Synopsis
Coordinated landing from a jump requires preparation, which must include appropriate positioning and configuration of the landing limbs and body to be successful. While well studied in mammals, our lab has been using the cane toad (Rhinella marinus) as a model for understanding the biomechanics of controlled landing in anurans, animals that use jumping or bounding as their dominant mode of locomotion. In this paper, we report new results from experiments designed to explore how different modes of sensory feedback contribute to previously identified features of coordinated landing in toads. More specifically, animals in which vision, hindlimb proprioception or vestibular feedback were removed, underwent a series of hopping trials while high-speed video was used to record and characterize limb movements and electromyographic activity was recorded from a major elbow extensor (m. anconeus). Results demonstrate that altering any sensory system impacts landing behavior, though loss of vision had the least effect. Blind animals showed significant differences in anconeus EMG timing relative to controls, but forelimb and hindlimb movements as well as the ability to successfully decelerate the body using the forelimbs were not affected. Compromising hindlimb proprioception led to distinctly different forelimb kinematics. Though EMG patterns were disrupted, animals in this condition were also able to decelerate after impact, though with less control, regularly allowing their trunks to make ground contact during landing. Animals with compromised vestibular systems showed the greatest deficits, both in takeoff and landing behavior, which were highly variable and rarely coordinated. Nevertheless, animals in this condition demonstrated EMG patterns and forelimb kinematics similar to those in control animals. The fact that no ablation entirely eliminates all aspects of landing preparation, suggests that its underpinnings are complex and that that there is no single sensory trigger for its initiation.https://ift.tt/2JMpBvm
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