An open intellectual initiative to reimagine how machines understand code — inspired by the human brain.
NeuroCode is a cognitively inspired framework for understanding source code.
It simulates a neural memory system for machines by extracting lightweight "code neurons" from source code, documentation, and usage patterns.
These code neurons are:
- Activated only when relevant
- Forgotten when unused (simulating memory decay)
- Context-weighted based on frequency and recency
- Organized to mimic human cognitive behavior (contextual recall, associative memory, long-term consolidation)
🎯 The ultimate goal:
To reduce reliance on constant full LLM inference by emulating selective memory recall — the way the human brain activates specific memory pathways depending on the task.
In many domains, it's impractical or impossible to pretrain on proprietary or evolving data (e.g., private source code, stories in progress, custom ontologies).
NeuroCode offers a new model: treating knowledge as modular and pluggable.
- You can inject dynamic code or domain-specific memory on the fly.
- The system decides which neurons to activate, ignore, or decay — just like adaptive cognitive memory.
- This makes NeuroCode useful for real-time, domain-specific, or privacy-critical environments.
Read the full open-initiative concept PDF here:
👉 initiative.pdf
Includes theoretical foundation, design principles, and architecture.
- 🧠 Code neuron extractor & semantic linker
- 🧩 Modular analyzers for generating cognitive embeddings
- 🔁 Context-aware recall simulation
- 🧪 Entry point script:
main.py
To keep the repo minimal:
- No pretrained data
- No saved models
- No test sets
Refer to docstrings in each module to simulate your own experiments.
# Clone and install
git clone https://github.com/FalahMsi/neurocode.git
cd neurocode
python -m venv .venv
.venv\Scripts\activate # On Windows
pip install -r requirements.txt
python main.py
🙋 Looking for Adoption
This is a public, open-source intellectual initiative.
Due to personal resource constraints, I cannot continue development alone.
If you’re a developer, researcher, or organization interested in expanding or building upon this concept — you’re welcome to fork, adapt, or reach out.
📫 Email: info.alharbi94@gmail.com
🤝 Contributions and collaborations are highly encouraged.