PUB - Publikationen an der Universität Bielefeld

Targeted reaching movements and spatial coordination of footfall patterns are prime examples of spatial coordination of limbs in insects. To explain this, both physiological and computational studies have suggested the use of movement primitives or the existence of an internal body representation, much like they are assumed to occur in vertebrates. Since insects lack a dedicated posture-sensing organ or vestibular system, it is hypothesized that they derive high-level postural information from low-level proprioceptive cues, integrated across their limbs. The present study tests the extent to which a multi-layer spiking neural network can extract high-level information about limb movement and whole-body posture from information provided by distributed local proprioceptors. In a preceding part of the study, we introduced the phasic-tonic encoding of joint angles by strictly local proprioceptive hair field afferents, as well as high-accuracy encoding of joint angles and angular velocities in first-order interneurons. Here, we extend this model by second-order interneurons that use coincidence detection from two or three leg-local inputs to encode movement primitives of a single leg. Using experimental data on whole-body kinematics of unrestrained walking and climbing stick insects, we show that these movement primitives can be used to signal particular step cycle phases, but also step cycle transitions such as leg lift-off. Additionally, third-order interneurons are introduced to indicate climbing behaviour, for example by encoding the body pitch angle from 6x3 local leg joints. All encoding properties are validated against annotated experimental data, allowing for relevance rating of particular leg types and/or leg joint actions for all measures encoded. Our results demonstrate that simple combinations of two or three position/velocity inputs from disjunct hair field arrays are sufficient to encode high-order movement information about step cycle phases. The resulting movement primitive encoding may converge to represent particular locomotor states and whole-body posture.