> For the complete documentation index, see [llms.txt](https://www.parapathology.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.parapathology.com/clippings/awesome-fly-curated-fruit-fly-connectome-projects.md).

# Awesome Fly: Curated Fruit Fly Connectome Projects

A curated collection of fruit fly (Drosophila melanogaster) connectome projects, covering MaleCNS, FlyWire, brain simulations, embodied models, games, and research tools by Mert Cobanov.

* **Curator & Maintainer:** [Mert Cobanov](https://github.com/cobanov)
* **Repository:** [cobanov/awesome-fly](https://github.com/cobanov/awesome-fly)
* **Starter Template:** [cobanov/fly-connectome-template](https://github.com/cobanov/fly-connectome-template)
* **License:** CC0 1.0 Universal (Linked projects retain their own licenses)
* **Scope:** Connectome-grounded projects across adult *Drosophila melanogaster* datasets (**MaleCNS**, **FlyWire / FAFB**, **BANC**), spanning biological network simulations, embodied biomechanical agents, game controllers, interactive desktop applications, and connectomic analysis libraries.

***

## Conceptual & Scientific Foundations

A **connectome** is an empirical map of anatomical neurons and their synaptic connections derived from serial-section electron microscopy (EM). Transforming a static connectomic graph into an active simulation requires defining physiological rules:

1. **Biological Topology $\neq$ Functional Dynamics:** Wiring diagrams constrain communication pathways, but simulations require explicit assumptions regarding synaptic weights, neurotransmitter sign (excitatory vs. inhibitory), leak conductances, membrane time constants, sensory transduction, and motor readouts.
2. **Key Connectomic Datasets:**
   * **MaleCNS (Janelia / Berg et al. 2026):** Complete adult male central nervous system, spanning both the brain and the ventral nerve cord (VNC), providing seamless brain-to-leg motor pathways.
   * **FlyWire / FAFB (Princeton / Seung & Murthy Labs / Dorkenwald et al. 2024):** Complete adult female brain connectome (\~139,000 neurons and tens of millions of synapses).
   * **BANC (Brain and Nerve Cord):** Adult female whole-CNS connectome integrating cephalic and thoracic-abdominal ganglia.
3. **Embodied Simulation (Brain + Body + Physics):** Neural activity alone does not explain behavior. Coupling connectome-constrained controllers to physical engines (e.g., **MuJoCo**) with anatomical biomechanical bodies (**Flybody**, **NeuroMechFly**) enables closed-loop sensorimotor experimentation.

