Intersegmental and local interneurons in the metathorax of the stick insect Carausius morosus that monitor middle leg position

Presynaptic inhibition selectively suppresses leg proprioception in behaving Drosophila

Controlling arms and legs requires feedback from proprioceptive sensory neurons that detect joint position and movement. Proprioceptive feedback must be tuned for different behavioral contexts, but the underlying circuit mechanisms remain poorly understood. Using calcium imaging in behaving Drosophila, we find that the axons of position-encoding leg proprioceptors are active across behaviors, whereas the axons of movement-encoding leg proprioceptors are suppressed during walking and grooming. Using connectomics, we identify a specific class of interneurons that provide GABAergic presynaptic inhibition to the axons of movement-encoding proprioceptors. The predominant synaptic inputs to these interneurons are descending neurons, suggesting they are driven by predictions of leg movement originating in the brain. Calcium imaging from both the interneurons and their descending inputs confirmed that their activity is correlated with self-generated but not passive leg movements. Overall, our findings elucidate a neural circuit for suppressing specific proprioceptive feedback signals during self-generated movements.

A spinal synergy of excitatory and inhibitory neurons coordinates ipsilateral body movements

Innate and goal-directed movements require a high-degree of trunk and appendicular muscle coordination to preserve body stability while ensuring the correct execution of the motor action. The spinal neural circuits underlying motor execution and postural stability are finely modulated by propriospinal, sensory and descending feedback, yet how distinct spinal neuron populations cooperate to control body stability and limb coordination remains unclear. Here, we identified a spinal microcircuit composed of V2 lineage-derived excitatory (V2a) and inhibitory (V2b) neurons that together coordinate ipsilateral body movements during locomotion. Inactivation of the entire V2 neuron lineage does not impair intralimb coordination but destabilizes body balance and ipsilateral limb coupling, causing mice to adopt a compensatory festinating gait and be unable to execute skilled locomotor tasks. Taken together our data suggest that during locomotion the excitatory V2a and inhibitory V2b neurons act antagonistically to control intralimb coordination, and synergistically to coordinate forelimb and hindlimb movements. Thus, we suggest a new circuit architecture, by which neurons with distinct neurotransmitter identities employ a dual-mode of operation, exerting either synergistic or opposing functions to control different facets of the same motor behavior.

The Role of Muscle Spindle Feedback in the Guidance of Hindlimb Movement by the Ipsilateral Forelimb during Locomotion in Mice

Safe and efficient locomotion relies on placing the foot on a reliable surface at the end of each leg swing movement. Visual information has been shown to be important for determining the location of foot placement in humans during walking when precision is required. Yet in quadrupedal animals where the hindlimbs are outside of the visual field, such as in mice, the mechanisms by which precise foot placement is achieved remain unclear. Here we show that the placement of the hindlimb paw is determined by the position of the forelimb paw during normal locomotion and in the presence of perturbations. When a perturbation elicits a stumbling corrective reaction, we found that the forelimb paw shifts posteriorly relative to body at the end of stance, and this spatial shift is echoed in hindlimb paw placement at the end of the swing movement. Using a mutant mouse line in which muscle spindle feedback is selectively removed, we show that this posterior shift of paw placement is dependent on muscle spindle feedback in the hindlimb but not in the forelimb. These findings uncover a neuronal mechanism that is independent of vision to ensure safe locomotion during perturbation. This mechanism adds to our general knowledge of how the nervous system controls targeted limb movements and could inform the development of autonomous walking machines.

Transfer of Spatial Contact Information Among Limbs and the Notion of Peripersonal Space in Insects

Internal representation of far-range space in insects is well established, as it is necessary for navigation behavior. Although it is likely that insects also have an internal representation of near-range space, the behavioral evidence for the latter is much less evident. Here, we estimate the size and shape of the spatial equivalent of a near-range representation that is constituted by somatosensory sampling events. To do so, we use a large set of experimental whole-body motion capture data on unrestrained walking, climbing and searching behavior in stick insects of the species Carausius morosus to delineate ‘action volumes’ and ‘contact volumes’ for both antennae and all six legs. As these volumes are derived from recorded sampling events, they comprise a volume equivalent to a representation of coinciding somatosensory and motor activity. Accordingly, we define this volume as the peripersonal space of an insect. It is of immediate behavioral relevance, because it comprises all potential external object locations within the action range of the body. In a next step, we introduce the notion of an affordance space as that part of peripersonal space within which contact-induced spatial estimates lie within the action ranges of more than one limb. Because the action volumes of limbs overlap in this affordance space, spatial information from one limb can be used to control the movement of another limb. Thus, it gives rise to an affordance as known for contact-induced reaching movements and spatial coordination of footfall patterns in stick insects. Finally, we probe the computational properties of the experimentally derived affordance space for pairs of neighboring legs. This is done by use of artificial neural networks that map the posture of one leg into a target posture of another leg with identical foot position.

