# Awesome Fly [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

> [!TIP]
> **Build your own fly experiment with [fly-connectome-template](https://github.com/cobanov/fly-connectome-template) by [Mert Cobanov](https://github.com/cobanov).**
>
> Start with a real MaleCNS soma atlas, the anatomical Flybody mesh, and a React + Three.js workbench. Bring your own environment and model; the starter includes a documented model-output format, not a pretrained brain.
>
> **[Use this template →](https://github.com/new?template_name=fly-connectome-template&template_owner=cobanov)** · [Explore the starter](https://github.com/cobanov/fly-connectome-template) · [Model integration guide](https://github.com/cobanov/fly-connectome-template/blob/main/docs/MODEL-INTEGRATION.md)
>
> Source-available under a [custom license](https://github.com/cobanov/fly-connectome-template/blob/main/LICENSE): linked template credit is required in your web UI and repository README.

> A curated collection of fruit fly connectome projects, from Doom and desktop pets to brain models, biomechanical bodies, and research tools.

Explore what people are building with **MaleCNS**, **FlyWire**, and the *Drosophila melanogaster* connectome. Each entry links to its creators' repository and explains what it actually offers.

Start with a [game](#games-and-control-experiments), explore a [desktop fly](#desktop-flies-and-interactive-worlds), or build your own using the [research foundations](#brain-models-and-embodied-simulation).

**Built something with a fly connectome? Add your own repository with a pull request.** Read the [contribution guide](CONTRIBUTING.md), [open a pull request](https://github.com/cobanov/awesome-fly/pulls), or [suggest a project](https://github.com/cobanov/awesome-fly/issues/new?template=add-project.yml).

## Contents

- [Start here](#start-here)
- [Games and control experiments](#games-and-control-experiments)
- [Desktop flies and interactive worlds](#desktop-flies-and-interactive-worlds)
- [Language, art, and other experiments](#language-art-and-other-experiments)
- [Brain models and embodied simulation](#brain-models-and-embodied-simulation)
- [Datasets and official resources](#datasets-and-official-resources)
- [Analysis libraries and viewers](#analysis-libraries-and-viewers)
- [Tutorials and papers](#tutorials-and-papers)
- [Related lists](#related-lists)
- [Contributing](#contributing)

## Start here

A **connectome** records neurons and their connections. A simulation adds assumptions about neuron dynamics, sensory input, and motor output. A moving fly, changing weights, or a game demo does not by itself demonstrate biological fidelity or learned behavior.

- **MaleCNS** covers the adult male central nervous system, including brain and ventral nerve cord. The official project dates v1.0 to **June 8, 2026** and the Cell paper to **September 3, 2026**. [Project and release history](https://male-cns.janelia.org/).
- **FlyWire / FAFB** is an adult female **brain** connectome, a different dataset from MaleCNS. [FlyWire](https://flywire.ai/).
- **Flybody** and **NeuroMechFly** supply simulated bodies and environments. Using either does not automatically connect a brain model to the body.

**Reading the list:** community entries summarize their authors' documentation, reviewed on **September 12, 2026**. These are source reviews, not independent reproductions. **Prototype**, **circuit subset**, and **release pending** identify useful limitations. Neuron counts depend on the release and filtering; synaptic contacts and directed neuron-pair connections are different quantities.

