A 3D fruit fly that lives on your macOS desktop, with spiking simulations built from FlyWire brain wiring and the MaleCNS brain-to-leg network. It combines identified neural circuits with modeled senses, joints and behavior.
The fly's brain window: 23,210 real neuron soma positions from FlyWire v783, with live spikes flashing at real neuron locations. The two glowing yellow markers are the Giant Fibers — the escape command neurons. Click any region to stimulate it.
- Motor-driven legs: added a MaleCNS v1.0 extract with 1,045 neurons and 17,224 measured connections. Simulated motor activity drives articulated joints, forward/backward stepping and steering, with joint and foot-contact feedback. The existing FlyWire brain connects through a modeled interface.
- Smooth behavior changes: walking, grooming, sleep and flight preserve the current joint pose. Returning to walking carries that pose and its velocity into the mechanics. Body turns, landing pitch and wing folding now ease between states instead of snapping.
- Wing and ledge fixes: raised and reshaped wing hinges prevent body clipping. Moving a window out from under the fly triggers takeoff instead of teleporting it to the window's new edge; threat turns stop overriding later steering once the dart ends.
- Consistent timing and Windows support: the full neural/body feedback loop runs at 120 Hz independently of display refresh. The Electron port shares the motor mechanics and transition fixes; the beetle body remains macOS-only.
- Validation and provenance: added reproducible extraction, source hashes, separate MaleCNS data licensing and 18 locomotor checks on each platform. All native and JavaScript suites pass. Native motion sequences were visually reviewed; Windows-native sensing still needs verification on Windows.
The new circuit adds measured anatomy; neural physiology, sensory tuning and muscle mechanics remain modeled. See evaluation and limitations and data provenance.
- 23,210 neuron soma positions (of 139,255 in FlyWire v783) render the rotating brain window, colored by super-class (FlyWire's coarse cell-type grouping).
- A 668-neuron female FlyWire circuit with 18,968 real connection rows (synapse
counts, signed by neurotransmitter prediction) runs as a 1 kHz
leaky-integrate-and-fire (LIF) simulation:
- LC4 (104) + LPLC2 (210) looming-detector visual neurons
- DNp01 / Giant Fiber (GF) (2) — the escape command neuron
- DNa01 + DNa02 (4) steering neurons · DNp09 (2) forward walking
- DNg11 (6) grooming · MDN (4) backward walking ("moonwalker")
- DNp02/DNp04/DNp11 (6) escape-maneuver (wing) neurons
- their 330 strongest partners, including ascending (proprioceptive) and sensory (wind) neurons
- A 1,045-neuron MaleCNS locomotor circuit adds 16 descending neurons, 622 VNC interneurons, 220 identified leg motor neurons, 153 leg sensory neurons and 34 ascending neurons. Its 17,224 real directed connections represent 708,689 synaptic contacts, with actual paths from descending neurons through the ventral nerve cord (VNC) to all six legs.
- The escape trigger uses simulated Giant Fiber spikes. Cursor approach drives the LC4/LPLC2 pathway, and a GF spike requests takeoff. Sensory gain, electrical-coupling approximation and delays are configured model parameters; the resulting reaction time is not a measurement of a living fly.
The body is procedural. The experimental MaleCNS path drives articulated leg joints and receives joint/contact feedback. Flight, wing-beat, grooming and sleep retain modeled animation and state rules. This is not a full CNS or a biologically calibrated walking simulation.
Requirements: macOS 13+, Xcode Command Line Tools (Swift 5.9+). No permissions or entitlements needed — everything it senses (cursor, window frames, clicks-as-taps, thermal state) is permission-free.
git clone https://github.com/DenisSergeevitch/desktop-fly.git
cd desktop-fly
./build.sh
./DesktopFlyA 🪰 item appears in the menu bar; quit from there. The fly wanders your desktop on a transparent, click-through overlay — it never intercepts your mouse or keyboard.
An Electron + three.js port with the same connectome extracts, neural models, and
the same test suites lives in windows/ (contributed by
@MikeMike88). Requires Windows 10/11 and
Node.js 18+:
cd desktop-fly/windows
npm install
npm start # tray icon 🪰; quit from there
npm test # all three suites, headlessSee windows/README.md for the macOS→Windows mapping table and platform notes (the fly there roams all monitors on its own). The optional stag-beetle body is macOS-only for now.
| item | effect |
|---|---|
| Pause / Resume | freeze the world |
| Show/Hide Brain | toggle the live brain window |
| Escape Test (loom) | inject a looming stimulus, watch the GF fire |
| Move to Next Display | hop the fly across monitors (shown when >1 display) |
| Add / Remove Fly | extra flies (only fly #1 carries the brain) |
| Scare Flies | startle everyone |
| Body: Fruit Fly / Stag Beetle | swap the body geometry — behavior is unchanged |
The same connectome, the same state machine, a different shell. The behavior layer only ever touches the body through one struct, so a second geometry drops in without a line of behavior code: the elytra open when it flies or when the escape descending neurons fire a grounded threat posture, and the membranous hindwings underneath are the surfaces that actually beat.
