Volker Dürr

Antennal movements and mechanoreception: neurobiology of active tactile sensors

Publisher Summary This chapter focuses on the biology of the antennal tactile sense of insects and crustaceans. It covers the biomechanics, kinematics, and behavioral biology of antennal movements, the peripheral and central neurobiology of antennal mechanoreception, and interdisciplinary aspects of biology and engineering of tactile sensing. The discussion is concentrated on a set of insect model organisms, all of which employ their antennae in active tactile sensing. Work on other species, particularly on decapod crustaceans, is used to complete and contrast the insights from the insect model organisms. The chapter discusses three aspects of the antennal tactile sense that draw on information from various sections and, therefore, require separate treatment. It addresses the behavioral similarities between insect and crustacean antennal tactile sensing, which are particularly remarkable when bearing in mind the morphological differences between these taxa. The chapter also provides a contrast in the categories of passive and active sensing, by relating them to a behavior-based classification of tactile sensing.

The behavioural transition from straight to curve walking: kinetics of leg movement parameters and the initiation of turning.

SUMMARY The control of locomotion requires the ability to adapt movement sequences to the behavioural context of the animal. In hexapod walking, adaptive behavioural transitions require orchestration of at least 18 leg joints and twice as many muscle groups. Although kinematics of locomotion has been studied in several arthropod species and in a range of different behaviours, almost nothing is known about the transition from one behavioural state to another. Implicitly, most studies on context-dependency assume that all parameters that undergo a change during a behavioural transition do so at the same rate. The present study tests this assumption by analysing the sequence of kinematic events during turning of the stick insect Carausius morosus, and by measuring how the time courses of the changing parameters differ between legs. Turning was triggered reliably at a known instant in time by means of the optomotor response to large-field visual motion. Thus, knowing the start point of the transition, the kinematic parameters that initiate turning could be ranked according to their time constants. Kinematics of stick insect walking vary considerably among trials and within trials. As a consequence, the behavioural states of straight walking and curve walking are described by the distributions of 13 kinematic parameters per leg and of orientation angles of head and antennae. The transitions between the behavioural states are then characterised by the fraction of the variance within states by which these distributions differ, and by the rate of change of the corresponding time courses. The antennal optomotor response leads that of the locomotor system. Visually elicited turning is shown to be initiated by stance direction changes of both front legs. The transition from straight to curve walking in stick insects follows different time courses for different legs, with time constants of kinematic parameters ranging from 1.7 s to more than 3 s. Therefore, turning is a behavioural transition that involves a characteristic orchestration of events rather than synchronous parallel actions with a single time constant.

The antennal motor system of the stick insect Carausius morosus: anatomy and antennal movement pattern during walking

Abstract. The stick insect Carausius morosus continuously moves its antennae during locomotion. Active antennal movements may reflect employment of antennae as tactile probes. Therefore, this study treats two basic aspects of the antennal motor system: First, the anatomy of antennal joints, muscles, nerves and motoneurons is described and discussed in comparison with other species. Second, the typical movement pattern of the antennae is analysed, and its spatio-temporal coordination with leg movements described. Each antenna is moved by two single-axis hinge joints. The proximal head-scape joint is controlled by two levator muscles and a three-partite depressor muscle. The distal scape-pedicel joint is controlled by an antagonistic abductor/adductor pair. Three nerves innervate the antennal musculature, containing axons of 14–17 motoneurons, including one common inhibitor. During walking, the pattern of antennal movement is rhythmic and spatio-temporally coupled with leg movements. The antennal abduction/adduction cycle leads the protraction/retraction cycle of the ipsilateral front leg with a stable phase shift. During one abduction/adduction cycle there are typically two levation/depression cycles, however, with less strict temporal coupling than the horizontal component. Predictions of antennal contacts with square obstacles to occur before leg contacts match behavioural performance, indicating a potential role of active antennal movements in obstacle detection.

Insect walking is based on a decentralized architecture revealing a simple and robust controller

Control of walking in rugged terrain requires one to incorporate different issues, such as the mechanical properties of legs and muscles, the neuronal control structures for the single leg, the mechanics and neuronal control structures for the coordination between legs, as well as central decisions that are based on external information and on internal states. Walking in predictable environments and fast running, to a large degree, rely on muscle mechanics. Conversely, slow walking in unpredictable terrain, e.g. climbing in rugged structures, has to rely on neuronal systems that monitor and intelligently react to specific properties of the environment. An arthropod model system that shows the latter abilities is the stick insect, based on which this review will be focused. An insect, when moving its six legs, has to control 18 joints, three per leg, and therefore has to control 18 degrees of freedom (d.f.). As the body position in space is determined by 6 d.f. only, there are 12 d.f. open to be selected. Therefore, a fundamental problem is as to how these extra d.f. are controlled. Based mainly on behavioural experiments and simulation studies, but also including neurophysiological results, the following control structures have been revealed. Legs act as basically independent systems. The quasi-rhythmic movement of the individual leg can be described to result from a structure that exploits mechanical coupling of the legs via the ground and the body. Furthermore, neuronally mediated influences act locally between neighbouring legs, leading to the emergence of insect-type gaits. The underlying controller can be described as a free gait controller. Cooperation of the legs being in stance mode is assumed to be based on mechanical coupling plus local positive feedback controllers. These controllers, acting on individual leg joints, transform a passive displacement of a joint into an active movement, generating synergistic assistance reflexes in all mechanically coupled joints. This architecture is summarized in the form of the artificial neural network, Walknet, that is heavily dependent on sensory feedback at the proprioceptive level. Exteroceptive feedback is exploited for global decisions, such as the walking direction and velocity.

