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Embodied intelligence requires effective control as environments, movement demands and body morphologies change. Biological nervous systems support such adaptability through highly structured connectivity, yet whether evolved neural wiring itself confers a computational advantage remains unclear. Here we use the adult Drosophila brain connectome as a fixed recurrent structural prior for closed-loop embodied control. In a neuromechanical digital fly, connectome-based and multilayer-perceptron controllers perform comparably during nominal locomotion but diverge as control demands change. Across vertical terrain negotiation, lateral direction turning and longitudinal speed modulation, the connectome exhibits a consistent advantage, improving obstacle negotiation and speed tracking while supporting smoother directional reconfiguration. Mechanistic analyses reveal spontaneous recruitment of behaviourally relevant sensorimotor pathways and distinct local policy geometry associated with robust adaptation. The same connectome prior improves locomotion after transfer to a quadrupedal body and outperforms representative artificial controllers in maze navigation, with its advantage widening as maze complexity increases, while remaining effective across two-, three-, four- and six-legged embodiments. These results identify adaptability as a functional advantage of connectome structure and establish evolved neural wiring as a transferable prior for adaptive embodied control.
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Yu et al. (2026) studied this question.
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