***

## Directory of Highlighted Projects & Toolkits

### 1. Games, Controls & Reinforcement Learning Experiments

| Project                                                                         | Author / Lab  | Mechanics & Biological Substrate                                                                                                                                                                  | Status / Nature                       |
| ------------------------------------------------------------------------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------- |
| [**Fly Dino**](https://github.com/cobanov/flyjump)                              | Mert Cobanov  | Chromium Dino runner controlled by an 80-neuron MaleCNS circuit with leaky tanh dynamics and a 243-parameter readout trained via Cross-Entropy Method (CEM). [Play](https://flydino.cobanov.dev/) | Circuit subset; open-source benchmark |
| [**Doomfly**](https://github.com/nftechie/doomfly)                              | nftechie      | MaleCNS simulation connected to ViZDoom with modeled visual inputs and fixed button readouts; documents negative validation results for survival.                                                 | Research experiment                   |
| [**FlyDoom**](https://github.com/eganeganegan/flydoom)                          | eganeganegan  | Benchmarks MaleCNS recurrent controllers against rewired random graphs and standard ANNs on ViZDoom tasks.                                                                                        | Control framework                     |
| [**Fly64**](https://github.com/ornata/fly)                                      | ornata        | Connects MaleCNS simulation to Super Mario 64 with a local macOS dashboard.                                                                                                                       | Playful controller                    |
| [**Fly Brain Minecraft**](https://github.com/blendi-remade/fly-brain-minecraft) | blendi-remade | Fabric mod driving fly mobs via filtered MaleCNS graphs with live neural HUDs.                                                                                                                    | Interactive mod                       |
| [**Flyhard**](https://github.com/MarkUnthank/flyhard)                           | MarkUnthank   | Connects MaleCNS model to CARLA simulator to evaluate steering through simulated limbs.                                                                                                           | Bounded steering                      |
| [**Help the Fly Escape**](https://github.com/dzhng/fly-escape)                  | dzhng         | 3D browser navigation game driven by a Rust/WASM MaleCNS circuit. [Play](https://fly-escape.vercel.app/)                                                                                          | Selected circuit                      |
| [**Swat**](https://github.com/hrook1/Swat)                                      | hrook1        | Browser game featuring a 6,000-neuron MaleCNS escape circuit influencing movement.                                                                                                                | Circuit subset                        |
| [**FlyPong**](https://github.com/jonatasperaza/FlyPong)                         | jonatasperaza | Pong paddle controller from MaleCNS subgraph testing dopamine-inspired plasticity.                                                                                                                | Negative control                      |
| [**Connectome Fighter**](https://github.com/Unjuno/connectome-fighter)          | Unjuno        | MaleCNS controller interfacing FightingICE with explicit sensory-motor mappings.                                                                                                                  | Research ledger                       |
| [**Fly Chess Lab**](https://github.com/tolatolatop/fly-chess)                   | tolatolatop   | FlyWire chess experiment with Rust/WASM Leaky Integrate-and-Fire (LIF) simulation.                                                                                                                | Untrained readout                     |
| [**fly-craftax**](https://github.com/liuzihe02/fly-craftax)                     | liuzihe02     | Connectome simulation connected to Craftax with PPO descending-neuron training.                                                                                                                   | Research prototype                    |
| [**FLYFEAR**](https://github.com/furkancak1r/flyfear)                           | furkancak1r   | Godot horror game where MaleCNS simulation drives an adaptive event policy.                                                                                                                       | Playable prototype                    |

***

### 2. Desktop Companions, Art & Interactive Worlds

* [**DesktopFly**](https://github.com/DenisSergeevitch/desktop-fly) (DenisSergeevitch): macOS/Electron desktop companion combining FlyWire spiking networks with MaleCNS brain-to-leg motor circuits.
* [**gnat**](https://github.com/lubabs770/gnat) (lubabs770): Linux/Hyprland desktop port of DesktopFly featuring a 668-neuron circuit subset and live stimulation GUI.
* [**DesktopFly for Linux**](https://github.com/somsom10/desktop-fly-linux) (somsom10): Python/GTK3/4 implementation for GNOME on X11/Wayland.
* [**flyverse**](https://github.com/tel-0s/flyverse-core) (tel-0s): Multi-sensory simulation with modeled color vision, olfaction, gustation, and wind mechanosensation.
* [**Infinite Sugar**](https://github.com/cnqso/infinite-sugar) (cnqso): Browser artwork where continuous sweet-sensing input drives neural firing in a terrarium. [Live Demo](https://infinitesugar.cnqso.com/)
* [**FLYBOARD**](https://github.com/NullLabTests/flybrain) (NullLabTests): CPU arcade board for current injection into named MaleCNS populations with live voltage field monitoring.
* [**FLM**](https://github.com/nftechie/flm) (nftechie): Couples a frozen LLM to the MaleCNS graph through an adapter interface.

