A 3D fruit fly on macOS desktop powered by the real FlyWire connectome

A new open-source macOS app, DesktopFly, simulates a 3D fruit fly on the desktop using a live spiking simulation of the real FlyWire connectome, with 23,210 neuron soma positions from FlyWire v783 and a 668-neuron circuit with ~19,000 synaptic connections. The fly reacts to cursor movement through real looming-detector neurons (LC4/LPLC2) and escapes only when the Giant Fiber neuron spikes, matching real fly behavior in ~4 ms. The project, available on GitHub, requires macOS 13+ and Xcode Command Line Tools, and offers an interactive brain window for optogenetic stimulation.

A 3D fruit fly that lives on your macOS desktop — driven by a live spiking simulation of the real FlyWire https://codex.flywire.ai connectome. It walks across your windows, grooms, sleeps, and decides to flee your cursor with the same neurons a real fly uses. 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. 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 circuit with ~19,000 real synaptic connections 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 Escape is not scripted. Your cursor's approach becomes looming input to the real LC4/LPLC2 cells; the fly takes off only when the Giant Fiber actually spikes through its real synapses — ~1,200 synapses of feedforward inhibition push back, which is why slow approaches are tolerated and fast lunges trigger escape in ~4 ms, just like the real animal. The body itself is procedural FlyWire is a brain connectome — no body geometry exists , with a tripod gait, visible wing-beat, altitude-scaled flight, grooming, and sleep postures. 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 ./DesktopFly A 🪰 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. | 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 | The brain window is interactive : hovering pauses the rotation; clicking a region "optogenetically" stimulates the ~60 nearest circuit neurons for 400 ms. The fly's reaction is whatever the real network does downstream — click the Giant Fiber and it escapes; click DNg11 and it grooms; click one side's DNa01/02 and it turns. | body behavior | driven by | |---|---| | escape takeoff | DNp01 giant fiber spike | | walk vs. rest, walking speed | DNp09 rate | | steering | DNa01+DNa02 left−right rate difference | | 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 | The loop also closes body→brain: the gait rhythm feeds the circuit's real ascending proprioceptive neurons in phase with the legs, and fast cursor motion stimulates its sensory wind partners. Window terrain : window top edges are ledges — the fly lands on them, walks along them, rides a window you drag, and startles when one closes under its feet. 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/flywire ./DesktopFly --simtest circuit invariants: GF silent at rest, 4 ms loom latency, ... ./DesktopFly --behaviortest 17 end-to-end checks: stimulate neurons - body reacts ./DesktopFly --snapshot f.png offscreen fly render ./DesktopFly --brainshot b.png offscreen brain render Honesty section: the connectome gives wiring, not physiology. The LIF dynamics, neurotransmitter signs ACh+, GABA−, Glu− , the gap-junction boost on LC→GF and wind→GF documented electrical coupling , synaptic delays, and the sensory transduction cursor → looming value are standard modeling choices layered on the real graph. Everything downstream of the sensory neurons — who connects to whom, and how strongly — is FlyWire data. Code is MIT. The files in data/ are derived from FlyWire FAFB v783 and are CC BY-NC 4.0 — see data/DATA LICENSE.md /DenisSergeevitch/desktop-fly/blob/master/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 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 https://doi.org/10.1038/s41586-024-07686-5