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eeg-tfr

Compute EEG time-frequency representations and inter-trial coherence from epoched data.

Updated Aug 27, 2026
Search Tags:#wavelets#itc#eeg#baseline correction#mne-python#tfr#erds
One-click install
npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-tfr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: eeg-tfr
Source: https://github.com/dengzhe-hou/auto-eeg-analysis/tree/main/skills/eeg-tfr
Command: npx skills add https://github.com/dengzhe-hou/auto-eeg-analysis --skill eeg-tfr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It computes EEG time-frequency representations (TFRs) and inter-trial coherence (ITC) from epoched data, producing outputs suitable for ERP/ERSP-style reporting and downstream statistics.

Core Features & Use Cases

  • Time-frequency decomposition: Computes Morlet wavelet TFR (with MNE options for multitaper or Stockwell alternatives) over a configurable frequency range.
  • Baseline correction & ERDS-ready outputs: Applies baseline correction in recommended logratio/db modes and produces band-aggregated ERDS tables.
  • Inter-trial coherence (ITC/PLF): Computes ITC separately (phase consistency across trials) without conflating it with power.

Quick Start

Tell the agent to run time-frequency computation for your epochs by specifying the project directory and your desired method, bands, and baseline mode (for example: “Use /eeg-tfr projects/my-study with method multitaper, bands theta and alpha, and baseline_mode db”).

Frequently Asked Questions about eeg-tfr

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

FAQPage Schema
How do I compute time-frequency representations and inter-trial coherence for epoched EEG data?▼

Time-frequency representations and inter-trial coherence are computed from epoched EEG data using Morlet wavelets via MNE-Python, applying baseline correction and generating ERDS-ready HDF5 and CSV outputs.

What is the best way to apply baseline correction for ERDS band outputs in EEG analysis?▼

Baseline correction for ERDS band outputs is applied using recommended logratio or decibel modes, ensuring power values are normalized across trials without conflating them with phase consistency measures.

Can I use multitaper or Stockwell methods instead of Morlet wavelets for EEG time-frequency decomposition?▼

Multitaper and Stockwell alternatives are supported alongside Morlet wavelets for time-frequency decomposition, configurable through MNE-Python options to handle validated frequency ranges and edge artifacts.

Why compute inter-trial coherence separately from power when analyzing EEG time-frequency data?▼

Inter-trial coherence is computed separately to measure phase consistency across trials without conflating it with power amplitude, ensuring accurate ERP and ERSP-style reporting for downstream statistics.

Do I need existing epochs and analysis plans to generate paper-ready time-frequency maps?▼

Existing epoched data, a DATASET_BRIEF.md, and an ANALYSIS_PLAN.md are required to generate paper-ready time-frequency maps, producing tfr-stage HDF5 and CSV artifacts for later statistics and figures.

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