The brain window is interactive: hovering pauses the rotation; clicking a region "optogenetically" stimulates the ~60 nearest circuit neurons for 400 ms. Spikes propagate through the extracted FlyWire graph and the configured body interface: the Giant Fiber requests escape, DNg11 requests grooming, and an asymmetric DNa01/02 stimulus changes the steering drive.
| body behavior | driven by |
|---|---|
| escape takeoff | DNp01 giant fiber spike |
| walk vs. rest | DNp09 rate through a modeled state threshold |
| leg activation and grounded movement | MaleCNS motor rates → modeled joints and foot contacts |
| steering drive | DNa01+DNa02 activity passed to the male descending populations |
| grooming | DNg11 rate |
| backward scoot | MDN burst |
| nervous darting | LC4/LPLC2 population rate |
| wing-beat effort, threat wing-raise | DNp02/04/11 rate |
| spontaneous takeoff | whole-population arousal |
FlyWire population rates drive corresponding male descending cell types through an explicit modeled interface between two specimens. Within MaleCNS, published connections link descending neurons, VNC interneurons, motor neurons, leg sensory neurons and ascending feedback. There are no invented cross-specimen synapses in the data.
Motor channels use named tibial and trochanteral flexors/extensors, sternal anterior/posterior coxal rotators, and named promotor/remotor groups. Body joint angles, velocities and contact/load estimates feed leg-local sensory inputs. Peripheral nerve and receptor-class identities are measured annotations; joint tuning, muscle forces and the conversion of those measurements into current are modeling choices. Fast cursor motion continues to stimulate the original FlyWire sensory pathway.
- Window terrain: window top edges are ledges — the fly lands on them, walks along them, follows nearby edge movement, and takes off when its supporting edge moves away or closes.
- Window looms: a window appearing near the fly feeds the looming pathway; the circuit decides whether to flee your dialogs.
- Clicks are substrate taps; clicking next to the fly startles it through the wind→GF pathway. Typing is vibration (idle-time API — knows when keys were pressed, never which).
- Circadian rhythm: dawn/dusk activity peaks, midday siesta, night quiescence. Sleep: idle at night → it sleeps, breathing slowly, with raised arousal threshold; it grooms after waking.
- Temperature: flies are ectotherms — a hot Mac is a faster fly.
data/ ships with compact derived files. To rebuild them from the raw
FlyWire Codex dumps (~60 MB download):
mkdir -p /tmp/flywire && cd /tmp/flywire
B=https://storage.googleapis.com/flywire-data/codex/data/fafb/783
curl -O "$B/classification.csv.gz" -O "$B/coordinates.csv.gz" \
-O "$B/connections.csv.gz" -O "$B/consolidated_cell_types.csv.gz"
cd - && python3 etl.py /tmp/flywireThe separate MaleCNS extractor downloads three public Feather tables (~1.11 GB) into a temporary directory and regenerates the compact locomotor graph:
python3 -m pip install numpy pandas pyarrow
python3 etl_malecns.py /tmp/fly-male-cns --downloadIt writes data/locomotor_circuit.json and data/locomotor_report.json.
The circuit records exact source URLs, SHA-256 hashes, native body IDs and
annotations. The report records real descending-to-motor paths and omitted
input coverage. See data/LOCOMOTOR_PROVENANCE.md
for the extraction rules and data/model boundary. Keep raw downloads outside
the repository; the original FlyWire files are not changed by this extractor.
./DesktopFly --simtest # circuit invariants and stimulus responses
./DesktopFly --behaviortest # end-to-end neural/body checks
./DesktopFly --locomotortest # actual MaleCNS closed loop, direction, lesions, frame-rate checks
./DesktopFly --snapshot f.png # offscreen body render (3/4 perspective)
./DesktopFly --snapshot f.png --top [--flying] [--beetle] # the overlay's own
# top-down orthographic view, the one users see
./DesktopFly --brainshot b.png # offscreen brain render
./DesktopFly --snapshot walk.png --top --walking # pose from the live motor circuitThe connectomes supply anatomy and contact counts, not a working physiological simulation. LIF dynamics, excitability, synaptic signs/delays, electrical-coupling boosts, rate normalization, the interface between specimens, sensory tuning, muscle mechanics and behavioral thresholds are configured models.
MaleCNS retains original neurotransmitter predictions and raw counts. The current sign convention is ACh+, GABA− and Glu−; unresolved/modulatory edges have zero direct current while retaining their source contacts. Motor channels retain only part of their full incoming contacts; the report provides exact coverage by leg and channel. Other inputs and much of the complete nervous system are omitted.
Connectivity alone does not establish alternating gait, stable balance or realistic muscle recruitment: a network may co-contract or settle under tonic drive. The motor evaluation requires sustained stepping after startup, physical backward motion, causal steering and loss of propulsion after motor silencing. The complete sensor/neuron/body feedback loop runs at 120 Hz independently of render refresh, with 1 kHz neurons and 600 Hz mechanical substeps. Muscle force and relaxation parameters are calibrated model choices; see evaluation. Anatomical path checks and software behavior tests do not demonstrate agreement with measured fly locomotion. The brain window continues to show the FlyWire visualization rather than all 1,713 simulated cells together.
Code is MIT. The original FlyWire-derived brain_points.json and circuit.json
are CC BY-NC 4.0. The MaleCNS-derived locomotor_circuit.json and
locomotor_report.json are CC BY 4.0 — see
data/DATA_LICENSE.md.
If you use this, cite:
- Dorkenwald, S. et al. Neuronal wiring diagram of an adult brain. Nature 634, 124–138 (2024). https://doi.org/10.1038/s41586-024-07558-y
- Schlegel, P. et al. Whole-brain annotation and multi-connectome cell typing of Drosophila. Nature 634, 139–152 (2024). https://doi.org/10.1038/s41586-024-07686-5
- MaleCNS v1.0 dataset, by FlyEM/HHMI Janelia, University of Cambridge, MRC Laboratory of Molecular Biology and Google Research.