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analog-neuromorphic-plasticity

Implement calcium-based synaptic plasticity with STDP protocols on BrainScaleS-2.

2|Updated Feb 12, 2026
Search Tags:#STDP#synaptic-plasticity#calcium-dynamics#analog-neuromorphic#brainscales-s2#STC#neural-hardware
Ready to run
npx skills add https://github.com/hiyenwong/ai_collection --skill analog-neuromorphic-plasticity
💬 Prompt for ChatGPT / Claude Chat▼
Please help me install this Agent Skill.
Skill: analog-neuromorphic-plasticity
Source: https://github.com/hiyenwong/ai_collection/tree/main/collection/skills/analog-neuromorphic-plasticity
Command: npx skills add https://github.com/hiyenwong/ai_collection --skill analog-neuromorphic-plasticity

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Enables modeling and verification of calcium-based, multi-time-scale synaptic plasticity on analog neuromorphic hardware, bridging biology and hardware constraints for research and development.

Core Features & Use Cases

  • Calcium dynamics model: Tracks calcium concentration with ms to s scales, enabling STC-inspired learning.
  • Hybrid compute architecture: Combines hardware-accelerated simulation with an embedded solver and bounded precision.
  • Protocol verification: Supports STDP, double-pulse, frequency-dependent, and timing-dependent protocols for validation.
  • Use Cases: Accelerated SNN simulation, plasticity mechanism research, neuromorphic chip development.

Quick Start

Configure a CalciumPlasticityRule with tau_ca, theta_p, and theta_d, simulate STDP pairings, and observe calcium traces and weight changes.

Frequently Asked Questions about analog-neuromorphic-plasticity

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

FAQPage Schema
How do I model calcium-based synaptic plasticity on analog neuromorphic hardware?▼

You can model calcium-based synaptic plasticity by configuring a CalciumPlasticityRule with parameters like tau_ca, theta_p, and theta_d, then simulating spike pairings to observe calcium traces and weight updates on hardware-constrained analog systems.

What is multi-time-scale calcium dynamics in neuromorphic computing?▼

Multi-time-scale calcium dynamics tracks calcium concentration changes from milliseconds to seconds, enabling biologically inspired synaptic time-constant (STC) learning and spike-timing-dependent plasticity (STDP) on neuromorphic hardware.

Can I use BrainScaleS-2 to verify STDP and STC learning protocols?▼

Yes, BrainScaleS-2 emulation supports the verification of STDP, double-pulse, frequency-dependent, and timing-dependent protocols, allowing you to validate multi-timescale plasticity mechanisms under hardware constraints.

Does neuromorphic synaptic plasticity modeling support integer arithmetic and stochastic rounding?▼

Yes, the Skill includes an emulator with integer arithmetic and stochastic rounding to handle hardware-constrained weight updates and bounded precision inherent in analog neuromorphic systems.

Why use an analog neuromorphic approach over standard SNN simulation for plasticity research?▼

Analog neuromorphic hardware provides hardware-accelerated simulation and protocol verification, bridging biological plasticity mechanisms with actual chip constraints to accelerate neuromorphic development.

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