Communication by analogue signals is relatively common in arthropod local networks. In the locust, non-spiking local interneurons play a key role in controlling sets of motor neurons in the generation of local reflex movements of the limbs. Here, our aim was two-fold. Our first aim was to determine the coding properties of a subpopulation of these interneurons by using system identification approaches. To this end, the femoro-tibial chordotonal organ, which monitors the movements of the tibia about the femur, was stimulated with Gaussian white noise and with more natural stimuli corresponding to the movements of the tibia during walking. The results showed that the sample of interneurons analysed displayed a wide, and overlapping, range of response characteristics. The second aim was to develop and test improved data analysis methods for describing neuronal function that are more robust and allow statistical analysis, a need emphasized by the high levels of background neuronal activity usually observed. We found that nonlinear models provided an improved fit in describing the response properties of interneurons that were then classified with statistical clustering methods. We identified four distinct categories of interneuron response that can be further divided into nine groups, with most interneurons being excited during extension movements of the leg, reflecting the outputs of upstream spiking local interneurons.