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neural-dynamics-universal-translator

Translate neural dynamics across LIF, Izhikevich, and HH models at single-spike resolution.

2|Updated Feb 12, 2026
Search Tags:#neuron-models#neural-dynamics#model-translation#single-spike#cross-model-alignment#computational-neuroscience
One-click install
npx skills add https://github.com/hiyenwong/ai_collection --skill neural-dynamics-universal-translator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neural-dynamics-universal-translator
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/neural-dynamics-universal-translator
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill neural-dynamics-universal-translator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Translates neural dynamics across heterogeneous neuron models to enable direct cross-model comparisons at single-spike resolution.

Core Features & Use Cases

  • Cross-model translation: map parameters between models (LIF, Izhikevich, HH) to align spike patterns.
  • Model conversion & analysis: support comparative dynamical analyses and neuroscience research workflows.
  • Use Case: researchers can translate LIF parameters into equivalent Izhikevich parameters for a given input current to study dynamical similarity.

Quick Start

Translate LIF parameters to equivalent Izhikevich parameters for a given input current.

Frequently Asked Questions about neural-dynamics-universal-translator

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

FAQPage Schema
How do I translate LIF parameters to equivalent Izhikevich parameters?▼

To translate LIF parameters to equivalent Izhikevich parameters, apply the parameterized translator to map values for a given input current. This aligns spike patterns across different neuron models for comparative dynamical analysis.

What is cross-model alignment in computational neuroscience?▼

Cross-model alignment maps neural dynamics across heterogeneous neuron models at single-spike resolution. It enables direct comparisons by optimizing spike-pattern similarity between models like LIF, Izhikevich, and HH.

Can I compare spike patterns between HH and Izhikevich models?▼

Yes, you can compare spike patterns between HH and Izhikevich models. The translator supports multiple model types and uses spike-pattern similarity optimization for direct comparative dynamical analyses.

Does the neural dynamics translator support single-spike resolution model conversion?▼

The neural dynamics translator supports single-spike resolution model conversion. It identifies and translates dynamics across different neuron models to enable direct cross-model comparisons.

What are the limitations of cross-model neuron parameter translation?▼

Cross-model neuron parameter translation relies on spike-pattern similarity optimization to align dynamics. Limitations arise when inherent structural differences between heterogeneous models prevent a perfect dynamical equivalence mapping.

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