ost algorithmic trading bots rely on standard linear heuristics or basic prompt-chained LLMs. We decided to take an experimental detour into computational neurobiology. We built Degeneret Fly, an open-source pipeline that drives a WebGL character using authentic reconstructed MaleCNS v1.0 fruit fly neuron morphology (SWC skeletons) and live market telemetry. How the Pipeline Works Sensory Drive: Top-of-book depth imbalance and bid/ask spread velocity from Polymarket's CLOB WebSocket are normalized and injected directly as synaptic current ($I_{syn}$) into sensory neuron clusters. Biophysical Loop: A continuous 8.333 ms Leaky Integrate-and-Fire (LIF) integration loop computes dynamic membrane voltages ($V_m$) against leak conductances. Volatility Modulator: Octopamine (the insect stress/arousal neuromodulator) scales with spread velocity, dynamically lowering action potential thresholds. Kinematics & Execution: Descending neurons (DNge104) gate 3D character animations and execution decisions in real time. Stack Rendering: Three.js / WebGL2 custom shaders Physics/LIF: TypeScript 8.333 ms integration loop Data: Polymarket CLOB WebSocket API Live Demo & Open Source We have the entire visualizer and execution engine streaming live right now: 🔴 Live Stream: https://kick.com/degenaratefly The repository, SWC parsing scripts, and LIF solver are 100% open source under the MIT license: 💻 GitHub: https://github.com/Rob-bio4/degeneretfly Feedback on conductance equations and WebGL optimization is welcome!