***

### 3. Brain Models, Neural Simulators & Embodied Physics

* [**Drosophila brain model**](https://github.com/philshiu/Drosophila_brain_model) (Shiu et al. / Seung & Murthy Labs): Landmark whole-brain Leaky Integrate-and-Fire (LIF) model based on FlyWire.
* [**flybody**](https://github.com/TuragaLab/flybody) (TuragaLab / Google DeepMind / HHMI Janelia; *Nature* 2025): Anatomically accurate fruit fly body in MuJoCo with aerodynamic wings, realistic joint limits, and reinforcement learning environments for walking and flight.
* [**FlyGym / NeuroMechFly**](https://github.com/NeLy-EPFL/flygym) (EPFL): Biomechanical simulation framework for embodied sensorimotor control in realistic physical environments.
* [**flyvis**](https://github.com/TuragaLab/flyvis) (TuragaLab; *Nature* 2024): Connectome-constrained deep neural network predicting visual system responses and optic flow processing.
* [**AxonWeave**](https://github.com/dhakalnirajan/axonweave): Python framework exposing MaleCNS as a sparse, differentiable substrate for NumPy, PyTorch, and TensorFlow.
* [**FastFly**](https://github.com/eonfathom/FastFly): High-performance CUDA/CuPy GPU simulator running the FlyWire v783 graph at real-time or faster speeds.
* [**webgpu-fly**](https://github.com/abgnydn/webgpu-fly): Browser-based WebGPU/WASM simulator joining FlyWire cephalic circuits, MANC nerve cord data, and Flybody meshes. [Demo](https://webgpu-fly.pages.dev/)

***

### 4. Connectomic Analysis Toolkits, Registries & Explorers

* [**Codex**](https://github.com/murthylab/codex) (Murthy Lab): Frontend and backend powering the [FlyWire Connectome Data Explorer](https://codex.flywire.ai/).
* [**FlyBrainLab**](https://github.com/FlyBrainLab/FlyBrainLab): Interactive 3D computing environment for constructing, analyzing, and executing Drosophila neural circuits.
* [**NAVis**](https://github.com/navis-org/navis) **&** [**fafbseg**](https://github.com/navis-org/fafbseg-py): Core Python ecosystem for 3D neuron skeletonization, morphology analysis, coordinate transforms, and mesh manipulation.
* [**connectome-interpreter**](https://github.com/YijieYin/connectome_interpreter): High-performance path-tracing, effective connectivity, and differentiable graph manipulation library.
* [**natverse**](https://github.com/natverse) (Cambridge Fly Connectomics / Jefferis Lab): Premier R suite for neuroanatomy and connectomics (`malecns`, `coconatfly`, `fafbseg`, `neuprintr`, `bancr`).
* [**CAVEclient**](https://github.com/CAVEconnectome/CAVEclient): Programmatic interface for the Connectome Annotation Versioning Engine.

***

### 5. Developer Starter Kit: Fly Connectome Template

Mert Cobanov provides a ready-to-build scaffolding template:

* [**fly-connectome-template**](https://github.com/cobanov/fly-connectome-template):
  * **Soma Atlas:** Prepared 3D spatial coordinates from MaleCNS.
  * **Body Mesh:** Anatomically scaled Flybody 3D asset pipeline.
  * **Interface:** React + Three.js interactive workbench for visualizing neural activation and body articulation.
  * **Decoupled Architecture:** Cleanly separates neural model execution from rendering, providing a standardized I/O format for custom neural networks or spiking models.

***

## Relevance to Computational Pathology & Spatial Biology

While connectomics operates on neuronal synapses rather than human tissue specimens, the computational methodologies directly cross-pollinate with digital pathology:

1. **Spatial Graphs & Cell Topologies:** Connectomic path-finding, motif discovery, and co-clustering (as seen in `cocoa` and `connectome-interpreter`) share identical mathematical foundations with spatial cell-interaction graphs in cancer immunology (e.g., \[\[Tumor budding T-cell graphs for pT1 colorectal cancer]]).
2. **Multi-Resolution Registration:** Aligning EM volumes, confocal stacks, and light microscopy in neuroanatomy leverages the same non-rigid deformation and transform engines used in cross-stain histology registration (\[\[Cross-Stain Registration]], \[\[From Samples to Knowledge 2025: QuPath Training Course]]).
3. **Biological Inductive Biases:** Benchmarking connectome-constrained sparse architectures against unconstrained artificial neural networks (e.g., in `flyvis` and `FlyDoom`) mirrors computational pathology efforts to incorporate tissue architecture priors rather than treating histology as unconstrained generic natural image patches.