pinn-neuronal-parameter-estimation

Estimate neuronal model parameters and hidden states from partial voltage observations using PINNs.

2|Updated Feb 12, 2026

Search Tags:#state-reconstruction #parameter-estimation #pinn #neuron-model #morris-lecar #inverse-problem #physics-informed-neural-network

Ready to run

npx skills add https://github.com/hiyenwong/ai_collection --skill pinn-neuronal-parameter-estimation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pinn-neuronal-parameter-estimation
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/pinn-neuronal-parameter-estimation
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill pinn-neuronal-parameter-estimation

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

参数和状态无直接观测时，通过 Physics-Informed Neural Networks (PINN) 进行神经元模型的参数估计与状态重构。该方法对初始参数不敏感，依赖部分观测即可推断未观测变量和生物物理参数。

Core Features & Use Cases

鲁棒性强: 对初始猜测不敏感，能在部分观测下工作。
端到端学习: 同时估计参数与重构状态，适用于 Morris-Lecar 等快慢耦合模型、呼吸神经元等场景。
适用范围广: 适用于多尺度神经元系统的参数估计、状态重构和逆向问题。

Quick Start

Estimate Morris-Lecar model parameters and reconstruct hidden neuronal states from partial voltage observations using PINNs.

Frequently Asked Questions about pinn-neuronal-parameter-estimation

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

FAQPage Schema

How do I estimate neuronal model parameters from partial voltage observations?▼

You can estimate neuronal model parameters from partial voltage observations by using Physics-Informed Neural Networks (PINNs) to fit observed data and infer unobserved biophysical parameters simultaneously.

How does state reconstruction work for unobserved variables in neuron models?▼

State reconstruction for unobserved variables in neuron models works by using PINNs with automatic differentiation to train trainable biophysical parameters that fit partial voltage data and reconstruct hidden states.

Can I use PINNs for parameter estimation in Morris-Lecar and fast-slow bursting neuron models?▼

Yes, you can use PINNs for parameter estimation in Morris-Lecar and fast-slow bursting neuron models, as the method is applicable to multi-scale neuronal systems and breathing neurons.

Do I need full voltage traces to solve the inverse problem for neuronal parameter estimation?▼

No, you do not need full voltage traces; PINNs enable robust parameter estimation and state reconstruction with limited data, relying on partial observations rather than complete datasets.

Why are PINNs robust against inaccurate initial parameter guesses in neuronal inverse problems?▼

PINNs are robust against inaccurate initial parameter guesses because the physics-informed neural network approach is insensitive to initial values while optimizing trainable biophysical parameters against observed data.

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