Central control components of a 'simple' stretch reflex

An information theoretic method to resolve millisecond-scale spike timing precision in a comprehensive motor program

Sensory inputs in nervous systems are often encoded at the millisecond scale in a precise spike timing code. There is now growing evidence in behaviors ranging from slow breathing to rapid flight for the prevalence of precise timing encoding in motor systems. Despite this, we largely do not know at what scale timing matters in these circuits due to the difficulty of recording a complete set of spike-resolved motor signals and assessing spike timing precision for encoding continuous motor signals. We also do not know if the precision scale varies depending on the functional role of different motor units. We introduce a method to estimate spike timing precision in motor circuits using continuous MI estimation at increasing levels of added uniform noise. This method can assess spike timing precision at fine scales for encoding rich motor output variation. We demonstrate the advantages of this approach compared to a previously established discrete information theoretic method of assessing spike timing precision. We use this method to analyze the precision in a nearly complete, spike resolved recording of the 10 primary wing muscles control flight in an agile hawk moth, Manduca sexta. Tethered moths visually tracked a robotic flower producing a range of turning (yaw) torques. We know that all 10 muscles in this motor program encode the majority of information about yaw torque in spike timings, but we do not know whether individual muscles encode motor information at different levels of precision. We demonstrate that the scale of temporal precision in all motor units in this insect flight circuit is at the sub-millisecond or millisecond-scale, with variation in precision scale present between muscle types. This method can be applied broadly to estimate spike timing precision in sensory and motor circuits in both invertebrates and vertebrates.

Mechanosensory pathways of scorpion pecten hair sensillae-Adjustment of body height and pecten position

Scorpions' sensory abilities are intriguing, especially the rather enigmatic ventral comb-like chemo- and mechanosensory organs, the so-called pectines. Attached ventrally to the second mesosomal segment just posterior to the coxae of the fourth walking leg pair, the pectines consist of the lamellae, the fulcra, and a variable number of pecten teeth. The latter contain the bimodal peg sensillae, used for probing the substrate with regard to chemo- and mechanosensory cues simultaneously. In addition, the lamellae, the fulcra and the pecten teeth are equipped with pecten hair sensillae (PHS) to gather mechanosensory information. Previously, we have analyzed the neuronal pathway associated with the peg sensillae unraveling their somatotopic projection pattern in dedicated pecten neuropils. Little is known, however, regarding the projections of PHS within the scorpion nervous system. Behavioral and electrophysiological assays showed involvement of PHS in reflexive responses but how the information is integrated remains unresolved. Here, we unravel the innervation pattern of the mechanosensory pecten hair afferents in Mesobuthus eupeus and Euscorpius italicus. By using immunofluorescent labeling and injection of Neurobiotin tracer, we identify extensive arborizations of afferents, including (i) ventral neuropils, (ii) somatotopically organized multisegmental sensory tracts, (iii) contralateral branches via commissures, and (iv) direct ipsilateral innervation of walking leg neuromeres 3 and 4. Our results suggest that PHS function as sensors to elicit reflexive adjustment of body height and obstacle avoidance, mediating accurate pecten teeth alignment to guarantee functionality of pectines, which are involved in fundamental capacities like mating or navigation.

A leg to stand on: computational models of proprioception

Dexterous motor control requires feedback from proprioceptors, internal mechanosensory neurons that sense the body's position and movement. An outstanding question in neuroscience is how diverse proprioceptive feedback signals contribute to flexible motor control. Genetic tools now enable targeted recording and perturbation of proprioceptive neurons in behaving animals; however, these experiments can be challenging to interpret, due to the tight coupling of proprioception and motor control. Here, we argue that understanding the role of proprioceptive feedback in controlling behavior will be aided by the development of multiscale models of sensorimotor loops. We review current phenomenological and structural models for proprioceptor encoding and discuss how they may be integrated with existing models of posture, movement, and body state estimation.

Drosophila neuroscience: Unravelling the circuits of sensory-motor control in the fly

Effective motor control requires the real-time transmission of information between sensory organs and the motor system. With the powerful techniques that are now available, Drosophila neuroscientists are unravelling the topology of the neural circuits that carry this information in the fly at synaptic resolution.

