Each subject’s eeg/ folder contains reports and visualizations generated during preprocessing.
These outputs provide transparency, allow quality control, and make it easier to share results with collaborators who may not run the pipeline themselves.

​
Example Layout


sub-451559/eeg/
├── 128\_Rest\_EyesOpen\_D1004\_autoclean\_report.pdf
├── 128\_Rest\_EyesOpen\_D1004\_processing\_log.csv
├── 128\_Rest\_EyesOpen\_D1004\_psd\_topo\_figure.png
├── 128\_Rest\_EyesOpen\_D1004\_raw\_vs\_cleaned\_overlay.png
├── 128\_Rest\_EyesOpen\_D1004-ica.fif
├── FlaggedChs.tsv
└── sub-451559\_task-restingstatetutorialica\_components\_all.pdf

​
File Descriptions

FilePurposeExample
*_autoclean_report.pdfFull QC report with preprocessing summary and visualizations.View Report
*_processing_log.csvRun-specific log of preprocessing parameters (see Processing Log).View Log
*_psd_topo_figure.pngPower spectral density (PSD) topography plot comparing raw vs. cleaned data.View PSD Plot
*_raw_vs_cleaned_overlay.pngOverlay of raw and cleaned signals for visual inspection.View Overlay
*-ica.fifICA decomposition weights in MNE format (stored separately from EEG).Download ICA
FlaggedChs.tsvList of channels flagged as bad during preprocessing.View Flagged Channels
*_ica_components_all.pdfReport showing ICA components and which were removed.View ICA Components

​
Visual Examples

​
PSD Topography Comparison

Power spectral density topography comparison

​
Raw vs Cleaned Signal Overlay

Raw vs cleaned EEG signal overlay

​
Why These Matter

  • Quality Control (QC): Each run produces both text logs and figures for visual inspection.
  • Transparency: Reports can be shared with collaborators or archived with publications.
  • Reproducibility: The .csv log and .fif ICA weights make it possible to rerun or reapply ICA later.
Subject-level reports are intended for human review.
They complement the standardized outputs in derivatives/ and final_files/.