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eeg-figure

Render publication-quality EEG figures from precomputed stage outputs and a deterministic FIGURE_PLAN.

Updated Aug 27, 2026
Search Tags:#matplotlib#time-frequency#eeg#journal formatting#figure rendering#topomaps#svg captions
One-click install
npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-figure
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eeg-figure
Source: https://github.com/dengzhe-hou/auto-eeg-analysis/tree/main/skills/eeg-figure
Command: npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-figure

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

EEG analyses often stop at computed results, but publishing requires consistent, journal-ready figures with correct styling, annotations, and reproducible captions.

Core Features & Use Cases

  • Figure-plan driven rendering: Reads FIGURE_PLAN.md to deterministically generate exactly the requested figure set with correct panel layouts and journal dimensions.
  • Multi-modal EEG visualization support: Produces ERP (butterflies, ROI overlays, difference with CI and clusters), TFR (heatmaps, ERDS maps, band time courses), topomaps (evoked and TFR), and decoding/spectral visuals.
  • Publication-quality outputs: Writes editable SVG plus PNG previews, with enforced typography, color accessibility, units, colorbars, and strict difference/topomap scaling.
  • Self-contained figure captions: Generates figure-stage/CAPTIONS.md entries that include what is plotted, statistical framing, N, and correct interpretation rules for cluster boundaries.

Quick Start

Use the eeg-figure skill to render paper-ready figures for an analysis by ensuring FIGURE_PLAN.md and the required stage outputs exist in your project directory, then run the skill for your project.

Frequently Asked Questions about eeg-figure

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I render publication-quality EEG figures from precomputed analysis outputs?▼

You can render publication-quality EEG figures by providing precomputed stage outputs and a FIGURE_PLAN.md file. The tool deterministically generates journal-ready SVG and PNG outputs with enforced typography, units, and colorbars.

What EEG visualization types are supported for journal formatting?▼

Supported EEG visualizations include ERP butterflies, ROI overlays, time-frequency heatmaps, ERDS maps, evoked and TFR topomaps, decoding panels, spectral plots, and bar or violin distributions for condition comparisons.

Do I need a specific analysis plan file to generate EEG topomaps and time-frequency maps?▼

Yes, generating EEG topomaps and time-frequency maps requires a FIGURE_PLAN.md and ANALYSIS_PLAN.md file. You also need corresponding stage directories like tfr-stage and an optional channel_mapping.json for topomap labeling.

How are figure captions and statistical framing handled for EEG analysis results?▼

Figure captions are automatically generated in a CAPTIONS.md file. These self-contained captions detail what is plotted, statistical framing, N, and correct interpretation rules for cluster boundaries.

What output formats are produced for journal-scaled EEG figures?▼

Journal-scaled EEG figures are produced as editable SVG files and PNG previews. The outputs enforce strict difference and topomap scaling using explicit symmetric vmin/vmax values for signed maps.

Can I use matplotlib to customize EEG topomaps and spectral plots generated from stage outputs?▼

The tool outputs editable SVG files, allowing further customization in vector graphics editors or compatible matplotlib workflows. It enforces journal-scaled styling and unit-annotated axes during the initial automated render.

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