A size principle for recruitment of Drosophila leg motor neurons

To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. Here, we use in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. We find that leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, we also find that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control.

Body side-specific changes in sensorimotor processing of movement feedback in a walking insect

Feedback from load and movement sensors can modify timing and magnitude of the motor output in the stepping stick insect. One source of feedback is stretch reception by the femoral chordotonal organ (fCO), which encodes such parameters as the femorotibial (FTi) joint angle, the angular velocity, and its acceleration. Stimulation of the fCO causes a postural resistance reflex, during quiescence, and can elicit the opposite, so-called active reaction (AR), which assists ongoing flexion during active movements. In the present study, we investigated the role of fCO feedback for the difference in likelihood of generating ARs on the inside vs. the outside during curve stepping. We analyzed the effects of fCO stimulation on the motor output to the FTi and the neighboring coxa-trochanter and thorax-coxa joints of the middle leg. In inside and outside turns, the probability for ARs increases with increasing starting angle and decreasing stimulus velocity; furthermore, it is independent of the total angular excursion. However, the transition between stance and swing motor activity always occurs after a specific angular excursion, independent of the turning direction. Feedback from the fCO also has an excitatory influence on levator trochanteris motoneurons (MNs) during inside and outside turns, whereas the same feedback affects protractor coxae MNs only during outside steps. Our results suggest joint- and body side-dependent processing of fCO feedback. A shift in gain may be responsible for different AR probabilities between inside and outside turning, whereas the general control mechanism for ARs is unchanged.NEW & NOTEWORTHY We show that parameters of movement feedback from the tibia in an insect during curve walking are processed in a body side-specific manner, and how. From our results it is highly conceivable that the difference in motor response to the feedback supports the body side-specific leg kinematics during turning. Future studies will need to determine the source for the inputs that determine the local changes in sensory-motor processing.

Discrimination of bursts and tonic activity in multifunctional sensorimotor neural network using the extended hill-valley method

Individual neurons can exhibit a wide range of activity, including spontaneous spiking, tonic spiking, bursting, or spike-frequency adaptation, and can also transition between these activity types. Manual identification of these activity patterns can be subjective and inconsistent. The extended hill-valley (EHV) analysis discriminates tonic spiking and bursts in a spike train by detecting fluctuations in a local, history-dependent analysis signal derived from the spike train. Consequently, the EHV method is not susceptible to changes in baseline firing rate and can identify different types of activity patterns. In addition, output from the EHV method can be used to identify more complex activity patterns such as phasotonic bursting, in which a burst is immediately followed by a period of tonic spiking.NEW & NOTEWORTHY Neurons exhibit diverse spiking patterns, but automated activity classification has focused mainly on detecting bursts. The novel extended hill-valley algorithm uses a smoothed, history-dependent signal to discriminate different types of activity, such as bursts and tonic spiking.

A New Perspective on Predictive Motor Signaling

Adaptive behavior relies on complex neural processing in multiple interacting networks of both motor and sensory systems. One such interaction employs intrinsic neuronal signals, so-called 'corollary discharge' or 'efference copy', that may be used to predict the sensory consequences of a specific behavioral action, thereby enabling self-generated (reafferent) sensory information and extrinsic (exafferent) sensory inflow to be dissociated. Here, by using well-established examples, we seek to identify the distinguishing features of corollary discharge and efference copy within the framework of predictive motor-to-sensory system coordination. We then extend the more general concept of predictive signaling by showing how neural replicas of a particular motor command not only inform sensory pathways in order to gate reafferent stimulation, but can also be used to directly coordinate distinct and otherwise independent behaviors to the original motor task. Moreover, this motor-to-motor pairing may additionally extend to a gating of sensory input to either or both of the coupled systems. The employment of predictive internal signaling in such motor systems coupling and remote sensory input control thus adds to our understanding of how an organism's central nervous system is able to coordinate the activity of multiple and generally disparate motor and sensory circuits in the production of effective behavior.