A load-based mechanism for inter-leg coordination in insects

Animals rely on an adaptive coordination of legs during walking. However, which specific mechanisms underlie coordination during natural locomotion remains largely unknown. One hypothesis is that legs can be coordinated mechanically based on a transfer of body load from one leg to another. To test this hypothesis, we simultaneously recorded leg kinematics, ground reaction forces and muscle activity in freely walking stick insects (Carausius morosus). Based on torque calculations, we show that load sensors (campaniform sensilla) at the proximal leg joints are well suited to encode the unloading of the leg in individual steps. The unloading coincides with a switch from stance to swing muscle activity, consistent with a load reflex promoting the stance-to-swing transition. Moreover, a mechanical simulation reveals that the unloading can be ascribed to the loading of a specific neighbouring leg, making it exploitable for inter-leg coordination. We propose that mechanically mediated load-based coordination is used across insects analogously to mammals.

Six-legged walking in insects: how CPGs, peripheral feedback, and descending signals generate coordinated and adaptive motor rhythms

Walking is a rhythmic locomotor behavior of legged animals, and its underlying mechanisms have been the subject of neurobiological research for more than 100 years. In this article, we review relevant historical aspects and contemporary studies in this field of research with a particular focus on the role of central pattern generating networks (CPGs) and their contribution to the generation of six-legged walking in insects. Aspects of importance are the generation of single-leg stepping, the generation of interleg coordination, and how descending signals influence walking. We first review how CPGs interact with sensory signals from the leg in the generation of leg stepping. Next, we summarize how these interactions are modified in the generation of motor flexibility for forward and backward walking, curve walking, and speed changes. We then review the present state of knowledge with regard to the role of CPGs in intersegmental coordination and how CPGs might be involved in mediating descending influences from the brain for the initiation, maintenance, modification, and cessation of the motor output for walking. Throughout, we aim to specifically address gaps in knowledge, and we describe potential future avenues and approaches, conceptual and methodological, with the latter emphasizing in particular options arising from the advent of neurogenetic approaches to this field of research and its combination with traditional approaches.

Differential control of temporal and spatial aspects of cockroach leg coordination

Ensembles of neuronal networks and sensory pathways participate in controlling the kinematic and dynamic parameters of animal movement necessary to achieve motor coordination. Determining the relative contribution of proprioceptive feedback is essential for understanding how animals sustain stable, coordinated locomotion in complex natural environments. Here, we focus on the role of chordotonal organs (COs), proprioceptors found in insect legs, in the spatial and temporal regulation of walking. We compare gait parameters of intact cockroaches (Periplaneta americana) and sensory-impaired ones, injected with pymetrozine, a chemical previously shown to abolish CO function in locusts. We verify that afferent CO activity in pymetrozine-treated cockroaches is inhibited, and analyze the effect of this sensory deprivation on inter-leg coordination. We find significant changes in tarsi placement and leg path trajectories after pymetrozine treatment. Leg touchdown accuracy, measured from relative tarsi positions of adjacent legs, is reduced in treated animals. Interestingly, despite poorer spatial coordination in both stance and swing, temporal properties of the gait remain largely the same as in the intact preparations, apart from changes in ipsilateral phase differences between front and middle legs. These findings provide insights into the role of COs in insect gait control and establish pymetrozine as a useful tool for further studies of insect locomotion.

