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Activation of these specific descending neurons serve to influence the controllers of the body, which have been trained by imitation learning to mimic particular fly behaviors. For example, in our model, antennal grooming is driven through antennal descending neurons (Seeds et al., 2014; Hampel et al., 2015; Hampel et al., 2020). Steering in our model is driven through the neurons DNa01 and DNa02 (Yang et al., 2024), which are implicated in turning. Forward velocity is modeled by activation of oDN1 (Sapkal et al., 2024). Feeding is modeled by activation of proboscis motor neurons, specifically MN9. We note that many DNs have validated, behaviorally meaningful roles, but also that these neurons operate in networks rather than as isolated one-neuron-to-one-behavior buttons. Braun et al. showed that command-like descending signals recruit broader descending populations; there are over 1,000 descending neurons. So the present controller is best thought of as a deliberately low-dimensional readout layer from a much richer neural system.
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