## Games and control experiments

- [Doomfly](https://github.com/nftechie/doomfly) by **nftechie** - MaleCNS simulation connected to ViZDoom through modeled visual inputs and a fixed button readout. Includes plasticity experiments and negative validation results; learned survival has not been demonstrated.
- [FlyDoom](https://github.com/eganeganegan/flydoom) by **eganeganegan** - Research framework comparing a MaleCNS-constrained sparse recurrent controller with rewired graphs, conventional neural networks, and other controls on simple VizDoom tasks.
- [Fly64](https://github.com/ornata/fly) by **ornata** - Hooks a MaleCNS model up to Super Mario 64, with a local dashboard and macOS setup. A playful experimental controller; requires your own game ROM.
- [Fly Brain Minecraft](https://github.com/blendi-remade/fly-brain-minecraft) by **blendi-remade** - Fabric mod that runs a filtered MaleCNS graph for each fly mob, with modeled sensory inputs, motor readouts, and live neural HUDs.
- [fly-flappy](https://github.com/ns2250225/fly-flappy) by **ns2250225** - Browser Flappy Bird experiment running the full MaleCNS v1.0 graph at 50 Hz with engineered visual inputs and either raw DNp01 decoding or a trainable logistic action readout. **Full retained graph; interface and readout are artificial.** The source repository currently has no separate license file.
- [Flyhard](https://github.com/MarkUnthank/flyhard) by **MarkUnthank** - Trains a MaleCNS-based model to operate a steering wheel through simulated fly limbs and connect it to CARLA. Documents a bounded steering result; visual driving remains a future milestone.
- [Help the Fly Escape](https://github.com/dzhng/fly-escape) by **dzhng** - Arrange household objects and observe flies navigating a 3D browser game. Rust/WASM simulation using a **selected MaleCNS circuit**. [Play](https://fly-escape.vercel.app/).
- [Swat](https://github.com/hrook1/Swat) by **hrook1** - Browser arcade game with a visible escape circuit: 6,000 MaleCNS neurons influence evasive movement alongside authored game mechanics. **Circuit subset.** [Play](https://fruitfly-tiny-brain.vercel.app/).
- [FlyBrain](https://github.com/Jhongdlp/FlyBrain) by **Jhongdlp** - MaleCNS-based game-boss experiment with a Rust neural engine, Python training environment, and Three.js viewer.
- [FlyPong](https://github.com/jonatasperaza/FlyPong) by **jonatasperaza** - Pong controller built from a MaleCNS subgraph, with documented controls and negative results for its dopamine-inspired plasticity experiments. **Circuit subset.**
- [Connectome Fighter](https://github.com/Unjuno/connectome-fighter) by **Unjuno** - MaleCNS controller connected to FightingICE through explicit sensory and action mappings, with a research ledger separating connectome structure from project-defined learning rules.
- [Fly Chess Lab](https://github.com/tolatolatop/fly-chess) by **tolatolatop** - FlyWire chess experiment with a Rust/WASM LIF simulation, spike traces, and disconnection controls. Uses an engineered, currently untrained move readout. [Demo](https://tolatolatop.github.io/fly-chess/).
- [fly-craftax](https://github.com/liuzihe02/fly-craftax) by **liuzihe02** - Connectome simulation connected to Craftax, with PPO training of a descending-neuron readout, baseline comparisons, and a replay viewer. **Research prototype.**
- [Fly Dino](https://github.com/cobanov/flyjump) by **cobanov** - Original Chromium Dino controlled by a fixed 80-neuron MaleCNS circuit with simplified leaky tanh dynamics and a 243-parameter readout trained with the cross-entropy method (CEM). Includes live computed activity, reproducible training, held-out benchmarks, and circuit-silencing controls. **Circuit subset:** only the artificial readout is trained. [Play](https://flydino.cobanov.dev/) · [Methods and results](https://github.com/cobanov/flyjump/blob/main/docs/experiment.md).
- [NeuroCraft Fly](https://github.com/evnsnclr/neurocraft-fly-public) by **evnsnclr** - Minecraft project with a recorded MaleCNS-based interactive demo and a release roadmap. **Release pending:** the public repository currently contains project materials, not runnable mod or companion source.
- [FLYFEAR](https://github.com/furkancak1r/flyfear) by **furkancak1r** - Godot horror prototype where a MaleCNS-derived simulation influences a fly and an external adaptive event policy. Includes training and validation reports. [Play](https://furkancakir.dev/flyfear/).
- [FLYT3](https://github.com/seanphan/flyt3) by **seanphan** - Tic-tac-toe against a full-graph MaleCNS LIF simulation with a REINFORCE-trained descending and VNC readout, plus a fire-watch mode that classifies satellite wildfire-damage tiles through the same frozen circuit (60.8% on 5 classes) with live activity and region-lesioning views. **Full retained graph; only the readout is trained.** Reports its own negative control: a pooled-pixel MLP on the same inputs scores 85.7%. Self-hosted demo, no public link.
- [fly-swing](https://github.com/JHC56/fly-swing) by **JHC56** - A MuJoCo fruit fly that web-swings through a random obstacle course like Spider-Man. There is no dodge code. The escape is fired by the real giant fiber circuit from MaleCNS (LC4/LPLC2 -> DNp01, LIF), and the whole brain runs live on screen. The fly picks where to swing with a kNN threat memory built on whitetree. It reaches the goal on 20 out of 20 random courses. **Circuit subset drives the fly; full retained graph is display only.**