Spatial coordination of foot contacts in unrestrained climbing insects

Animals that live in a spatially complex environment such as the canopy of a tree, constantly need to find reliable foothold in three-dimensional (3D) space. In multi-legged animals, spatial coordination among legs is thought to improve efficiency of finding foothold by avoiding searching-movements in trailing legs. In stick insects, a "targeting mechanism" has been described that guides foot-placement of hind and middle legs according to the position of their leading ipsilateral leg. So far, this mechanism was shown for standing and tethered walking animals on horizontal surfaces. Here, we investigate the efficiency of this mechanism in spatial limb coordination of unrestrained climbing animals. For this, we recorded whole-body kinematics of freely climbing stick insects and analyzed foot placement in 3D space. We found that touch-down positions of adjacent legs were highly correlated in all three spatial dimensions, revealing 3D coordinate transfer among legs. Furthermore, targeting precision depended on the position of the leading leg. A second objective was to test the importance of sensory information transfer between legs. For this, we ablated a proprioceptive hair field signaling the levation of the leg. After ablation, the operated leg swung higher and performed unexpected searching-movements. Furthermore, targeting of the ipsilateral trailing leg was less precise in antero-posterior and in dorso-ventral directions. Our results reveal that the targeting mechanism is used by unrestrained climbing stick insects in 3D space and that information from the trochanteral hair field is used in ipsilateral spatial coordination among legs.

Walknet, a bio-inspired controller for hexapod walking

Walknet comprises an artificial neural network that allows for the simulation of a considerable amount of behavioral data obtained from walking and standing stick insects. It has been tested by kinematic and dynamic simulations as well as on a number of six-legged robots. Over the years, various different expansions of this network have been provided leading to different versions of Walknet. This review summarizes the most important biological findings described by Walknet and how they can be simulated. Walknet shows how a number of properties observed in insects may emerge from a decentralized architecture. Examples are the continuum of so-called "gaits," coordination of up to 18 leg joints during stance when walking forward or backward over uneven surfaces and negotiation of curves, dealing with leg loss, as well as being able following motion trajectories without explicit precalculation. The different Walknet versions are compared to other approaches describing insect-inspired hexapod walking. Finally, we briefly address the ability of this decentralized reactive controller to form the basis for the simulation of higher-level cognitive faculties exceeding the capabilities of insects.

Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster

Coordinated walking in vertebrates and multi-legged invertebrates [corrected] such as Drosophila melanogaster requires a complex neural network coupled to sensory feedback. An understanding of this network will benefit from systems such as Drosophila that have the ability to genetically manipulate neural activities. However, the fly's small size makes it challenging to analyze walking in this system. In order to overcome this limitation, we developed an optical method coupled with high-speed imaging that allows the tracking and quantification of gait parameters in freely walking flies with high temporal and spatial resolution. Using this method, we present a comprehensive description of many locomotion parameters, such as gait, tarsal positioning, and intersegmental and left-right coordination for wild type fruit flies. Surprisingly, we find that inactivation of sensory neurons in the fly's legs, to block proprioceptive feedback, led to deficient step precision, but interleg coordination and the ability to execute a tripod gait were unaffected.DOI:http://dx.doi.org/10.7554/eLife.00231.001.

Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster

Coordinated walking in vertebrates and multi-legged invertebrates such as Drosophila melanogaster requires a complex neural network coupled to sensory feedback. An understanding of this network will benefit from systems such as Drosophila that have the ability to genetically manipulate neural activities. However, the fly's small size makes it challenging to analyze walking in this system. In order to overcome this limitation, we developed an optical method coupled with high-speed imaging that allows the tracking and quantification of gait parameters in freely walking flies with high temporal and spatial resolution. Using this method, we present a comprehensive description of many locomotion parameters, such as gait, tarsal positioning, and intersegmental and left-right coordination for wild type fruit flies. Surprisingly, we find that inactivation of sensory neurons in the fly's legs, to block proprioceptive feedback, led to deficient step precision, but interleg coordination and the ability to execute a tripod gait were unaffected.

DOI:http://dx.doi.org/10.7554/eLife.00231.001

Most animals need to be able to move to survive. Animals without limbs, such as snakes, move by generating by wave-like contractions along their bodies, whereas limbed animals, such as vertebrates and arthropods, walk by coordinating the movements of multi-jointed arms and legs. Locomotion in limbed animals involves bending each joint within each arm or leg in a coordinated manner, while also ensuring that the movements of all the limbs are coordinated with each other. In bipeds such as humans, for example, it is critical that one leg is in the stance phase when the other leg is in the swing phase. The rules that govern the coordination of limbs also depend on the gait, so the rules for walking are not the same as the rules for running.