The contribution of small and large sensory afferents to postural control in patients with peripheral neuropathy

Peripheral neuropathy (PN) is a multifarious disorder that is caused by damage to the peripheral nerves. Although the symptoms of PN vary with the etiology, most cases are characterized by impaired tactile and proprioceptive sensation that progresses in a distal to proximal manner. Balance also tends to deteriorate as the disorder becomes more severe, and those afflicted are substantially more likely to fall while walking compared with those who are healthy. Most patients with PN walk more cautiously and with greater stride variability than age-matched controls, but the majority of their falls occur when they must react to a perturbation such as a slippery or uneven surface. The purpose of this study was to first describe the role of somatosensory feedback in the control of posture and then discuss how that relationship is typically affected by the most common types of PN. A comprehensive review of the scientific literature was conducted using MEDLINE, and the relevant information was synthesized. The evidence indicates that the proprioceptive feedback that is conveyed primarily through larger type I afferents is important for postural control. However, the evidence indicates that the tactile feedback communicated through smaller type II afferents is particularly critical to the maintenance of balance. Many forms of PN often lead to chronic tactile desensitization in the soles of the feet and, although the central nervous system seems to adapt to this smaller type II afferent dysfunction by relying on more larger type I afferent reflex loops, the result is still decreased stability. We propose a model that is intended both to help explain the relationship between stability and the smaller type II afferent and the larger type I afferent feedback that may be impaired by PN and to assist in the development of pertinent rehabilitative interventions.

Closed-loop control of trunk posture improves locomotion through the regulation of leg proprioceptive feedback after spinal cord injury

After spinal cord injury (SCI), sensory feedback circuits critically contribute to leg motor execution. Compelled by the importance to engage these circuits during gait rehabilitation, assistive robotics and training protocols have primarily focused on guiding leg movements to reinforce sensory feedback. Despite the importance of trunk postural dynamics on gait and balance, trunk assistance has comparatively received little attention. Typically, trunk movements are either constrained within bodyweight support systems, or manually adjusted by therapists. Here, we show that real-time control of trunk posture re-established dynamic balance amongst bilateral proprioceptive feedback circuits, and thereby restored left-right symmetry, loading and stepping consistency in rats with severe SCI. We developed a robotic system that adjusts mediolateral trunk posture during locomotion. This system uncovered robust relationships between trunk orientation and the modulation of bilateral leg kinematics and muscle activity. Computer simulations suggested that these modulations emerged from corrections in the balance between flexor- and extensor-related proprioceptive feedback. We leveraged this knowledge to engineer control policies that regulate trunk orientation and postural sway in real-time. This dynamical postural interface immediately improved stepping quality in all rats regardless of broad differences in deficits. These results emphasize the importance of trunk regulation to optimize performance during rehabilitation.

Mechanosensation and Adaptive Motor Control in Insects

The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing.

Flexion Reflex Can Interrupt and Reset the Swimming Rhythm

The spinal cord can generate the hip flexor nerve activity underlying leg withdrawal (flexion reflex) and the rhythmic, alternating hip flexor and extensor activities underlying locomotion and scratching, even in the absence of brain inputs and movement-related sensory feedback. It has been hypothesized that a common set of spinal interneurons mediates flexion reflex and the flexion components of locomotion and scratching. Leg cutaneous stimuli that evoke flexion reflex can alter the timing of (i.e., reset) cat walking and turtle scratching rhythms; in addition, reflex responses to leg cutaneous stimuli can be modified during cat and human walking and turtle scratching. Both of these effects depend on the phase (flexion or extension) of the rhythm in which the stimuli occur. However, similar interactions between leg flexion reflex and swimming have not been reported. We show here that a tap to the foot interrupted and reset the rhythm of forward swimming in spinal, immobilized turtles if the tap occurred during the swim hip extensor phase. In addition, the hip flexor nerve response to an electrical foot stimulus was reduced or eliminated during the swim hip extensor phase. These two phase-dependent effects of flexion reflex on the swim rhythm and vice versa together demonstrate that the flexion reflex spinal circuit shares key components with or has strong interactions with the swimming spinal network, as has been shown previously for cat walking and turtle scratching. Therefore, leg flexion reflex circuits likely share key spinal interneurons with locomotion and scratching networks across limbed vertebrates generally.

