Ansgar Büschges

Pattern generation for stick insect walking movements : multisensory control of a locomotor program

8. Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 8.1. Distinction between central, peripheral and coordinating influences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 8.2. Generation of reflex reversal by a distributed network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 8.3. Decisions in modular systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

Assessing sensory function in locomotor systems using neuro-mechanical simulations

Computer simulations are being used increasingly to gain an understanding of the complex interactions between the neuronal, sensory, muscular and mechanical components of locomotor systems. Recent neuro-mechanical simulations of walking in humans, cats and insects, and of swimming in lampreys, have provided new information on the functional role of specific groups of sensory receptors in regulating locomotion. As we discuss in this review, these studies also make it clear that a full understanding of the neural and mechanical mechanisms that underlie locomotion can be achieved only by using simulations in parallel with physiological investigations. The widespread implementation of this approach would be enhanced by the development of freely available and easy-to-use software tools.

Sensory pathways and their modulation in the control of locomotion

Recent experiments have extended our understanding of how sensory information in premotor networks controlling motor output is processed during locomotion, and at what level the efficacy of specific sensory-motor pathways is determined. Phasic presynaptic inhibition of sensory transmission combined with postsynaptic alterations of excitatory and inhibitory synaptic transmission from interneurons of the premotor networks contribute to the modulation of reflex pathways and to the generation of reflex reversal. These mechanisms play an important role in adapting the operation of central networks to external demands and thus help optimize sensory-motor integration.

Sensory Feedback Induced by Front-Leg Stepping Entrains the Activity of Central Pattern Generators in Caudal Segments of the Stick Insect Walking System

Legged locomotion results from a combination of central pattern generating network (CPG) activity and intralimb and interlimb sensory feedback. Data on the neural basis of interlimb coordination are very limited. We investigated here the influence of stepping in one leg on the activities of neighboring-leg thorax–coxa (TC) joint CPGs in the stick insect (Carausius morosus). We used a new approach combining single-leg stepping with pharmacological activation of segmental CPGs, sensory stimulation, and additional stepping legs. Stepping of a single front leg could activate the ipsilateral mesothoracic TC CPG. Activation of the metathoracic TC CPG required that both ipsilateral front and middle legs were present and that one of these legs was stepping. Unlike the situation in real walking, ipsilateral mesothoracic and metathoracic TC CPGs activated by front-leg stepping fired in phase with the front-leg stepping. Local (intralimb) sensory feedback from load sensors could override this intersegmental influence of front-leg stepping, shifting retractor motoneuron activity relative to the front-leg step cycle and thereby uncoupling them from front-leg stepping. These data suggest that front-leg stepping in isolation would result in in-phase activity of all ipsilateral legs, and functional stepping gaits (in which the three ipsilateral legs do not step in synchrony) emerge because of local load sensory feedback overriding this in-phase influence.

Adaptive motor behavior in insects.

As insects move through tortuous, unpredictable terrain, their neural system allows them to exhibit striking adaptability and researchers must use every technique at their disposal to unravel the underlying mechanisms. Descending commands from brain centers that process tremendous amounts of information from head sensors work together with local motor control altering their operation to deal with barriers or move toward important targets. By analyzing movements in detail with high-speed video, recording from identified neurons in thoracic ganglia and examining activity in different brain regions, we are beginning to understand how these remarkable animals navigate their environment. Coupled with new and exciting neurogenetic tools, the near future promises an exciting time for studying the neural basis of insect movement.

Segment specificity of load signal processing depends on walking direction in the stick insect leg muscle control system.

In terrestrial locomotion, sensory feedback from load sensors is important for altering ongoing motor output on a step-by-step basis. We investigated the influence of load signals from the leg on motoneuron pools of the thorax-coxa (ThC) joint in the stick insect walking system. Load sensors were stimulated during rhythmic, alternating activity in protractor coxae (ProCx) and retractor coxae (RetCx) motoneuron pools. Alternating activity in the segment of interest was induced by mechanical stimulation of the animal or pharmacological activation of the isolated thoracic ganglia. Load signals from the legs altered the timing of ThC motoneuron activity by resetting and entraining the activity of the central rhythm generating network of the ThC joint. In the front and middle legs, load signals induced or promoted RetCx activity and decreased or terminated ProCx activity. In the hindleg, reverse transitions were elicited, with increasing load terminating RetCx and initiating ProCx activity. Studies in semi-intact walking animals showed that the effect of load on the ThC-joint motoneurons depended on walking direction, with increased load promoting the functional stance phase motoneuron pool (in forward walking, RetCx activity; in backward walking, ProCx activity). Thus, we show that modifications of sensory feedback in a locomotor system are related to walking direction. In a final set of ablation experiments, we show that the load influence is mediated by the three groups of trochanteral campaniform sensilla.