The nervous systems of bipeds and other animals that walk solve these problems by using complex neural circuits that coordinate the firing of the relevant motor neurons. Two general mechanisms are used to coordinate the firing of motor neurons. In one mechanism, local interneurons within the central nervous system coordinate motor neuron activities: in vertebrates these interneurons are found in the spinal cord. A second mechanism, termed proprioception, relies on sensory neurons that report the load and joint angles from the arms and legs back to the central nervous system, and thereby influence the firing of the motor neurons. Remarkably, both of these mechanisms, and also the types of neurons that comprise motor neuron circuits, are conserved from arthropods to vertebrates.

Mendes et al. describe a new approach that can be used to analyze how the fruit fly, D. melanogaster, walks on surfaces. They use a combination of an optical touch sensor and high-speed video imaging to follow the body of the fly as it walks, and also to record when and where it places each of its six feet on the surface as it moves. Then, using a software package called FlyWalker, they are able to extract a large of number of parameters that can be used to describe locomotion in adult fruit flies with high temporal and spatial resolution. Many of these parameters have never been measured or studied before.

Mendes et al. show that fruit flies do not display the abrupt transitions in gait that are typically observed in vertebrates. However, they do modify their neural circuits depending on their speed: indeed it appears that flies use subtly different neural circuitry for walking at slow, medium and fast speeds. Moreover, when genetic methods are used to block sensory feedback, the fly is still able to walk, albeit with reduced coordination and precision. Further, the data suggest that proprioception is less important when flies walk faster compared to when they walk more slowly. The next step in this research will be to combine this new method for analyzing locomotion in flies with the wide range of genetic tools that are available for the study of Drosophila: this will allow researchers to explore in greater detail the components of the motor neuron circuitry and their role in coordinated walking.

DOI:http://dx.doi.org/10.7554/eLife.00231.002

Segment-specific and state-dependent targeting accuracy of the stick insect

In its natural habitat, Carausius morosus climbs on the branches of bushes and trees. Previous work suggested that stick insects perform targeting movements with their hind legs to find support more easily. It has been assumed that the animals use position information from the anterior legs to control the touchdown position of the ipsilateral posterior legs. Here we address the questions if not only the hind but also the middle leg performs targeting, and if targeting is still present in a walking animal when influences of mechanical coupling through the ground are removed. If this were the case, it would emphasize the role of underlying neuronal mechanisms. We studied whether targeting occurred in both legs, when the rostral neighboring leg, i.e. either middle- or front leg, was placed at defined positions relative to the body, and analyzed targeting precision for dependency on the targeted position. Under these conditions, the touchdown positions of the hind legs show correlation to the position of the middle leg parallel and perpendicular to the body axis while only weak correlation exists between the middle and front legs, and only in parallel to the body axis. In continuously walking tethered animals targeting accuracy of hind and middle legs parallel to the body axis was barely different. However, targeting became significantly more accurate perpendicular to the body axis. Our results suggest that a neural mechanism exists for controlling the touchdown position of the posterior leg but that the strength of this mechanism is segment-specific and dependent on the behavioral context in which it is used.

Quadrupedal gaits in hexapod animals - inter-leg coordination in free-walking adult stick insects

The analysis of inter-leg coordination in insect walking is generally a study of six-legged locomotion. For decades, the stick insect Carausius morosus has been instrumental for unravelling the rules and mechanisms that control leg coordination in hexapeds. We analysed inter-leg coordination in C. morosus that freely walked on straight paths on plane surfaces with different slopes. Consecutive 1.7 s sections were assigned inter-leg coordination patterns (which we call gaits) based on footfall patterns. Regular gaits, i.e. wave, tetrapod or tripod gaits, occurred in different proportions depending on surface slopes. Tetrapod gaits were observed most frequently, wave gaits only occurred on 90 deg inclining slopes and tripod gaits occurred most often on 15 deg declining slopes, i.e. in 40% of the sections. Depending on the slope, 36-66% of the sections were assigned irregular gaits. Irregular gaits were mostly due to multiple stepping by the front legs, which is perhaps probing behaviour, not phase coupled to the middle legs' cycles. In irregular gaits, middle leg and hindleg coordination was regular, related to quadrupedal walk and wave gaits. Apparently, front legs uncouple from and couple to the walking system without compromising middle leg and hindleg coordination. In front leg amputees, the remaining legs were strictly coordinated. In hindleg and middle leg amputees, the front legs continued multiple stepping. The coordination of middle leg amputees was maladapted, with front legs and hindlegs performing multiple steps or ipsilateral legs being in simultaneous swing. Thus, afferent information from middle legs might be necessary for a regular hindleg stepping pattern.

