Predicting sensory modulation of precise spike timing for motor control

Animals from flying insects to running humans thrive in uncertain and noisy environments. They smoothly navigate, swiftly track targets and escape predators because their sensorimotor systems are precisely fine-tuned for these tasks. Millisecond-precise spike timing codes, prevalent in both sensory and motor systems, can prompt large changes in muscle forces especially when several muscles coordinate to control a biomechanical action. Such coordinated spike timing changes, modulated by task-relevant sensory encoding over long timescales, can significantly contribute to the effectiveness of motor control. However, how does this modulation play into goal-directed control of motor action? A critical step in determining this is predicting motor spike timing changes from sensory encoding. Some existing algorithms can predict spike timings by training spiking neurons to spike within precise time windows. Yet their applicability is limited to simulated data on feedforward two-layered networks only. Therefore, to predict the motor spike timings in a biologically meaningful way, we need computational frameworks based on physiology and experimental data that combine sensing models with coordinated motor program prediction models. A hawkmoth, with its millisecond-precise motor control, serves as an excellent model organism here because the information required to build its visuomotor models based on a comprehensive motor program is readily available. Here, we propose a model of the hawkmoth visuomotor circuit which sequentially predicts precise timings of coordinated motor spikes from the visual encoding of an oscillating flower’s motion. Our model is based on event-based motion detection, coupled with a compound eye model, and an artificial recurrent neural network (RNN) that predicts the hawkmoth’s comprehensive spike-resolved motor program (precise spike timings of 10 major flight muscles). Besides being trained on the experimental data, our model features a motion detection mechanism inspired by a compound eye as well as signal compression and expansion ratios in hawkmoth’s sensorimotor neural circuits.