Identified nonspiking interneurons in leg reflexes and during walking in the stick insect

In the stick insect Carausius morosus identified nonspiking interneurons (type E4) were investigated in the mesothoracic ganglion during intraand intersegmental reflexes and during searching and walking.In the standing and in the actively moving animal interneurons of type E4 drive the excitatory extensor tibiae motoneurons, up to four excitatory protractor coxae motoneurons, and the common inhibitor 1 motoneuron (Figs. 1–4).In the standing animal a depolarization of this type of interneuron is induced by tactile stimuli to the tarsi of the ipsilateral front, middle and hind legs (Fig. 5). This response precedes and accompanies the observed activation of the affected middle leg motoneurons. The same is true when compensatory leg placement reflexes are elicited by tactile stimuli given to the tarsi of the legs (Fig. 6).During forward walking the membrane potential of interneurons of type E4 is strongly modulated in the step-cycle (Figs.8–10). The peak depolarization occurs at the transition from stance to swing. The oscillations in membrane potential are correlated with the activity profile of the extensor motoneurons and the common inhibitor 1 (Fig. 9).The described properties of interneuron type E4 in the actively behaving animal show that these interneurons are involved in the organization and coordination of the motor output of the proximal leg joints during reflex movements and during walking.

Inter-leg coordination in the control of walking speed in Drosophila

SUMMARY Legged locomotion is the most common behavior of terrestrial animals and it is assumed to have become highly optimized during evolution. Quadrupeds, for instance, use distinct gaits that are optimal with regard to metabolic cost and have characteristic kinematic features and patterns of inter-leg coordination. In insects, the situation is not as clear. In general, insects are able to alter inter-leg coordination systematically with locomotion speed, producing a continuum of movement patterns. This notion, however, is based on the study of several insect species, which differ greatly in size and mass. Each of these species tends to walk at a rather narrow range of speeds. We have addressed these issues by examining four strains of Drosophila, which are similar in size and mass, but tend to walk at different speed ranges. Our data suggest that Drosophila controls its walking speed almost exclusively via step frequency. At high walking speeds, we invariably found tripod coordination patterns, the quality of which increased with speed as indicated by a simple measure of tripod coordination strength (TCS). At low speeds, we also observed tetrapod coordination and wave gait-like walking patterns. These findings not only suggest a systematic speed dependence of inter-leg movement patterns but also imply that inter-leg coordination is flexible. This was further supported by amputation experiments in which we examined walking behavior in animals after the removal of a hindleg. These animals show immediate adaptations in body posture, leg kinematics and inter-leg coordination, thereby maintaining their ability to walk.

Neural control of unloaded leg posture and of leg swing in stick insect, cockroach, and mouse differs from that in larger animals.

Stick insect (Carausius morosus) leg muscles contract and relax slowly. Control of stick insect leg posture and movement could therefore differ from that in animals with faster muscles. Consistent with this possibility, stick insect legs maintained constant posture without leg motor nerve activity when the animals were rotated in air. That unloaded leg posture was an intrinsic property of the legs was confirmed by showing that isolated legs had constant, gravity-independent postures. Muscle ablation experiments, experiments showing that leg muscle passive forces were large compared with gravitational forces, and experiments showing that, at the rest postures, agonist and antagonist muscles generated equal forces indicated that these postures depended in part on leg muscles. Leg muscle recordings showed that stick insect swing motor neurons fired throughout the entirety of swing. To test whether these results were specific to stick insect, we repeated some of these experiments in cockroach (Periplaneta americana) and mouse. Isolated cockroach legs also had gravity-independent rest positions and mouse swing motor neurons also fired throughout the entirety of swing. These data differ from those in human and horse but not cat. These size-dependent variations in whether legs have constant, gravity-independent postures, in whether swing motor neurons fire throughout the entirety of swing, and calculations of how quickly passive muscle force would slow limb movement as limb size varies suggest that these differences may be caused by scaling. Limb size may thus be as great a determinant as phylogenetic position of unloaded limb motor control strategy.

Mechanosensory Feedback in Walking: From Joint Control to Locomotor Patterns

Abstract The generation of a functional motor output for walking is the result of the activity of central pattern generating networks, local feedback from sensory neurons about movements and forces generated in the locomotor organs and through interaction with coordinating signals from neighbouring segments or appendages. This chapter addresses the current knowledge about the role and processing of mechanosensory feedback for walking in insects. Special focus will be given to (i) the mechanosensory signals that are utilized for the generation and control of walking, and the state-dependent modification in their processing, (ii) the organization of neural networks controlling single-leg stepping, (iii) the role of mechanosensory signals in intersegmental coordination and, finally, (iv) modifications in the walking motor output that are associated with changing walking speed and walking direction. We will place the current knowledge and new results into the broader context of motor pattern generation for other locomotor behaviours and in other organisms.