Walking on smooth and rough ground: activity and timing of the claw retractor muscle in the beetle Pachnoda marginata peregrina (Coleoptera, Scarabaeidae)

The activity pattern of the claw retractor muscle of Pachnoda marginata peregrina beetles was examined in this study. We found this muscle to be located in the tibia, without a femoral part, as is the case in other insects. Electromyograms (EMGs) of the muscle revealed a rather similar activity pattern during beetle locomotion on rough and smooth substrates. We recorded units with small and large amplitude, with the smaller one being active during almost the entire stance phase, the larger one roughly in the first half of stance. Small but significant differences were found in the precise onset and end of activity. Both small and large units began their activity earlier on the rough surface. While there was no difference at the end of activity in the small unit between both surfaces, the large unit ended its activity significantly earlier on the rough substrate. The spike frequencies on both surfaces were also significantly different for both small and large units. The small unit showed a higher spike frequency on the smooth surface, while the large unit had a higher spike frequency on the rough surface. From our experiments, we conclude that the muscle is controlled by the same basic activity pattern on different surfaces, with some adjustments due to sensory feedback. The adjustments cause differences in onset and end of activity, as well as in spike frequency of the involved muscle units.

From neuron to behavior: dynamic equation-based prediction of biological processes in motor control

This article presents the use of continuous dynamic models in the form of differential equations to describe and predict temporal changes in biological processes and discusses several of its important advantages over discontinuous bistable ones, exemplified on the stick insect walking system. In this system, coordinated locomotion is produced by concerted joint dynamics and interactions on different dynamical scales, which is therefore difficult to understand. Modeling using differential equations possesses, in general, the potential for the inclusion of biological detail, the suitability for simulation, and most importantly, parameter manipulation to make predictions about the system behavior. We will show in this review article how, in case of the stick insect walking system, continuous dynamical system models can help to understand coordinated locomotion.

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et al. (Arthropod Struct Dev 33:287-300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.

What does body configuration in microgravity tell us about the contribution of intra- and extrapersonal frames of reference for motor control?

The authors report that the reorganization of body configuration during weightlessness is based on an intrapersonal frame of reference such as the configuration of the support surface and the position of the body's center of gravity. These results stress the importance of “knowledge” of the state of internal geometric structures, which cannot be directly signalled by specific receptors responsible for direct dialogue with the physical external world.

Reciprocal and coactivation commands are not sufficient to describe muscle activation patterns

Recent results have shown that the relative activation of muscles is different for isometric contractions and for movements. These results exclude an explanation of muscle activation patterns by a combination ofreciprocal and coactivation commands. These results also indicate that joint stiffness is not uniquely determined and that it may be different for isometric contractions and movements.

Frames of reference interact and are task-dependent

The problem for the CNS in any particular movement task is to coordinate the various frames of reference appropriate to the task. Control variables are determined by this coordination. The coordination problem varies greatly from task to task, and so no single set of control variables is likely to account for a broad range of movement tasks.

The λ model for motor control: More than meets the eye

Understanding of the λ model has greatly increased in recent years as evidenced by most of the commentaries. Some commentators underscored the potential of the model to integrate aspects of different sensorimotor systems in the production of movement. Other commentators focused on not-yet-fully-developed parts of the model. A few persisted in misunderstanding some of its basic concepts, and on these grounds they reject it. In responding to commentaries we continue to elaborate on some fundamental points of the model, especially control variables, the idea of movement production by shifting the positional frame of reference and the hypothesis of biomechanical correspondence in motor control. We also continue to develop our ideas on the intrinsic generation of the frame of reference associated with external space and utilized for the control of arm movement and locomotion. The dynamic principles underlying the model are discussed in light of the dynamical systems approach.

