I connected an authentic fruit fly brain to Polymarket order books via WebGL

说明与用途

作者构建了一个由果蝇神经网络驱动的 WebGL 可视化器，实时响应 Polymarket 订单簿数据，展示了新颖的神经启发式交易界面。

问题

Traditional algorithmic trading bots rely on simple heuristics or basic LLM prompts, limiting their ability to capture complex market dynamics.

结果

A live demo where a WebGL character, driven by a fruit fly neural model, reacts in real time to Polymarket order book dynamics, showcasing a novel neuro‑inspired trading interface.

工作流

• 1. Capture top-of-book depth imbalance and bid/ask spread velocity via Polymarket CLOB WebSocket.
• 2. Normalize these signals and inject them as synaptic currents into sensory neuron clusters.
• 3. Run an 8.333 ms Leaky Integrate‑and‑Fire (LIF) loop to compute membrane voltages.
• 4. Scale octopamine levels with spread velocity to modulate action‑potential thresholds.
• 5. Use descending neurons to trigger 3D character animations and execution decisions in real time.
• 6. Render the visualizer with Three.js/WebGL2 and stream live via Kick.

证据

We built Degeneret Fly, an open‑source pipeline that drives a WebGL character using authentic reconstructed MaleCNS v1.0 fruit fly neuron morphology and live market telemetry.

来源

The repository, SWC parsing scripts, and LIF solver are 100% open source under the MIT license.

来源