- [The Fly's Table](https://github.com/WilliamJones/fly-blackjack) by **WilliamJones** - Heads-up blackjack against a MaleCNS mushroom-body model: 682 projection neurons, 1,200 Kenyon cells, 97 output neurons and 332 dopaminergic neurons with measured wiring, learning at the table through a project-defined dopamine-gated depression rule. One seat, a queue, spectators, and a brain shared through Firestore that persists between players. The same repository holds an 80-neuron Dino controller, a Flybody walker, and odour-conditioning experiments, each with silenced-circuit or dopamine-cut controls. **Circuit subset; only Kenyon-cell-to-output synaptic gains change.** Reports its own results: 30,000 solo hands move the fly from a -45% to a -16% winrate with 52% agreement with basic strategy, disconnecting dopamine removes the gain, and a poker attempt is documented as a negative result. [Play](https://fly-blackjack.vercel.app/).
- [Fly-NAF](https://github.com/ArtyMend07/Fly-NAF) by **ArtyMend07** - Five Nights at Freddy's 1 played by the whole FlyWire v783 graph, 138,639 LIF neurons with their measured weights under a uniform x3 gain and nothing trained. LPLC2 and LC4 drive DNp01 to slam the doors, DNp09 raises the camera tablet, and GABAergic inhibitors silence DNp01 while it is up. On Pirate Cove, LC9 and LC31a drive DNp09 and a project-defined ten-second memory lets DNp04 shut the left door on Foxy. Builds on [fly-brain](https://github.com/eonsystemspbc/fly-brain), GPL v3. **Full retained graph; no trained readout; screen input and mouse readout are hand-made.** A starvation timer forces a look at any hallway unwatched for thirty seconds. Live panel of every soma. Windows; the Linux X11 backend has not run a night. No playable demo. Best run reached 5 AM on night 3. [Video](https://www.youtube.com/watch?v=R4Ogbf33Gfo).
- [Fly Self Driving](https://github.com/suanmiao/fly-self-driving) by **suanmiao** - Drives a simulated street from a 64x32 windscreen using the MaleCNS connectome (165,122 neurons, 25,563,197 synapses). **Complete retained graph:** the wiring is frozen; only one gain per synapse and one leak per neuron are learned, with a random frozen pixel map and steering readout, and the network state is carried between decisions. Completes 58 of 60 across three held-out sets with no car collisions, against a randomly rewired graph (16/20), a linear map (12/20) and an MLP (18/20). One training seed per condition; it does not brake yet. [Demo](https://fly-self-driving.kylon.app)
- [Banana Quest](https://github.com/professorwang/flybrain-banana-quest) by **professorwang** - Browser foraging game on the full FlyWire FAFB v783 graph: 139,255 LIF neurons run in a Web Worker, odor-gradient input is split across left/right antennal ORN pools, and turning, feeding, and startle-escape are gated by descending-neuron (GNG_DESC) and SEZ/motor readout, with a live 63-group activity view and an in-app honesty panel separating measured wiring from artificial mappings. Zero-dependency vanilla JS, reusing the snedea/flybrain data packaging. **Full retained graph; sensory mapping and readout pools are artificial.** [Play](https://professorwang.github.io/flybrain-banana-quest/).
- [fly-cartpole](https://github.com/Curt-Park/fly-cartpole) by **Curt-Park** - Balances CartPole-v1 as a reflex with the MaleCNS flight-stabilisation circuit: 5,459 neurons from the haltere, ocellar and HS-cell inputs to the wing steering motor neurons. **Circuit subset; the wiring stays frozen and only five sensory input gains are tuned,** with a reward signal computed outside the circuit. Untuned it lasts 275.6 steps (random pushes: 22.1); self-tuned it reaches 499.9 on held-out seeds. [Demo](https://curt-park.github.io/fly-cartpole/).
- [Doodle Fly](https://github.com/dtecx/doodle-fly) by **dtecx** - Doodle-Jump-style browser game steered by the whole FlyWire v783 brain: 138,639 LIF neurons with the Shiu et al. 2024 model and parameters run in a Web Worker; the target platform drives LC10a on one side, and six descending-neuron types (incl. DNa02), right minus left, press the left and right buttons after a start-up calibration. The sugar -> proboscis and looming -> giant-fibre circuits are live too. **Full retained graph; target selection, LC10a drive and the button readout are hand-made; nothing is trained.** Reports controls: 0-1 falls in 2 minutes intact, 41-44 with the eyes swapped, hopping in place when blind. [Play](https://dtecx.github.io/doodle-fly/) · [Results](https://github.com/dtecx/doodle-fly#is-it-really-playing).
- [20fly8](https://github.com/dtecx/20fly8) by **dtecx** - 2048 learned in the browser by a FlyWire v783 mushroom-body model: each board cell and tile size drives its own projection neuron (32 of 267), the measured PN -> Kenyon-cell (27,502) and Kenyon-cell -> MBON (62,261) connections carry the smell to 96 output neurons, and approach vs avoidance is read from which dopamine cluster (PAM or PPL1) innervates each MBON. A project-defined dopamine rule driven by a reward-prediction error (TD learning on afterstates) changes only the Kenyon-cell -> MBON gains. **Circuit subset; firing-rate model, not spikes.** Reports frozen-synapse controls over 500 games: random moves 1,103, naive fly 1,594, trained after 3,000 games 6,986 (512 in 75%, 1024 in 15%), nose rewired 925, synapses shuffled 1,287. [Play](https://dtecx.github.io/20fly8/) · [Results](https://github.com/dtecx/20fly8#is-it-really-learning).
- [katamari-connectome](https://github.com/PedroKeita/katamari-connectome) by **PedroKeita** - FlyWire v783 whole-brain LIF simulation (~75k neurons, ~375k synapses across reward, visual, CX, PCB, escape, and PPL circuits) connected to Katamari Damacy REROLL through a Python screen-capture and dual-stick keyboard controller. No RL, no training; a -0.70 lateral turning bias in the readout is zeroed by hand. Reports 4.6 collections/minute from one 181-second session, no baseline. **Circuit subset:** about 54% of FlyWire's neurons; sensory encoding and motor readout are hand-mapped. [Demo](https://katamari-connectome.vercel.app).