Grip force adjustments during rapid hand movements suggest that detailed movement kinematics are predicted

The λ model suggests that detailed kinematics arise from changes in control variables and need not be explicitly planned. However, we have shown that when moving a grasped object, grip force is precisely modulated in phase with acceleration-dependent inertial load. This suggests that the motor system can predict detailed kinematics. This prediction may be based on a forward model of the dynamics of the loaded limb.

Let us accept a “controlled trade-off” model of motor control

The trade-off between force and length of muscle as adjusted by neural signals is a critical fact in the dynamics of motor control. Whether we call it “length-tension effect,” “feedback-like,” “invariant condition,” or “spring-like” is unimportant. We must not let semantics or details of representation obscure the basic physics of effects introduced by this trade-off in muscle.

Equilibrium-point control? Yes! Deterministic mechanisms of control? No!

The equilibrium-point hypothesis (the λ-model) is superior to all other models of single-joint control and provides deep insights into the mechanisms of control of multi-joint movements. Attempts at associating control variables with neurophysiological variables look confusing rather than promising. Probabilistic mechanisms may play an important role in movement generation in redundant systems.

The unobservability of central commands: Why testing hypotheses is so difficult

The experiments Feldman and Levin suggest do not definitively test their proposed solution to the problem of selecting muscle activations. Their test of the movement directions that elicit EMG activity can be interpreted without regard to the form of the central commands, and their fast elbow flexion test is based on a forward computation that obscures the insensitivity of the predicted trajectory to the details of the putative commands.

Biological variability and control of movements via δλ

Three issues related to Feldman and Levin's treatment of biological variability are discussed. We question the usefulness of the indirect component of δλ. We suggest that trade-offs between speed and accuracy in aimed movements support identification of δλ, rather than λ, as a control variable. We take issue with the authors' proposal for resolving redundancy in multi-joint movements, given recent data.

A few reasons why psychologlsts can adhere to Feldman and Levin's model

We emphasize the relevance to cognitive psychology of Feldman and Levin's theoretical position. Traditional views of motor control have failed to clearly separate “production control” at the level of motor command, based on task-independent CV (control variables), from intentional “product control” based on task-dependent parameters. Because F&L's approach concentrates on the first process (trajectory formation), it can distinguish the product control stage.

Levers to generate movement

The following questions are discussed: (1) Who determines the nature of “control variables”? (2) Is the “positional monopoly” healthy? (3) Does a descending command alter reflex threshold alone without eoncomitantly altering stiffness? (4) How does the CNS deal with history-dependent effects? (5) Should we abandon the idea that the CNS controls classical Newtonian variables such as muscle length?

Kinematic invariances and body schema

Generalizing the notion that muscles are positional frames of reference, a high-dimensional muscle space is defined for multi-muscle systems with an embedded low-dimensional motor manifold of functional articulators. A central representation of such a manifold is proposed as computational body schema. The example of the jaw-tongue system is presented, discussing the relation of functional articulators with kinematic invariances and control problems.

Tendon elasticity and positional control

The spring-like behaviour of a joint following a sudden change of torque is partly a result of the elastic properties of tendons. A large fall in a muscle with a long tendon may be accompanied by tendon recoil causing joint movements as large as 20°.

Command invariants and the frame of reference for human movement

We describe a solution to the redundancy problem related to that proposed in Feldman & Levin's target article. We suggest that the system may use a fixed mapping between commands organized at the level of degrees of freedom and commands to individual muscles. This proposal eliminates the need to maintain an explicit representation of musculoskeletalgeometry in planning movements.

Frameworks on shifting sands

Feldman and Levin present a model for movement control in which the system is said to seek equilibrium points, active movement being produced by shifting frames of reference in space. It is argued that whatever merit this model might have is limited to an understanding of “the how” and not “the why” we move. In this way the authors seem to be forced into a dualistic position leaving the upper level of the proposed control hierarchy “floating.”

Conservative or nonconservative control schemes

The conservative strategy proposed by the authors suggests a solution of the degrees-of-freedom problem of the controller. However, several simple motor control tasks cannot be explained by this strategy. A nonconservative strategy, in which more parameters of the control signal vary, can account for these simple motor tasks. However, the simplicity that distinguishes the proposed model from many others is lost.

