EEG Paradigm Designer

Design EEG paradigms isolating ERP components with validated timing and trial counts.

34|5|Updated Feb 28, 2026
One-click install
npx skills add https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills --skill eeg-paradigm-designer-neuroaihub
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: EEG Paradigm Designer
Source: https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills/tree/main/skills/eeg-paradigm-designer
Command: npx skills add https://github.com/NeuroAIHub/awesome_cognitive_and_neuroscience_skills --skill eeg-paradigm-designer-neuroaihub

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Designing EEG paradigms that isolate specific ERP components requires expert knowledge about timing constraints, trial counts, subtraction control conditions, and artifact mitigation, and non-specialists often choose parameters that create ERP overlap or confounded sensory responses without realizing it.

Core Features & Use Cases

  • Component-to-paradigm mapping that links each ERP signature (P1, N170, N2pc, P3b, N400, P600, MMN, ERN, LRP, CNV, SSVEP) to canonical designs, latency targets, and appropriate electrode montages.
  • Timing and trial guidance covering ISI/SOA ranges, jitter strategies, epoch windows, and trial-count targets with built-in attrition buffers to deliver clean averages.
  • Control subtraction design outlining matched stimuli, montage density, and checks for common pitfalls such as overlap, habituation, response confounds, and baseline contamination.
  • Use case: plan an N400 sentence reading experiment or a P3b oddball study by locking in ISIs, montages, block structure, and artifact-resilient trial counts before data collection.

Quick Start

Ask the skill to design an EEG paradigm isolating your ERP component with validated timing, trial counts, and subtraction logic.

Frequently Asked Questions about EEG Paradigm Designer

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

FAQPage Schema
How do I design an EEG paradigm that isolates ERP components without signal overlap?

Designing an EEG paradigm that isolates ERP components requires validated timing, jitter strategies, and matched control conditions to prevent signal overlap. The skill maps component-specific ISIs, electrode montages, and subtraction logic to deliver clean difference waves.

What is the appropriate trial count and ISI range for an N400 semantic violation experiment?

The appropriate trial count and ISI range for an N400 semantic violation experiment depends on target latency and artifact mitigation needs. The skill provides component-specific trial-count targets with attrition buffers and jitter strategies to ensure clean signal averages.

How do I set up control subtraction conditions for a P3b oddball study?

Setting up control subtraction conditions for a P3b oddball study involves matched stimuli and baseline checks to avoid confounded sensory responses. The skill outlines subtraction logic and evaluates montage density to isolate the target difference waves.

Can I use this to plan timing parameters for visual search tasks isolating the N2pc?

Yes, you can plan timing parameters for visual search tasks isolating the N2pc. The skill supports component-to-paradigm mapping for N2pc designs, providing appropriate SOA ranges, epoch windows, and artifact mitigation requirements.

What are common pitfalls when choosing electrode montages for ERP difference waves?

Common pitfalls when choosing electrode montages for ERP difference waves include baseline contamination and habituation confounds. The skill evaluates montage density and checks for response confounds to ensure your subtraction logic yields valid results.