## Desktop flies and interactive worlds

- [DesktopFly](https://github.com/DenisSergeevitch/desktop-fly) by **DenisSergeevitch** - A macOS desktop fly combining FlyWire spiking circuits with a MaleCNS brain-to-leg extract, modeled senses, and articulated behavior. Includes an Electron port.
- [gnat](https://github.com/lubabs770/gnat) by **lubabs770** - Linux/Hyprland desktop port of DesktopFly with a brain window and stimulation controls. Uses a **668-neuron circuit subset**.
- [DesktopFly for Linux](https://github.com/somsom10/desktop-fly-linux) by **somsom10** - Python/GTK port of DesktopFly for GNOME on X11 and Wayland, retaining the upstream FlyWire circuit and documenting platform limitations.
- [FlyBrain](https://github.com/snedea/flybrain) by **snedea** - Browser-based FlyWire FAFB v783 LIF simulation with food, touch, light, and temperature inputs and a live neural activity display.
- [FlyWire Neuro](https://github.com/pusulamkendim/flywire-neuro) by **pusulamkendim** - Local FlyWire LIF simulation linked to a persistent 3D body, sensory controls, and recorded runs. Descending-neuron activity selects measured or cached motor behavior. **Research prototype.**
- [Closed-Loop Fly](https://github.com/ZeroXClem/closed-loop-fly) by **ZeroXClem** - Browser sensorimotor loop joining a modeled compound eye and optic lobe to MaleCNS descending-neuron readouts and a simulated flying body.
- [flyverse](https://github.com/tel-0s/flyverse-core) by **tel-0s** - MaleCNS simulation with modeled color vision, smell, taste, wind, locomotion, and an inspectable room environment. Sensory and motor physiology remain project assumptions.
- [NeuroTerrarium](https://github.com/5p00kyy/neuroterrarium) by **5p00kyy** - Inspectable 3D lab with a synthetic terrarium and a separate 51-body MaleCNS giant-fiber microcircuit. Reports a negative topology-control result. **Circuit subset.**
- [FLYBOARD](https://github.com/NullLabTests/flybrain) by **NullLabTests** - CPU arcade interface for injecting current into named MaleCNS populations while viewing the modeled voltage and spike field.
- [Infinite Sugar](https://github.com/cnqso/infinite-sugar) by **cnqso** - Browser artwork placing a FlyWire-based fly in a terrarium with continuous sweet-sensing input. Neural activity drives some movements while wings and small foot motions use supplied patterns. [Experience](https://infinitesugar.cnqso.com/).
- [Barfly](https://github.com/rustyorb/barfly) by **rustyorb** - A fly at a bar who is given nothing to do. The whole FlyWire v783 graph (138,639 LIF neurons, Shiu et al. 2024 model, on [doodle-fly](https://github.com/dtecx/doodle-fly)'s engine) runs in a Web Worker: a sugar-neuron drive is drawn as a beer mug and the proboscis motor neurons decide when he drinks, a looming drive is a door bang and DNp01 makes him flinch, and a made-up buzz meter scales every GABA neuron's outgoing weights. A language model writes his lines from a log of what his body did and never feeds back into the brain. **Full retained graph; the sensory drives, readouts, buzz meter and all dialogue are artificial; nothing is trained.** Reports single-run headless numbers and no biological validation. Runs from a local dev server; no hosted demo. Submitted by the project's author.
- [Fly brews matcha](https://github.com/linhkid/fly-matcha) by **linhkid** - 3D browser scene of a scripted male fly brewing matcha beside a point cloud of his own nervous system. Each sip drives his taste neurons and his moving legs drive their knee sensors, with spikes replayed from leaky integrate-and-fire runs on the **full MaleCNS v1.0 graph** rather than simulated live. The body is scripted (motor neurons fire but do not move it), the recordings are single-seed pilots, and a pre-registered test that sugar drives the proboscis motor neuron MN9 [did not pass](https://github.com/linhkid/fly-matcha/blob/main/specs/matcha-fly/assets/evidence/05/README.md), so no feeding is shown. Runs from a local dev server; no hosted demo. Submitted by the project's author.