The origin and use of positional frames of reference in motor control

A hypothesis about sensorimotor integration (the λ model) is described and applied to movement control and kinesthesia. The central idea is that the nervous system organizes positional frames of reference for the sensorimotor apparatus and produces active movements by shifting the frames in terms of spatial coordinates. Kinematic and electromyographic patterns are not programmed, but emerge from the dynamic interaction among the system s components, including external forces within the designated frame of reference. Motoneuronal threshold properties and proprioceptive inputs to motoneurons may be cardinal components of the physiological mechanism that produces positional frames of reference. The hypothesis that intentional movements are produced by shifting the frame of reference is extended to multi-muscle and multi-degrees-of-freedom systems with a solution of the redundancy problem that allows the control of a joint alone or in combination with other joints to produce any desired limb configuration and movement trajectory. The model also implies that for each motor behavior, the nervous system uses a strategy that minimizes the number of changeable control variables and keeps the parameters of these changes invariant. Examples are provided of simulated kinematic and electromyographic signals from single- and multi-joint arm movements produced by suggested patterns of control variables. Empirical support is provided and additional tests of the model are suggested. The model is contrasted with others based on the ideas of programming of motoneuronal activity, muscle forces, stiffness, or movement kinematics.

Origins of origins of motor control

Examination of infant spontaneous and goal-directed arm movements supports Feldman and Levin's hypothesis of a functional hierarchy. Early infant movements are dominated by biomechanical and dynamic factors without external frames of reference. Development involves not only learning to generate these frames of reference, but also protecting the higher-level goal of the movement from internal and external perturbations.

Spatial frames for motor control would be commensurate with spatial frames for vision and proprioception, but what about control of energy flows?

The model identifies a spatial coordinate frame within which the sensorimotor apparatus produces movement. Its spatial nature simplifies its coupling with spatial reference frames used concurrently by vision and proprioception. While the positional reference frame addresses the performance of spatial tasks, it seems to have little to say about movements involving energy expenditure as the principle component of the task.

Interneurons as backseat drivers and the elusive control variable

It is proposed here that the spinal network of proprioceptive feedback from length and force receptors constitutes the mechanism underlying the coordination of activation thresholds for muscles acting about the same and neighboring joints. For the most part, these circuits come between motoneurons and supraspinal signals, invalidating the idea that the activation thresholds constitute control variables for the motor system.

Two joints are more than twice one joint

An alternative multi-joint extension to the lambda model is proposed. According to this extension, the activity of a muscle depends not only on the difference between lambda and length of that muscle, but also on the difference between lambda and length of other muscles. This 2-D extension can describe more neurophysiological experiments than the extension proposed in the target article.

Control parameters, equilibria, and coordination dynamics

Important similarities exist between the dynamical concepts implicit in Feldman & Levin's extended λ model and those basic to a dynamical systems approach. We argue that careful application of the key concepts of control and order parameters, equilibria, and stability, can relate known facts of neuromuscular processes to the observables of functional, task-specific behavior.

Shifting frames of reference but the same old point of view

Models of central control variables (CVs) that are expressed in positional reference frames and rely on proprioception as the dominant specifier of muscle activation patterns have not yet been shown to be adequate for the description of fast, voluntary movement, even of single joints. An alternative model with illustrative data is proposed.

Inverse kinematic problem: Solutions by pseudoinversion, inversion and no-inversion

Kinematic properties of reaching movements reflect constraints imposed on the joint angles. Contemporary models present solutions to the redundancy problem by a pseudoinverse procedure (Whitney 1969) or without any inversion (Berkenblit et al. 1986). Feldman & Levin suggest a procedure based on a regular inversion. These procedures are considered as an outcome of a more general approach.

Natural unconstrained movements obey rules different from constrained elementary movements

The concept of a conservative control strategy minimizing the number of degrees of freedom used is criticised with reference to 3-D simple reaching and grasping experiments. The vector error in a redundant system would not be the prime controlled variable, but rather the posture for reaching, as exemplified by nearly straight displacements in joint space as opposed to curved ones in task space.

Is λ an appropriate control variable for locomotion?

The lambda model predicts that the command received by each motor nucleus during locomotion is specific for the joint at which its muscle acts and is independent of external conditions. However, investigation of the commands received by motor nuclei during fictive locomotion and of the sensitivity of these commands to feedback from the limb during locomotion indicates that neither condition is satisfied.

How far should we extend the equilibrium point (lambda) hypothesis?

