In legged animals integration of information from various proprioceptors in and on the appendages by local premotor networks in the central nervous system is crucial for controlling motor output. To ensure posture maintenance and precise active movements, information about limb loading and movement is required. In insects, various groups of campaniform sensilla (CS) measure forces and loads acting in different directions on the leg, and the femoral chordotonal organ (fCO) provides information about movement of the femur-tibia (FTi) joint. In this study, we used extra- and intracellular recordings of extensor tibiae (ExtTi) and retractor coxae (RetCx) motor neurons (MNs) and identified local premotor nonspiking interneurons (NSIs), and mechanical stimulation of the fCO and tibial or trochanterofemoral CS (tiCS, tr/fCS), to investigate the premotor network architecture underlying multimodal proprioceptive integration. We found that load feedback from tiCS altered the strength of movement-elicited resistance reflexes and determined the specificity of ExtTi and RetCx MN responses to various load and movement stimuli. These responses were mediated by a common population of identified NSIs into which synaptic inputs from the fCO, tiCS, and tr/fCS are distributed, and whose effects onto ExtTi MNs can be antagonistic for both stimulus modalities. Multimodal sensory signal interaction was found at the level of single NSIs and MNs. The results provide evidence that load and movement feedback are integrated in a multimodal, distributed local premotor network consisting of antagonistic elements controlling movements of the FTi joint, thus substantially extending current knowledge on how legged motor systems achieve fine-tuned motor control.

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Nervous systems face a torrent of sensory inputs, including proprioceptive feedback. Signal integration depends on spatially and temporally coinciding signals. It is unclear how relative time delays affect multimodal signal integration from spatially distant sense organs. We measured transmission times and latencies along all processing stages of sensorimotor pathways in the stick insect leg muscle control system using intra- and extracellular recordings. Transmission times of signals from load-sensing tibial and trochanterofemoral campaniform sensilla (tiCS, tr/fCS) to the premotor network were longer than from the movement-sensing femoral chordotonal organ (fCO). We characterized connectivity patterns from tiCS, tr/fCS, and fCO afferents to identified premotor nonspiking interneurons (NSIs) and motor neurons (MNs) by distinguishing short- and long-latency responses to sensory stimuli. Functional NSI connectivity depended on sensory context. The timeline of concurrent tiCS and fCO signals had an early phase of movement signal influences and delayed load influences. Temporal differences persisted into MN activity and muscle force development. We demonstrate a temporal difference in the processing of two distinct sensory modalities generated by the sensorimotor network and affecting motor output. The reported temporal differences in sensory processing and signal integration improve our understanding of sensory network computation and function in motor control.

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Producing context-specific motor acts requires sensorimotor neural networks to integrate multiple sensory modalities. Some of this integration occurs via presynaptic interactions between proprioceptive afferent neurons themselves, other by afferents of different modalities targeting appropriate motor neurons (MNs). How the interneuronal network typically interposed between sensory afferents and MNs contributes to this integration, particularly at single-neuron resolution, is much less understood. In stick insects, this network contains nonspiking interneurons (NSIs) converging onto the posture-controlling slow extensor tibiae motor neuron (SETi). We analyzed how load altered movement signal processing by tracing the interaction of movement (femoral chordotonal organ, fCO) and load (tibial campaniform sensilla, tiCS) signals from the afferents through the NSI network to the motor output. On the afferent level, load reduced movement signal gain by presynaptic inhibition; tiCS stimulation elicited primary afferent depolarization and reduced fCO afferent action potential amplitude. In the NSI network, graded responses to movement and load inputs summed nonlinearly and increased the gain of NSIs opposing movement-induced reflexes. The gain of SETi and muscle movement reflex responses consequently decreased. Gain modulation was movement parameter-specific and required presynaptic inhibition; pharmacologically blocking presynaptic inhibition abolished load-dependent tuning of SETi responses. These data describe sensorimotor gain control at the sensory, premotor, and motor levels. Presynaptic inhibition-mediated nonlinear integration allowed the NSI network to respond to movement sensory input in a context (load)-dependent manner. These findings show how gain changes can allow premotor networks to integrate multiple sensory modalities and thus generate context-appropriate motor activity.