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Animals utilize a number of neuronal systems to produce locomotion. One type of sensory organ that contributes in insects is the campaniform sensillum (CS) that measures the load on their legs. Groups of the receptors are found on high stress regions of the leg exoskeleton and they have significant effects in adapting walking behavior. Recording from these sensors in freely moving animals is limited by technical constraints. To better understand the load feedback signaled by CS to the nervous system, we have constructed a dynamically scaled robotic model of the Carausius morosus stick insect middle leg. The leg steps on a treadmill and supports weight during stance to simulate body weight. Strain gauges were mounted in the same positions and orientations as four key CS groups (Groups 3, 4, 6B, and 6A). Continuous data from the strain gauges were processed through a previously published dynamic computational model of CS discharge. Our experiments suggest that under different stepping conditions (e.g., changing “body” weight, phasic load stimuli, slipping foot), the CS sensory discharge robustly signals increases in force, such as at the beginning of stance, and decreases in force, such as at the end of stance or when the foot slips. Such signals would be crucial for an insect or robot to maintain intra- and inter-leg coordination while walking over extreme terrain.
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This content will become publicly available on June 1, 2026
Force sensing in small animals: recording response properties and modeling of tibial campaniform sensilla in blow flies
Force sensing is advantageous in walking and can signal leg slipping that could destabilize support of body weight, prior to changes in body position. Recordings of strain-detecting campaniform sensilla in blow fly legs showed force encoding in ranges reflecting their minimal body weight but firing was also inhibited by very small transient force decreases. A mathematical model of the receptors reproduced these characteristics and could aid in control of walking machines, independent of size and mass.
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- Award ID(s):
- 2113028
- PAR ID:
- 10637725
- Publisher / Repository:
- Journal of Neurophysiology
- Date Published:
- Journal Name:
- Journal of Neurophysiology
- Volume:
- 133
- Issue:
- 6
- ISSN:
- 0022-3077
- Page Range / eLocation ID:
- 1749 to 1760
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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