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F1 — Move the sensory boundary outward: let the optic lobe compute motion and looming #6

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@kkokosa

Today the retina encoder injects rates straight into T4 and LC4 — i.e. C# computes what the optic lobe should compute from light. The optic lobe (lamina → medulla → lobula/lobula plate) is in the checkpoint; whether the uniform-LIF dynamics make it work is unknown and cheap to test.

Deliverables

  1. Test the optic lobe (CLI, ~1 hour): drive the photoreceptor / lamina layer (R1–R6 or L1/L2) with a moving pattern via dotfly run --stimulate and check whether T4a–d become direction-selective and LC4 expansion-tuned in this model.
  2. If it does: photoreceptor-level retina encoder — luminance per ommatidium → photoreceptor rate — and let the connectome compute motion and looming itself (removes Retina.cs's dark-fraction / image-shift logic).
  3. Landing triggered by visual expansion (LC4 / Giant Fiber) gated by odor, as in flying flies (van Breugel & Dickinson 2012), instead of "odor high and sugar below".
  4. Object-approach readouts: LC10 / LC11 → their descending targets, if they respond — a measured "approach dark objects" behaviour (Wu et al. 2016; Keleš & Frye 2017).
  5. New findings written up in PLAN.md §12 and docs/findings.md.

Acceptance: no C# computes what a neuron in the checkpoint computes; encoders reduce to physically defined light / odor / wind / contact transductions; behaviour verified in the room demo.

Context: roadmap, measured vs engineered, PLAN.md §11 (F1). Dombrovski et al. 2023 (LC4 → DNp02/DNp04 gradients); Lappalainen et al. 2024 showed the connectome wiring suffices for T4/T5 selectivity with fitted parameters.

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    featureA roadmap feature (PLAN.md §11)run-the-real-flyMoves the sensory/decision boundary from adapters into the connectome

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