Encode. Spike. Wire. Stimulate. Deploy.
Modular, hardware-agnostic libraries for spiking neural networks and bio-inspired computation.
Limen Neural is a solo research org building small, reusable building blocks for SNNs — encoding, dynamics, topology, training loops, GPU kernels, interchange (NIR), and runtimes. Work is experimental, agent-assisted, and released under permissive licenses for anyone who wants to try it.
This org is intentionally small. Broader experiments, tooling, quantization labs, viz, cloud notes, and one-off research live under my personal account @rmems so Limen-Neural stays a clean core surface for a solo maintainer.
I am a solo maintainer.
I am currently enrolled at Western Governors University (WGU) in AI Engineering, and I am investing more time learning and manually reviewing code in:
- Rust
- Python
- Julia
- C# / .NET
Issues and PRs of any size are welcome.
Limen Neural keeps hard repo boundaries. Each repository owns one concern.
| Layer | Purpose | Core repos |
|---|---|---|
| Encoding | Analog / feature streams → spike trains | axon-encoder |
| Neuron dynamics | Biologically grounded models + neuromodulation | neuromod |
| Topology & wiring | Graphs, delays, sparse synaptic maps | synaptic-wiring |
| Interchange | Framework-agnostic SNN IR (NIR) | nir-rs |
| Training loops | Offline / closed-loop plasticity | plasticity-lab |
| GPU kernels | Blackwell-oriented CUDA / Rust compute | myelin-accelerator |
| Runtime | Headless SNN inference daemon | brainstem-daemon |
| Transport | Spike wire protocol, ZMQ transport, and REST contract between components | corpus-ipc |
| Reward shaping | Neuromodulatory critic for plasticity | limbic-critic |
Shared org CI and the profile README live in .github.
| Repository | Role |
|---|---|
| neuromod | Core SNN library: LIF, GIF, Izhikevich, FitzHugh–Nagumo, Hodgkin–Huxley, neuromodulators, plasticity hooks |
| axon-encoder | Sensory / feature → spike encoding (rate, delta, latency, population, …) |
| synaptic-wiring | Topology generators, axonal delays, sparse wiring |
| nir-rs | Pure-Rust NIR graph model + optional HDF5 .nir I/O |
| plasticity-lab | Domain-agnostic reward-modulated training loops around neuromod |
| myelin-accelerator | Low-level CUDA/Rust kernels (Blackwell / sm_120, ternary paths, routing/SAT experiments) |
| brainstem-daemon | Headless SNN inference runtime (soma-daemon) |
| corpus-ipc | Spike and neuromodulator wire protocol and IPC transports (ZMQ, REST contract) for SNN runtimes |
| limbic-critic | Neuromodulatory reward-shaping primitive (Environment → Critic → ModulatorVector) for plasticity |
| Crate | crates.io | docs.rs |
|---|---|---|
neuromod |
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axon-encoder |
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nir-rs |
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synaptic-wiring |
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limbic-critic |
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plasticity-lab |
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myelin-accelerator |
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corpus-ipc |
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brainstem-daemon |
Not published yet | — |
| Repository | Role |
|---|---|
| .github | Org profile + shared GitHub Actions workflows |
Personal and broader experimental repos (quantization bridges, MoE→SNN labs, telemetry, viz, HDL, trading research, agent tooling, cloud portfolio notes, Julia research apps, etc.) are not listed as Limen-Neural surface area. Browse @rmems if you are looking for those.
Examples of that wider sandbox include SAAQ / symbolic-regression work, hybrid MoE–SNN labs, gaming and mining telemetry collectors, spike visualization, SystemVerilog FPGA sketches, and multi-language playgrounds. They move faster, break more often, and are kept out of this org on purpose.
- Rust — performance-critical infrastructure: dynamics, encoding, wiring, IR, kernels, runtimes
- Julia — research-scale simulation and personal language practice (packages live under @rmems unless promoted here)
- Python / C# .NET — growing personal fluency for review, tooling, and broader ecosystem access (not a promise of first-class org packages yet)
- Hard boundaries — one repo, one concern; no cross-layer state duplication
- Portable & reproducible — CPU-first where possible; CUDA/FPGA paths explicit and optional
- Permissive licenses — MIT / Apache-2.0 unless a repo says otherwise
Python accessibility across open neuromorphic frameworks remains a longer-term interest as the core matures.
- Core SNN stack quality — stable APIs in
neuromod, encoders, mesh, and training loops - NIR in Rust — interchange without forcing a Python runtime
- GPU neuromorphic kernels — Blackwell-oriented paths in
myelin-accelerator - Hybrid SNN–LLM / quantization — mostly explored in personal
@rmemslabs, then folded back only when a piece is modular enough for this org
Shared workflows live in Limen-Neural/.github/workflows.
Typical gates (per language / repo):
- Rust — fmt, Clippy, build/test, docs, feature matrix, MSRV where configured
- Julia — package build, tests, formatting, coverage (shared templates; Julia packages are primarily under
@rmems) - Containers — optional reproducible images (GHCR / Docker Hub) where a repo opts in
Each library README shows its own badges. Agents and humans both benefit from failing early.
Limen-Neural/.github is the organization profile (what you are reading on https://github.com/Limen-Neural) and the home for shared GitHub configuration.
Libraries are permissively licensed. Use them, fork them, break them, rebuild them.
Issues and PRs are welcome — small fixes, docs tweaks, big features, all of it. I am a solo maintainer, so replies can take a bit.
Solo experimental neuromorphic libraries — Limen Neural · maintained by @rmems · 2026