## Language, art, and other experiments

- [FLM](https://github.com/nftechie/flm) by **nftechie** - Frozen language model coupled to the retained MaleCNS graph through a trained readout adapter. Language ability comes from the pretrained language model.
- [fly-brain](https://github.com/lixiang1076/fly-brain) by **lixiang1076** - FlyWire LIF simulation with a natural-language interface and project-defined dopamine-learning experiments.
- [Fly / Wirehead](https://github.com/mattyhempstead/fly-wirehead) by **mattyhempstead** - A MaleCNS simulation receives frames from insect videos on a virtual phone. Local Python/C++ simulation, browser observation chamber, and neural telemetry.
- [FlyScroll](https://github.com/ranagwho/Fruitfly-Doomscroller) by **ranagwho** - MaleCNS-based video-feed experiment where modeled visual and mushroom-body activity influences when the viewer advances to the next clip.
- [Stonkfly](https://github.com/nftechie/stonkfly) by **nftechie** - Experimental MaleCNS controller with market-chart inputs, paper trading, and optional Coinbase integration. Includes modeled reinforcement and memory; profitable learning has not been demonstrated.
- [OpenFly](https://github.com/marketcalls/openfly) by **marketcalls** - MaleCNS-based controller for a paper-traded NIFTY options strategy through OpenAlgo. Live trading is opt-in and no profitable edge has been demonstrated.
- [Fly Lab](https://github.com/Apolotary/fly-lab) by **Apolotary** - Ableton Live music experiments driven by simulated fly motor circuits and a small trainable musical readout. The measured wiring remains fixed.
- [Faiku](https://github.com/xyzzyapps/faiku) by **xyzzyapps** - Haiku and glyph-tracing experiment using MaleCNS simulation and mushroom-body-inspired reinforcement, with a separate reduced fallback model.
- [Fruitless](https://github.com/nicodunks/fruitless) by **nicodunks** - MaleCNS intervention study and Three.js visualization testing how blocking modeled mAL output changes activity in courtship-related candidate neurons.
- [fly-odor-onoff](https://github.com/yukincom/fly-odor-onoff) by **yukincom** - Reproducible odor ON/OFF intervention experiments using [Fly Brain Minecraft](https://github.com/blendi-remade/fly-brain-minecraft)'s filtered MaleCNS LIF graph. Includes input-pathway audits and four-PN DM1/VA2 responses under externally scheduled OFF-only input blocking. **Fixed circuit; no biological validation.** [Methods and results](https://github.com/yukincom/fly-odor-onoff/blob/main/experiments/brain-four-pn-readout/README_eng.md).
- [Fruit Fly Fashion](https://github.com/jtc268/fruit-fly-fashion) by **jtc268** - Reproducible art experiment using MaleCNS spike vectors to control the placement, rotation, and scale of print designs.
- [mindmeld-with-fly](https://github.com/Decentricity/mindmeld-with-fly) by **Decentricity** - Sparse MaleCNS reservoir experiments with terminal rendering and recording/replay. **Prototype:** the README places the EEG interface in a future phase.
- [boltzmann-fly](https://github.com/jniimi/boltzmann-fly) by **jniimi** - Energy-based world model of simulated consumer behaviour (the author's own Purchase World model, ICONIP 2026) re-trained as a Boltzmann machine whose couplings are masked to an extracted MaleCNS circuit: the right-hemisphere mushroom body (PN -> Kenyon cell -> MBON). Ships the original dense model as an anchor, degree-preserving and Erdős–Rényi rewiring controls, CPU-reproducible weights, and a results note. **Research prototype:** the fly wiring matches the original on prediction and on one counterfactual parameter, is below it on the other, and flips the sign of the free-energy clamp test (one seed).
- [ENSOphilia](https://github.com/nicpittman/ENSOphilia) by **nicpittman** - El Niño forecasting using an extracted 80-neuron MaleCNS circuit and NOAA ERSSTv6 sea-surface temperatures. Compared against 100 rewired networks; no advantage from biological wiring was found. [Results](https://github.com/nicpittman/ENSOphilia/blob/main/RESULTS.md).
- [BioReservoir](https://github.com/igdigitallab/bioreservoir) by **igdigitallab** - Whole retained MaleCNS graph run as a fixed reservoir for visitor questions: a text embedding sets Poisson rates on real sensory populations, the full brain runs 250 ms of LIF per trial, and the answer is the lateral bias across descending neurons after subtracting each brain's intrinsic handedness measured on neutral reference sentences. Reproduces Shiu et al.'s sugar -> MN9 response; the female BANC connectome fails the equivalent lateral check and that failure is published rather than dropped. **Not trained on outcomes and makes no forecasting claim - entertainment and research. Per-run measurements against rewired-connectome, no-connectome and random-graph controls are published in the repository.** [Live page](https://fly.igdigi.com) · [results](https://github.com/igdigitallab/bioreservoir/blob/main/experiments/001-fly-oracle/RESULTS.md). Submitted by the project's own team.
- [FlyGateDemo](https://github.com/ProfTAlent/FlyGateDemo) by **ProfTAlent** - C#/.NET rate model of the MaleCNS olfactory circuit guarding a real blog: request text becomes odors through an artificial 53-channel nose, 2,044 right-side Kenyon cells with APL-style sparsity encode them, and dopamine-gated depression of KC→MBON synapses implements punishment, reward and novelty. **Circuit subset; rate model, only KC→MBON synapses learn.** One punishment makes the fly avoid 23–88% of later probes of a scanner family at 0.1–8% reader false blocks, while plain cosine on the request text reaches 98.5–100%. Runs on 142,770 bundled anonymized requests.
- [flybrain-connectome](https://github.com/lm203688/flybrain-connectome) by **lm203688** - Generates multi-agent topologies (LangGraph, CrewAI and AutoGen exports) from MaleCNS v1.0 graph motifs and records, as W3C PROV-JSON, which neuron or synapse class each edge came from. A developer toolkit, not a fly simulation or a trained model. [Demo](https://lm203688.github.io/flybrain-connectome/demo/).

