Force dynamics and synergist muscle activation in stick insects: the effects of using joint torques as mechanical stimuli

Abstract

Many sensory systems are tuned to specific parameters of behaviors and have effects that are task-specific. We have studied how force feedback contributes to activation of synergist muscles in serially homologous legs of stick insects. Forces were applied using conventional half-sine or ramp and hold functions. We also utilized waveforms of joint torques calculated from experiments in freely walking animals. In all legs, forces applied to either the tarsus (foot) or proximal leg segment (trochanter) activated synergist muscles that generate substrate grip and support, but coupling of the depressor muscle to tarsal forces was weak in the front legs. Activation of trochanteral receptors using ramp and hold functions generated positive feedback to the depressor muscle in all legs when animals were induced to seek substrate grip. However, discharges of the synergist flexor muscle showed adaptation at moderate force levels. In contrast, application of forces using torque waveforms, which do not have a static hold phase, produced sustained discharges in muscle synergies with little adaptation. Firing frequencies reflected the magnitude of ground reaction forces, were graded to changes in force amplitude, and could also be modulated by transient force perturbations added to the waveforms. Comparison of synergist activation by torques and ramp and hold functions revealed a strong influence of force dynamics (dF/d t). These studies support the idea that force receptors can act to tune muscle synergies synchronously to the range of force magnitudes and dynamics that occur in each leg according to their specific use in behavior. NEW & NOTEWORTHY The effects of force receptors (campaniform sensilla) on leg muscles and synergies were characterized in stick insects using both ramp and hold functions and waveforms of joint torques calculated by inverse dynamics. Motor responses were sustained and showed reduced adaptation to the more "natural" and nonlinear torque stimuli. Calculation of the first derivative (dF/d t) of the torque waveforms demonstrated that this difference was correlated with the dynamic sensitivities of the system.

Location and arrangement of campaniform sensilla in Drosophila melanogaster

“…This extension is still in line with the previous literature, but allows for the naming to serve as more precise map of CS. This is necessary given the leg‐specific sensitivity and functional roles of individual CS and fields of CS along an insect leg (Zill et al, 2018).…”

“…The three pairs of insect legs (pro‐, meso‐, and metathoracic) differ both morphologically and functionally (Mahfooz et al, 2007; Seeds et al, 2014; Zumstein, 2004); the same task (e.g., forward propulsion during walking) in different legs can, therefore, cause different profiles of cuticular strains. Understanding which CS are stimulated by which cuticular forces thus requires detailed and comprehensive knowledge of their locations, orientations, and anatomy (Zill, Dallmann, Büschges, Chaudhry, & Schmitz, 2018).…”

“…Understanding which CS are stimulated by which cuticular forces thus requires detailed and comprehensive knowledge of their locations, orientations, and anatomy (Zill, Dallmann, Büschges, Chaudhry, & Schmitz, 2018).…”

Measuring strain in the exoskeleton of spiders—virtues and caveats

“…Avoidance of anteriad force components ( x ) in the local metatarsus-fixed system requires an adaptation of leg posture which is controlled at the coxa-trochanter joint. In consequence, high torques at the coxa-trochanter joint are expected with respect to an axis parallel to the major hinge joint axes (Dallmann et al 2016 ; Zill et al 2018 ).…”

Extending the Functional Subnetwork Approach to a Generalized Linear Integrate-and-Fire Neuron Model

“…Additionally, spiking neurons and synapses may be beneficial because even a simple model like that used in this work can produce a wide variety of behaviors and responses (Mihalaş and Niebur, 2009). For example, setting m > 0 can produce spike frequency adaptation and phasic spiking, which are known to be critical for filtering sensory feedback in locomotory systems (Mamiya et al, 2018;Zill et al, 2018). Such rate-sensitive responses can be produced by small networks of non-spiking neurons and synapses , but force the modeler to use more neurons than may be necessary.…”