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Abstract Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the ‘lower level’ ventral nerve cord (VNC) and the ‘higher level’ head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as ‘positive feedback’ may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the ‘reflex reversal’ of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect ( Carausius morosus ) femur-tibia (FTi) and coxa-trochanter joint control networks ‘in-the-loop’ with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce ‘sideways stepping’. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network’s flexion position and velocity afferents generated a reflex reversal in the robot limb’s FTi joint. We also explored the intact network’s ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control.
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This content will become publicly available on December 1, 2026
Rhythm generation, robustness, and control in stick insect locomotion: modeling and analysis
Abstract Stick insect stepping patterns have been studied for insights about locomotor rhythm generation and control, because the underlying neural system is relatively accessible experimentally and produces a variety of rhythmic outputs. Harnessing the experimental identification of effective interactions among neuronal units involved in stick insect stepping pattern generation, previous studies proposed computational models simulating aspects of stick insect locomotor activity. While these models generate diverse stepping patterns and transitions between them, there has not been an in-depth analysis of the mechanisms underlying their dynamics. In this study, we focus on modeling rhythm generation by the neurons associated with the protraction-retraction, levation-depression, and extension-flexion antagonistic muscle pairs of the mesothoracic (middle) leg of stick insects. Our model features a reduced central pattern generator (CPG) circuit for each joint and includes synaptic interactions among the CPGs; we also consider extensions such as the inclusion of motoneuron pools controlled by the CPG components. The resulting network is described by an 18-dimensional system of ordinary differential equations. We use fast-slow decomposition, projection into interacting phase planes, and a heavy reliance on input-dependent nullclines to analyze this model. Specifically, we identify and eludicate dynamic mechanisms capable of generating a stepping rhythm, with a sequence of biologically constrained phase relationships, in a three-joint stick insect limb model. Furthermore, we explain the robustness to parameter changes and tunability of these patterns. In particular, the model allows us to identify possible mechanisms by which neuromodulatory and top-down effects could tune stepping pattern output frequency.
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- Award ID(s):
- 2037828
- PAR ID:
- 10696721
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- Journal of Computational Neuroscience
- Volume:
- 53
- Issue:
- 4
- ISSN:
- 0929-5313
- Page Range / eLocation ID:
- 521 to 549
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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