## Brain models and embodied simulation

- [Drosophila brain model](https://github.com/philshiu/Drosophila_brain_model) by **philshiu and collaborators** - Research code for the Shiu et al. connectome-based leaky integrate-and-fire model, including activation/silencing experiments, notebooks, and FlyWire data configuration.
- [fly-brain](https://github.com/eonsystemspbc/fly-brain) by **Eon Systems** - FlyWire whole-brain LIF implementation based on Shiu et al., with multiple simulation backends and benchmarking tools. This repository supplies the neural model; it is not a complete embodied demo package.
- [flybody](https://github.com/TuragaLab/flybody) by **TuragaLab / Google DeepMind / HHMI Janelia** - Anatomically detailed MuJoCo fruit-fly body, walking and flight environments, and reinforcement-learning examples. A body and control platform.
- [FlyGym / NeuroMechFly](https://github.com/NeLy-EPFL/flygym) by **NeLy-EPFL** - Python framework for embodied sensorimotor experiments with a biomechanical fly, sensory interfaces, and physical environments. Check version-specific documentation when following older tutorials.
- [flyvis](https://github.com/TuragaLab/flyvis) by **TuragaLab** - PyTorch implementation of connectome-constrained models of the fly visual system, with pretrained models and analysis tutorials.
- [train-your-fly / connectome](https://github.com/eudald-seeslab/train-your-fly) by **eudald-seeslab** - PyTorch Geometric toolkit for connectome-constrained vision models: a *Drosophila* eye model feeding message passing over the FlyWire v783 whole-brain graph to a Kenyon-cell readout. **Fixed wiring; only per-synapse gains and a linear readout are trained.** The [connectome](https://github.com/eudald-seeslab/connectome) study adds colour, shape, and numerosity tasks, randomized-ensemble controls, and manifold analysis; graphs archived on [Zenodo](https://doi.org/10.5281/zenodo.21549559).
- [webgpu-fly](https://github.com/abgnydn/webgpu-fly) by **abgnydn** - Browser-based WebGPU/WASM experiment joining FlyWire brain activity, MANC nerve-cord data, and a Flybody body through explicit approximate motor mappings. [Demo](https://webgpu-fly.pages.dev/).
- [NeuroFly](https://github.com/seven-monarchs/NeuroFly) by **seven-monarchs** - Closed-loop personal research project coupling FlyWire-based neural activity to a NeuroMechFly body, with recorded simulations and documented assumptions.
- [Fruit Fly Lab](https://github.com/vaibhavkedarisetti/fruit-fly-lab) by **vaibhavkedarisetti** - Interactive FlyWire v783 whole-brain LIF simulation with stimulus controls and activity visualization. **Research prototype.**
- [CHIMERA](https://github.com/caparison1234/chimera) by **caparison1234** - Drosophila larval connectome experiment linking a 1,373-neuron circuit to a MuJoCo body and a language-to-stimulus interface. **Larval circuit subset.**
- [Connectome OS](https://github.com/ruvnet/Connectome-OS) by **ruvnet** - Rust LIF runtime and debugging interface for stimulating, cutting, and measuring FlyWire-derived graph activity. **Alpha research preview.**
- [FastFly](https://github.com/eonfathom/FastFly) by **eonfathom** - CUDA and CuPy simulator targeting real-time or faster execution of the FlyWire v783 graph on a consumer NVIDIA GPU.
- [MaleCNS on Apple MPS](https://github.com/seohyunjun/mps-malecns-model) by **seohyunjun** - Experimental PyTorch MPS simulator for Apple Silicon with verified data preparation, named-cell stimulation, and 3D activity reports.
- [drosophila-brain-mlx](https://github.com/Kisame76/drosophila-brain-mlx) by **Kisame76** - Apple MLX and Metal port of the Shiu et al. LIF model on the complete FlyWire v630 graph, with a MaleCNS v1.0 pack, upstream-compatible `run_exp` output, and validation against the Brian2 reference. Includes a degree-preserving shuffled-connectome control. **Apple Silicon only.** [Control result](https://github.com/Kisame76/drosophila-brain-mlx#does-the-wiring-matter).
- [AxonWeave](https://github.com/dhakalnirajan/axonweave) by **dhakalnirajan** - Python library exposing MaleCNS as a sparse, trainable substrate for NumPy, PyTorch, and TensorFlow while keeping source topology and modeling policies explicit.
- [Embodied fly-brain](https://github.com/erojasoficial-byte/fly-brain) by **erojasoficial-byte** - Community research repository combining a FlyWire spiking model with NeuroMechFly/MuJoCo, sensory experiments, and an accompanying preprint.
- [Wired Different](https://github.com/dhruvin-sarkar/ConnectomeLens) by **dhruvin-sarkar** - classifier predicting sexually dimorphic cell types from male CNS connectome (male-cns v1.0) wiring, validated against degree-preserving null graphs; static demo with atlas, pathfinder and guessing game.
- [fault-lines](https://github.com/dhruvin-sarkar/fault-lines) by **dhruvin-sarkar** - Attack tolerance and structural robustness of the complete Drosophila male CNS connectome derived from the fruit fly research published by google
- [price-of-thought](https://github.com/dhruvin-sarkar/price-of-thought) by **dhruvin-sarkar** - Wiring cost and the brain-nerve cord connective in the complete Drosophila male CNS connectome derived from the fruit fly research published by google

