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tms-eeg-biomarkers

Evaluate reliability and validity metrics for TMS-EEG biomarkers across sessions and labs.

2|Updated Feb 12, 2026
Search Tags:#reliability#validity#connectivity#biomarkers#tms-eeg#tep#gamma-power
One-click install
npx skills add https://github.com/hiyenwong/ai_collection --skill tms-eeg-biomarkers
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tms-eeg-biomarkers
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/tms-eeg-biomarkers
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill tms-eeg-biomarkers

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematically evaluate the reliability and validity of TMS-EEG biomarkers to ensure robust research findings and accurate clinical interpretations.

Core Features & Use Cases

  • Reliability framework: ICC, test-retest, and cross-site reliability analyses for TMS-EEG biomarkers.
  • Validity framework: content, criterion, convergent, and discriminant validity assessments with related measures.
  • Operational toolkit: TE P extraction, gamma-power analysis, connectivity metrics, and quality-control checks.
  • Use cases: clinical neurophysiology studies predicting treatment response, methodological validation, and cross-lab device benchmarking.

Quick Start

Load your EEG data and TMS onset times, then run the TMSEEGReliability and TMSEEGBiomarkers to compute ICC, extract TEP components, and analyze gamma power.

Frequently Asked Questions about tms-eeg-biomarkers

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

FAQPage Schema
How do I calculate ICC and test-retest reliability for TMS-EEG biomarkers?▼

You can evaluate TMS-EEG biomarker validity by running convergent and discriminant validity assessments against related measures, alongside content and criterion validity checks, to ensure robust clinical neurophysiology research findings.

Can I extract TEP components and gamma power using Python for TMS-EEG analysis?▼

Cross-site TMS-EEG reliability is evaluated by applying the reliability framework to compute ICC and test-retest metrics across different labs and devices, enabling accurate cross-site device comparisons and methodological validation.

What is the best way to validate TMS-EEG biomarkers for clinical neurophysiology research?▼

The best way to validate TMS-EEG biomarkers is to systematically evaluate both reliability (ICC, test-retest, cross-site) and validity (content, criterion, convergent, discriminant) to ensure accurate clinical interpretations and treatment response predictions.

Do I need specific Python libraries to assess TMS-EEG biomarker reliability and validity?▼

You need Python libraries such as numpy, scipy, and scikit-learn to assess TMS-EEG biomarker reliability and validity, perform quality-control checks, and extract TEP components, gamma power, and functional connectivity metrics.

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