A key feature of the lambda model is the hypothesis of a local spring-like muscle-reflex system defined by a central control variable that has units of position. This is intriguing, especially for a study of postural stability in large-scale systems, but it has limited direct application to skilled everyday movements. If movement is considered as a goal-directed, neuro-optimization problem, however, theavailabilityof lambda-like peripheral models (vs. conventional musculoskeletal models) deserves exploration.

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.

Perturbation of leg protraction causes context-dependent modulation of inter-leg coordination, but not of avoidance reflexes

All animals capable of legged locomotion execute fast, adaptive compensatory movements in response to perturbation of a step cycle. In terms of motor control, such adaptive behaviour typically involves changes in the kinematics of the perturbed limb as well as changes in coordination between legs. Moreover, the unpredictable variety of real life situations implies that compensatory responses should be sensitive to the behavioural context of the animal. We have investigated the extent to which the compensatory response of a walking stick insect (Carausius morosus) adapts in parallel to strong context-dependent adaptation of step kinematics and inter-leg coordination. The behavioural contexts we chose were straight walking and visually induced curve walking, for both of which the steady state limb kinematics and inter-leg coupling strengths were known. In case of curve walking, we further distinguished contexts according to whether the inner or the outer leg was perturbed. The three contexts differed strongly with respect to the set of joint actions before perturbation. Upon mechanical perturbation of front leg protraction, we studied context-dependent differences in a local avoidance reflex of the perturbed leg, as well as in coordination mechanisms that couple the step cycles of the perturbed leg to its unperturbed neighbours. In all three walking contexts, obstacle contact caused an avoidance movement of the front leg that deviated from the unperturbed swing trajectory. Swing duration was increased while step distance was decreased; however, both effects vanished in the subsequent unperturbed step. The prevailing immediate reaction of the three leg joints were retraction of the coxa (>76%), levation of the femur (>80%), and flexion of the tibia (>80%), regardless of the behavioural context and, therefore, joint action prior to perturbation. Moreover, activation of each one of these joint actions was shown to be independent of the other two. Thus, local avoidance reflexes are not modulated by the descending visual information that causes transition from straight to curve walking, but are composed of context-independent joint actions. Perturbation of the front leg also caused significant shifts of the touch-down position of the perturbed leg and of its unperturbed neighbours. If the inner front leg was perturbed, this shift could persist until the subsequent step. Perturbation affected both the spatial location and the timing of touch-down and lift-off transitions in unperturbed neighbouring legs. These effects on inter-leg coordination were context-dependent. For example, time delay to lift-off of the contralateral neighbour was shortened in inner and straight walking legs, but not in outer legs. Finally, a targeting mechanism that determines foot placement in stick insects was shown to be affected by perturbation in a context-dependent manner. We conclude that the immediate compensatory response of the perturbed leg is not adapted to the behavioural context in spite of strongly differing step kinematics, whereas the compensatory effect on inter-limb coupling is context-dependent.

Intersegmental transfer of sensory signals in the stick insect leg muscle control system

Intersegmental coordination during locomotion in legged animals arises from mechanical couplings and the exchange of neuronal information between legs. Here, the information flow from a single leg sense organ of the stick insect Cuniculina impigra onto motoneurons and interneurons of other legs was investigated. The femoral chordotonal organ (fCO) of the right middle leg, which measures posture and movement of the femur-tibia joint, was stimulated, and the responses of the tibial motoneuron pools of the other legs were recorded. In resting animals, fCO signals did not affect motoneuronal activity in neighboring legs. When the locomotor system was activated and antagonistic motoneurons were bursting in alternation, fCO stimuli facilitated transitions from flexor to extensor activity and vice versa in the contralateral leg. Following pharmacological treatment with picrotoxin, a blocker of GABA-ergic inhibition, the tibial motoneurons of all legs showed specific responses to signals from the middle leg fCO. For the contralateral middle leg we show that fCO signals encoding velocity and position of the tibia were processed by those identified local premotor nonspiking interneurons known to contribute to posture and movement control during standing and voluntary leg movements. Interneurons received both excitatory and inhibitory inputs, so that the response of some interneurons supported the motoneuronal output, while others opposed it. Our results demonstrate that sensory information from the fCO specifically affects the motoneuronal activity of other legs and that the layer of premotor nonspiking interneurons is a site of interaction between local proprioceptive sensory signals and proprioceptive signals from other legs.