## Datasets and official resources

- [MaleCNS](https://male-cns.janelia.org/) - Official male CNS project, cell-type exploration, release history, and [downloads](https://male-cns.janelia.org/download/). Collaboration between FlyEM/HHMI Janelia, Cambridge, MRC LMB, and Google Research.
- [MaleCNS project source](https://github.com/janelia-flyem/male-cns) - Source for the project website and Dimorphism Explorer.
- [MaleCNS Cell Type Explorer](https://github.com/reiserlab/celltype-explorer-drosophila-male-cns) - Source and generated documentation for browsing MaleCNS v1.0 cell types, connectivity, regions, and morphology.
- [MaleCNS supplemental data](https://github.com/flyconnectome/2025malecns) - Derived data and analysis notebooks accompanying Berg et al., including sensorimotor flow and cell-type information.
- [Male optic lobe connectome code](https://github.com/reiserlab/male-drosophila-visual-system-connectome-code) - Analysis and reproduction code accompanying the complete male visual-system connectome study.
- [BANC project](https://github.com/htem/BANC-project) - Data, figures, notebooks, and documentation for the adult female Brain-And-Nerve-Cord connectome and its accompanying publication.
- [FlyWire](https://flywire.ai/) - Adult female brain reconstruction, research resources, and links to exploration tools.
- [FlyWire annotations](https://github.com/flyconnectome/flywire_annotations) - Neuron annotations and other data products for the FlyWire v783 release.
- [Drosophila neurotransmitters](https://github.com/flyconnectome/drosophila_neurotransmitters) - Versioned literature-derived neurotransmitter ground truth linked across major fly connectome datasets.
- [Optic lobe annotations](https://github.com/flyconnectome/ol_annotations) - Cross-dataset cell-type matches between FAFB/FlyWire and the MaleCNS optic lobe.

Follow each upstream dataset's citation and licensing requirements. The license of this list does not relicense linked code, datasets, or artwork.

