Neuromodulation + Eligibility Traces (Three-Factor Learning)
CommunityThree-factor learning guided by neuromodulation.
Education & Research#STDP#neuromodulation#eligibility-traces#three-factor-learning#online-plasticity#neuroscience-inspired-ai
Authorsovr610
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Enables online, neuromodulation-driven gating of eligibility traces for three-factor learning, bridging local synaptic activity with delayed modulatory signals to drive plasticity.
Core Features & Use Cases
- Supports accumulating, replacing, and Dutch trace variants with rate-based and STDP kernels, enabling flexible online learning in biologically inspired architectures.
- Provides end-to-end config via EligibilityConfig, NeuromodConfig, ThreeFactorConfig, and PlasticityFullConfig for online, hybrid, and auxiliary_loss modes.
- Real-world use: accelerate reward-guided adaptation in cognitive agents by gating weight updates with DA/ACh/NE/5-HT signals.
Quick Start
Initialize the Neuromodulation + Eligibility Traces skill and execute a minimal online three-factor update using a reward signal.
Dependency Matrix
Required Modules
torch
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Neuromodulation + Eligibility Traces (Three-Factor Learning) Download link: https://github.com/sovr610/refffiy/archive/main.zip#neuromodulation-eligibility-traces-three-factor-learning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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