--apply_filter] [--lfreq LFREQ] [--hfreq HFREQ] [--apply_ica] [--block]

Post-ICA QC visualization tool for MEGnet (or other ICA pipelines) outputs.

optional arguments:
  -h, --help            show this help message and exit
  --results_dir RESULTS_DIR, -dir RESULTS_DIR
                        Path to MEGnet (or other ICA pipelines) results.
  --ica_file ICA_FILE, -ica ICA_FILE
                        Path to ICA-applied file.
  --data_file DATA_FILE, -data DATA_FILE
                        Raw MEG file.
  --apply_filter        Apply bandpass filter before plotting.
  --lfreq LFREQ         Low cutoff for bandpass filter.
  --hfreq HFREQ         High cutoff for bandpass filter.
  --apply_ica           Apply ICA manually on raw data.
  --block               Block GUI for plots.

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Common workflows

• Visualize precomputed ICA results (e.g., from MEGnet or another ICA pipeline in MNE-Python):

python ica_qc.py --results_dir <path/to/results_directory>

• Apply ICA Manually

python ica_qc.py \
  --ica_file <path/to/xxx_0-ica_applied.fif> \
  --data_file <path/to/xxx_raw_tsss.fif> \
  --apply_filter \
  --lfreq <low_freq_cutoff> \
  --hfreq <high_freq_cutoff> \
  --apply_ica \
  --block

• --apply_filter, --lfreq, --hfreq: add a band-pass filter before visualization.

• --apply_ica: apply ICA to raw data.

• --block: block execution until the GUI window is closed after selection/de-selection.

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Contribution

Contributions are most welcome! Please open an issue or submit a pull request.

License

See LICENSE for details.