Active tactile exploration for adaptive locomotion in the stick insect

Insects carry a pair of actively movable feelers that supply the animal with a range of multimodal information. The antennae of the stick insect Carausius morosus are straight and of nearly the same length as the legs, making them ideal probes for near-range exploration. Indeed, stick insects, like many other insects, use antennal contact information for the adaptive control of locomotion, for example, in climbing. Moreover, the active exploratory movement pattern of the antennae is context-dependent. The first objective of the present study is to reveal the significance of antennal contact information for the efficient initiation of climbing. This is done by means of kinematic analysis of freely walking animals as they undergo a tactually elicited transition from walking to climbing. The main findings are that fast, tactually elicited re-targeting movements may occur during an ongoing swing movement, and that the height of the last antennal contact prior to leg contact largely predicts the height of the first leg contact. The second objective is to understand the context-dependent adaptation of the antennal movement pattern in response to tactile contact. We show that the cycle frequency of both antennal joints increases after obstacle contact. Furthermore, inter-joint coupling switches distinctly upon tactile contact, revealing a simple mechanism for context-dependent adaptation.

A posture optimization algorithm for model-based motion capture of movement sequences

We have developed and evaluated a new optical motion capture approach that is suitable for a wide range of studies in neuroethology and motor control. Based on the stochastic search algorithm of Simulated Annealing (SA), it utilizes a kinematic body model that includes joint angle constraints to reconstruct posture from an arbitrary number of views. Rather than tracking marker trajectories in time, the algorithm minimizes an error function that compares predicted model projections to the recorded views. Thus, each video-frame is analyzed independently from other frames, enabling the system to recover from incorrectly analyzed postures. The system works with standard computer and video equipment. Its accuracy is evaluated using videos of animated locust leg movements, recorded by two orthogonal views. The resulting joint angle RMS errors range between 0.7 degrees and 4.9 degrees, limited by the pixel resolution of the digital video. 3D-movement reconstruction is possible even from a single view. In a real experimental application, stick insect walking sequences are analyzed with leg joint angle deviations between 0.5 degrees and 3.0 degrees. This robust and accurate performance is reached in spite of marker fusions and occlusions, simply by exploiting the natural constraints imposed by a kinematic chain and a known experimental setup.

Tactile efficiency of insect antennae with two hinge joints

Antennae are the main organs of the arthropod tactile sense. In contrast to other senses that are capable of retrieving spatial information, e.g. vision, spatial sampling of tactile information requires active movement of the sense organ. For a quantitative analysis of basic principles of active tactile sensing, we use a generic model of arbitrary antennae with two hinge joints (revolute joints). This kind of antenna is typical for Orthoptera and Phasmatodea, i.e. insect orders that contain model species for the study of antennal movements, including cricket, locust and stick insect. First, we analyse the significance of morphological properties on workspace and sampling acuity. It is shown how joint axis orientation determines areas out of reach while affecting acuity in the areas within reach. Second, we assume a parametric set of movement strategies, based on empirical data on the stick insect Carausius morosus, and investigate the role of each strategy parameter on tactile sampling performance. A stochastic environment is used to measure sampling density, and a viscous friction model is assumed to introduce energy consumption and, thus, a measure of tactile efficiency. Up to a saturation level, sampling density is proportional to the range or frequency of joint angle modulation. The effect of phase shift is strong if joint angle modulation frequencies are equal, but diminishes for other frequency ratios. Speed of forward progression influences the optimal choice of movement strategy. Finally, for an analysis of environmental effects on tactile performance, we show how efficiency depends on predominant edge direction. For example, with slanted and non-orthogonal joint axis orientations, as present in the stick insect, the optimal sampling strategy is less sensitive to a change from horizontal to vertical edge predominance than with orthogonal and non-slanted joint axes, as present in a cricket.

