FlyAim

Drives a closed-loop aiming task from MaleCNS v1.0, 166,700 neurons and 25,582,938 edges, against a degree-preserving shuffle, a PID ceiling and a random floor on matched seeds and frame budgets. The pre-registered verdict is that the wiring makes no causal contribution, and the result is stronger: both network arms end up significantly further from the target than random, 412.5 and 430.9 pixels against 251.7. Making the connectome weights learnable under a three-factor rule failed all three gates too. The README insists what is refuted is this LIF model with static weights, not the fly.

Official site ↗

#negative-result#preregistered#shuffled-control#aiming#lif#plasticity#gpu#malecns