Banana Quest
Browser foraging game on the full FlyWire FAFB v783 graph: 139,255 LIF neurons run in a Web Worker, odor-gradient input is split across left/right antennal ORN pools, and turning, feeding, and startle-escape are gated by descending-neuron (GNG_DESC) and SEZ/motor readout, with a live 63-group activity view and an in-app honesty panel separating measured wiring from artificial mappings. Zero-dependency vanilla JS, reusing the snedea/flybrain data packaging. Full retained graph; sensory mapping and readout pools are artificial.
Nobody has read this one closely enough to attach evidence to a level. Until they have, it stays unrated — a guess would be worse than a gap.
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No evidence, no level.Nothing filed yet. The description above is carried over from cobanov/awesome-fly and townie/awesome-fruit-fly, which is a source review — not an independent reproduction, and not enough on its own to earn a level.
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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.