Neuroethological Concepts and their Transfer to Walking Machines

A systems approach to animal motor behavior reveals concepts that can be useful for the pragmatic design of walking machines. This is because the relation of animal behavior to its underlying nervous control algorithms bears many parallels to the relation of machine function to electronic control. Here, three major neuroethological concepts of motor behavior are described in terms of a conceptual framework based on artificial neural networks (ANN). Central patterns of activity and postural reflexes are both interpreted as a result of feedback loops, with the distinction of loops via an internal model from loops via the physical environment (body, external world). This view allows continuous transitions between predictive (centrally driven) and reactive (reflex driven) motor systems. Motor primitives, behavioral modules that are elicited by distinct commands, are also considered. ANNs capture these three major concepts in terms of a formal description, in which the interactions and mutual interdependences of the various output parameters are comprised by the weight matrix of the net. Based upon behavioral observations of insect walking, we further demonstrate how a decentralized network of separate modules, each one described by an ANN, can account for adaptive behavior. Complex coordination patterns of several manipulators are controlled by imposing simple interaction rules between limbs, and by exploiting the interaction of the body with its physical environment. Finally, we discuss the technical use of leg-like active tactile sensors for obstacle detection, and we show how specific design of such active sensors may increase efficiency of walking on rough terrain. Applied to active sensors, an example of parallel, self-organizing forward models on the basis of extended Kohonen maps is presented to emphasize the potential of adaptive forward models in motor control.

Context-dependent changes in strength and efficacy of leg coordination mechanisms

SUMMARY Appropriate coordination of stepping in adjacent legs is crucial for stable walking. Several leg coordination rules have been derived from behavioural experiments on walking insects, some of which also apply to arthropods with more than six legs and to four-legged walking vertebrates. Three of these rules affect the timing of stance–swing transition [rules 1 to 3 (sensu Cruse)]. They can give rise to normal leg coordination and adaptive responses to disturbances, as shown by kinematic simulations and dynamic hardware tests. In spite of their importance to the study of animal walking, the coupling strength associated with these rules has never been measured experimentally. Generally coupling strength of the underlying mechanisms has been considered constant rather than context-dependent. The present study analyses stepping patterns of the stick insect Carausius morosus during straight and curve walking sequences. To infer strength and efficacy of coupling between pairs of sender and receiver legs, the likelihood of the receiver leg being in swing is determined, given a certain delay relative to the time of a swing–stance (or stance–swing) transition in the sender leg. This is compared to a corresponding measure for independent, hence uncoupled, step sequences. The difference is defined as coupling strength. The ratio of coupling strength and its theoretical maximum is defined as efficacy. Irrespective of the coordination rule, coupling strength between ipsilateral leg pairs is at least twice that of contralateral leg pairs, being strongest between ipsilateral hind and middle legs and weakest between contralateral middle legs. Efficacy is highest for inhibitory rule 1, reaching 84–95% for ipsilateral and 29–65% for contralateral leg pairs. Efficacy of excitatory rules 2 and 3 ranges between 35–56% for ipsilateral and 8–21% for contralateral leg pairs. The behavioural transition from straight to curve walking is associated with context-dependent changes in coupling strength, increasing in both outer leg pairs and decreasing between inner hind and middle leg. Thus, the coordination rules that are thought to underlie many adaptive properties of the walking system, themselves adapt in a context-dependent manner.

Inter-joint coupling and joint angle synergies of human catching movements

A central question in motor control is how the central nervous system (CNS) deals with redundant degrees of freedom (DoFs) inherent in the musculoskeletal system. One way to simplify control of a redundant system is to combine several DoFs into synergies. In reaching movements of the human arm, redundancy occurs at the kinematic level because there is an unlimited number of arm postures for each position of the hand. Redundancy also occurs at the level of muscle forces because each arm posture can be maintained by a set of muscle activation patterns. Both postural and force-related motor synergies may contribute to simplify the control problem. The present study analyzes the kinematic complexity of natural, unrestrained human arm movements, and detects the amount of kinematic synergy in a vast variety of arm postures. We have measured inter-joint coupling of the human arm and shoulder girdle during fast, unrestrained, and untrained catching movements. Participants were asked to catch a ball launched towards them on 16 different trajectories. These had to be reached from two different initial positions. Movement of the right arm was recorded using optical motion capture and was transformed into 10 joint angle time courses, corresponding to 3 DoFs of the shoulder girdle and 7 of the arm. The resulting time series of the arm postures were analyzed by principal components analysis (PCA). We found that the first three principal components (PCs) always captured more than 97% of the variance. Furthermore, subspaces spanned by PC sets associated with different catching positions varied smoothly across the arms workspace. When we pooled complete sets of movements, three PCs, the theoretical minimum for reaching in 3D space, were sufficient to explain 80% of the datas variance. We assumed that the linearly correlated DoFs of each significant PC represent cardinal joint angle synergies, and showed that catching movements towards a multitude of targets in the arms workspace can be generated efficiently by linear combinations of three of such synergies. The contribution of each synergy changed during a single catching movement and often varied systematically with target location. We conclude that unrestrained, one-handed catching movements are dominated by strong kinematic couplings between the joints that reduce the kinematic complexity of the human arm and shoulder girdle to three non-redundant DoFs.