Python library for analysis of neuroanatomical data.
Embodied Drosophila: 138,639-neuron whole-brain connectome simulation (FlyWire v783) in a biomechanical body (NeuroMechFly v2 / MuJoCo). Vision, olfaction, gustation, flight, and emergent behaviors — all from the real connectome.
Tools to work with the FlyWire connectome. Fully interoperable with navis.
Windows port (C#/.NET 8/Direct3D11) of desktop-vibe-fly - a 3D fruit fly on your desktop driven by a live FlyWire connectome simulation, with a vibecode nose for AI agent activity. Fork/port of kulikov0/desktop-vibe-fly, itself a fork of DenisSergeevitch/desktop-fly.
Virtual organisms powered by real brain wiring. Connectome data → spiking neural network → physics body → emergent behavior.
Linux/X11 port of DesktopFly (desktop-fly): a 3D fruit fly on your GNOME desktop, driven by a live spiking simulation of the real FlyWire connectome. Python + GTK3 + cairo, no Electron.
Whole-brain Drosophila simulation at 2.2x real time on 4 CPU cores, no GPU. 138,639 neurons bit-identical to the reference, with nine switchable neuron models and a live 3D interface.
🪰 Chat with 138,000 neurons — whole-brain fruit fly simulation with natural language interface and dopamine learning
A bio-inspired RNN that fuses Drosophila connectome constraints with valence-modulated plasticity. Uses reservoir computing: fixed realistic circuits for innate odor paths plus learnable dopamine-gated synapses. Captures learning dynamics and aversive-conditioning limits from hardwired biases.
Code for my Bachelor's project: Utilizing the neural network architecture of a fly brain for image processing
基于FlyWire真实神经元数据的球形脑空间模拟器
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