flywire-playground
FlyWire sub-circuits as spiking networks that play games using the fly’s own dopamine update rule.
Synapses change under a modeled rule grounded in fly biology — for example dopamine-gated change on Kenyon-cell → MBON synapses in the mushroom body. Learning begins here.
Dispute this rating →The evidence
No evidence, no level.Plastic synapses are depressed by the product of a decaying eligibility trace and a dopaminergic compartment gate, written directly into the connectome weight array and floored at a fraction of the original measured weight.
https://github.com/hills-dong/flywire-playground/blob/d041a2770ad8ac07929f66477d864a4b0e74cc5f/flysmell/agent.py#L168-L182The leaky integrate-and-fire parameters follow the published Shiu et al. 2024 Nature whole-brain model rather than being chosen for the demo.
https://github.com/hills-dong/flywire-playground/blob/d041a2770ad8ac07929f66477d864a4b0e74cc5f/README.md
L2: dopamine-gated depression on FlyWire KC→MBON synapses with an eligibility trace and homeostatic recovery toward the measured baseline. Neuron parameters are taken from the Shiu et al. 2024 whole-brain model rather than tuned by hand, which is why L1 is comfortably cleared on the way. Not L3: no published comparison of its behaviour against real flies.
Record
Nearby
All projects →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.
Research framework comparing a MaleCNS-constrained sparse recurrent controller with rewired graphs, conventional neural networks, and other controls on simple VizDoom tasks.
Ratings on thelearningfly.com are proposals, not verdicts. Every one of them is arguable in public.