FlyWire Neuro
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.
Neurons are simulated — leaky integrate-and-fire or better — with documented, tuned parameters.
Dispute this rating →The evidence
No evidence, no level.The Hebbian rule writes directly into the connectome's own synaptic weight values, in place, with a sign-preserving clamp.
https://github.com/pusulamkendim/flywire-neuro/blob/9bafdeb0a04635a79a2581a017fa506585860d02/fly-brain-embodied/brain_body_bridge.py#L385-L398_syn_vals is a mutable view into the loaded FlyWire sparse weight matrix, not a separate readout layer.
https://github.com/pusulamkendim/flywire-neuro/blob/9bafdeb0a04635a79a2581a017fa506585860d02/fly-brain-embodied/brain_body_bridge.py#L337-L346The update runs inside the brain's per-timestep step(), every 10 steps, during the run.
https://github.com/pusulamkendim/flywire-neuro/blob/9bafdeb0a04635a79a2581a017fa506585860d02/fly-brain-embodied/brain_body_bridge.py#L451-L462The project's own divergence analysis reports that the connectome's original wiring dominates and the Hebbian change is a very small perturbation.
https://github.com/pusulamkendim/flywire-neuro/blob/9bafdeb0a04635a79a2581a017fa506585860d02/fly-brain-embodied/compare_plasticity.py#L210-L232The README states the project is an experimental prototype, not a biologically validated digital organism - no published behavioural comparison.
https://github.com/pusulamkendim/flywire-neuro/blob/9bafdeb0a04635a79a2581a017fa506585860d02/README.md#L12
Second reading, downgraded from a proposed L2, on the same ground as two sibling projects running the identical formula. The rule does write into a mutable view of the FlyWire weight values from inside step(), with no optimizer — that part holds. But dW = eta * pre * post * sign − alpha * w applied uniformly across all ~15M synapses is generic pre-post correlation with decay: no dopamine, no compartment, no cell type, nothing that would read differently in a paper about any other animal. L2 asks for a rule grounded in fly biology and this is a general learning rule pointed at a fly graph. The project’s own compare_plasticity.py agrees in effect, reporting that structural wiring utterly dominates the perturbation. L1 is well earned on the FlyWire LIF engine driving a persistent body.
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