## Analysis libraries and viewers

- [Codex](https://github.com/murthylab/codex) by **Murthy Lab** - Source for the FlyWire Connectome Data Explorer. [Explore neurons](https://codex.flywire.ai/).
- [FlyBrainLab](https://github.com/FlyBrainLab/FlyBrainLab) - Interactive platform for exploring fly brain data, constructing executable circuits, and studying their modeled function.
- [EOScircuits](https://github.com/FlyBrainLab/EOScircuits) by **FlyBrainLab** - Executable models of the Drosophila antenna, antennal lobe, and mushroom body for early olfactory-system experiments.
- [NAVis](https://github.com/navis-org/navis) by **navis-org** - Python tools for neuron morphology analysis, visualization, transformations, and data access.
- [fafbseg](https://github.com/navis-org/fafbseg-py) by **navis-org** - FlyWire/FAFB segmentation tools for meshes, skeletons, annotations, and connectivity queries, interoperable with NAVis.
- [navis-flybrains](https://github.com/navis-org/navis-flybrains) by **navis-org** - Template brains and transforms for mapping neurons between Drosophila datasets and coordinate spaces.
- [connectome-interpreter](https://github.com/YijieYin/connectome_interpreter) by **YijieYin** - Python library for effective connectivity, path finding, circuit manipulation, and differentiable models at whole-brain scale.
- [connectome data prep](https://github.com/YijieYin/connectome_data_prep) by **YijieYin** - Prepared connectivity matrices and reproducible preprocessing for MaleCNS, BANC, FlyWire, hemibrain, and other datasets.
- [cocoa](https://github.com/flyconnectome/cocoa) by **flyconnectome** - Python library for comparative connectomics, co-clustering, cell typing, and matching across FlyWire, hemibrain, MANC, and MaleCNS.
- [Connecto](https://github.com/schlegelp/connecto) by **schlegelp** - Unified Python interface that normalizes connectivity, metadata, and morphology queries across CAVE and neuPrint datasets.
- [DROCAT](https://github.com/Swida-Alba/Drosophila-cross-dataset-connectome-analysis) by **Swida-Alba** - Python and web toolkit for path finding, network visualization, morphology, and cross-dataset analysis across neuPrint, FAFB, and BANC.
- [BigClust 2](https://github.com/flyconnectome/bigclust2) by **flyconnectome** - Interactive application for exploring high-dimensional connectomic clusterings with linked 2D, 3D, connectivity, and annotation views.
- [neuVid](https://github.com/connectome-neuprint/neuVid) by **connectome-neuprint** - Generates anatomical Drosophila videos from high-level descriptions using neuPrint data and Blender or VVDViewer.
- [malecns](https://github.com/natverse/malecns) by **natverse** - R access to MaleCNS data with metadata and morphology conveniences.
- [coconatfly](https://github.com/natverse/coconatfly) by **natverse** - Comparative connectomics across fly datasets, including FlyWire, hemibrain, MANC, FANC, and MaleCNS.
- [fafbseg for R](https://github.com/natverse/fafbseg) by **natverse** - R tools for FlyWire/FAFB segmentation, meshes, annotations, and connectivity analysis.
- [neuprintr](https://github.com/natverse/neuprintr) by **natverse** - R client for neuPrint, designed to work with the wider natverse neuroanatomy ecosystem.
- [bancr](https://github.com/natverse/bancr) by **natverse** - R package for querying BANC metadata, connectivity, skeletons, and meshes.
- [neuprint-python](https://github.com/connectome-neuprint/neuprint-python) by **connectome-neuprint** - Python client for querying connectivity and metadata through neuPrint.
- [CAVEclient](https://github.com/CAVEconnectome/CAVEclient) by **CAVEconnectome** - Python client for the Connectome Annotation Versioning Engine, used to access versioned connectomic data and annotations.
- [FlyWire network analysis](https://github.com/murthylab/flywire-network-analysis) by **Murthy Lab** - Research scripts and notebooks for network statistics, motifs, connectivity, and graph structure.

## Tutorials and papers

- [Fly connectome data tutorial](https://github.com/sjcabs/fly_connectome_data_tutorial) - Workshop materials for loading, analyzing, and visualizing major fly connectome datasets using Python and R.
- [FlyWire data access](https://github.com/seung-lab/FlyConnectome) - Seung Lab tutorials for programmatic access to FlyWire data, meshes, and annotations.
- [Hemibrain examples](https://github.com/flyconnectome/2020hemibrain_examples) - Code examples accompanying Schlegel and Bates et al. for exploring cell types and circuits in the hemibrain dataset.
- [Neuronal wiring diagram of an adult brain](https://doi.org/10.1038/s41586-024-07558-y) - Dorkenwald et al., Nature (2024), the adult female brain connectome.
- [Whole-brain annotation and multi-connectome cell typing of Drosophila](https://doi.org/10.1038/s41586-024-07686-5) - Schlegel et al., Nature (2024), cell annotations and comparisons across connectomes.
- [Connectome-constrained networks predict neural activity across the fly visual system](https://www.nature.com/articles/s41586-024-07939-3) - Lappalainen et al., Nature (2024), the research behind flyvis.
- [Whole-body simulation of realistic fruit fly locomotion with deep reinforcement learning](https://www.nature.com/articles/s41586-025-09029-4) - The research accompanying flybody.

## Related lists

- [Awesome Fruit Fly Connectome](https://github.com/watthem/awesome-fruit-fly-connectome) - An earlier community list of datasets, tools, papers, and fly-connectome experiments.
- [Fly Connectomics tools](https://github.com/flyconnectome/tools) - Overview of R and Python neuroscience tools maintained by the Cambridge Fly Connectomics Group and Jefferis Lab.

## Contributing

Small projects are welcome. We prioritize a clear connection to fly connectomics, useful documentation, original creators, and accurate descriptions over star counts. Substantial ports belong here when their upstream origin is credited. Announcement-only projects must say that runnable code is pending.

Built a project that belongs here? Read [CONTRIBUTING.md](CONTRIBUTING.md), add your repository to the relevant section, and [open a pull request](https://github.com/cobanov/awesome-fly/pulls). You can also use the [project suggestion form](https://github.com/cobanov/awesome-fly/issues/new?template=add-project.yml) if you do not want to edit the list yourself. The list is maintained by [cobanov](https://github.com/cobanov), who also maintains [Fly Dino](https://github.com/cobanov/flyjump).

## License

[CC0 1.0 Universal](LICENSE). Linked projects retain their own licenses.