FlyGym / NeuroMechFly
Python framework for embodied sensorimotor experiments with a biomechanical fly, sensory interfaces, and physical environments. Check version-specific documentation when following older tutorials.
Read, and deliberately left unrated. The reasoning is below.
Propose a rating →The evidence
No evidence, no level.A Python framework for embodied sensorimotor experiments with a biomechanical fly, sensory interfaces and physical environments.
https://github.com/NeLy-EPFL/flygym
Deliberately unrated on a second reading, and my first rating of it was wrong. I filed it L1 for shipping neural controllers with stated parameters; reading the current source, a search of src/ for membrane potential, spikes, synapses, firing rate, v_rest or tau_m returns nothing at all. The only controller is six coupled phase-amplitude oscillators in the demo package, indexing preprogrammed steps — a gait generator, not a neuron model. It also uses no connectome data, which puts it exactly where flybody sits: the platform other projects attach a brain to, and something the scale cannot measure. The NeuroMechFly v2 paper’s touchpoints with real flies are qualitative or use recorded kinematics as model input rather than as a comparison axis, so no validation mark either.
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Nearby
All projects →Research code for the Shiu et al. connectome-based leaky integrate-and-fire model, including activation/silencing experiments, notebooks, and FlyWire data configuration.
FlyWire whole-brain LIF implementation based on Shiu et al., with multiple simulation backends and benchmarking tools. This repository supplies the neural model; it is not a complete embodied demo package.
Ratings on thelearningfly.com are proposals, not verdicts. Every one of them is arguable in public.