SIGNIFICANCE STATEMENT

The spinal cord can generate leg withdrawal (flexion reflex), locomotion, and scratching in limbed vertebrates. It has been hypothesized that there is a common set of spinal cord neurons that produce hip flexion during flexion reflex, locomotion, and scratching based on evidence from studies of cat and human walking and turtle scratching. We show here that flexion reflex and swimming also share key spinal cord components based on evidence from turtles. Foot stimulation can reset the timing of the swimming rhythm and the response to each foot stimulation can itself be altered by the swim rhythm. Collectively, these studies suggest that spinal cord neuronal networks underlying flexion reflex, multiple forms of locomotion, and scratching share key components.

Mechanisms Underlying the Neuromodulation of Spinal Circuits for Correcting Gait and Balance Deficits after Spinal Cord Injury

Epidural electrical stimulation of lumbar segments facilitates standing and walking in animal models and humans with spinal cord injury. However, the mechanisms through which this neuromodulation therapy engages spinal circuits remain enigmatic. Using computer simulations and behavioral experiments, we provide evidence that epidural electrical stimulation interacts with muscle spindle feedback circuits to modulate muscle activity during locomotion. Hypothesis-driven strategies emerging from simulations steered the design of stimulation protocols that adjust bilateral hindlimb kinematics throughout gait execution. These stimulation strategies corrected subject-specific gait and balance deficits in rats with incomplete and complete spinal cord injury. The conservation of muscle spindle feedback circuits across mammals suggests that the same mechanisms may facilitate motor control in humans. These results provide a conceptual framework to improve stimulation protocols for clinical applications.

Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited this therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here, we developed novel stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real–time control software that modulate extensor versus flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight–bearing capacities, endurance and skilled locomotion in multiple rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans.

Controlling legs for locomotion-insights from robotics and neurobiology

Walking is the most common terrestrial form of locomotion in animals. Its great versatility and flexibility has led to many attempts at building walking machines with similar capabilities. The control of walking is an active research area both in neurobiology and robotics, with a large and growing body of work. This paper gives an overview of the current knowledge on the control of legged locomotion in animals and machines and attempts to give walking control researchers from biology and robotics an overview of the current knowledge in both fields. We try to summarize the knowledge on the neurobiological basis of walking control in animals, emphasizing common principles seen in different species. In a section on walking robots, we review common approaches to walking controller design with a slight emphasis on biped walking control. We show where parallels between robotic and neurobiological walking controllers exist and how robotics and biology may benefit from each other. Finally, we discuss where research in the two fields diverges and suggest ways to bridge these gaps.

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans

Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous systems show basic similarities. The main similarities are the segmental organization, and the way the function of the segmental units is coordinated. We set out to construct a model that could describe locomotion (walking) in animals with more than 6 legs, as well as in 6-legged animals (insects). To this end, we extended a network model by Daun-Gruhn and Tóth (Journal of Computational Neuroscience, doi: 10.1007/s10827-010-0300-1 , 2011). This model describes inter-segmental coordination of the ipsilateral legs in the stick insect during walking. Including an additional segment (local network) into the original model, we could simulate coordination patterns that occur in animals walking on eight legs (e.g., crayfish). We could improve the model by modifying its original cyclic connection topology. In all model variants, the phase relations between the afferent segmental excitatory sensory signals and the oscillatory activity of the segmental networks played a crucial role. Our results stress the importance of this sensory input on the generation of different stable coordination patterns. The simulations confirmed that using the modified connection topology, the flexibility of the model behaviour increased, meaning that changing a single phase parameter, i.e., gating properties of just one afferent sensory signal was sufficient to reproduce all coordination patterns seen in the experiments.

The effect of sensory feedback on crayfish posture and locomotion: II. Neuromechanical simulation of closing the loop

Neuromechanical simulation was used to determine whether proposed thoracic circuit mechanisms for the control of leg elevation and depression in crayfish could account for the responses of an experimental hybrid neuromechanical preparation when the proprioceptive feedback loop was open and closed. The hybrid neuromechanical preparation consisted of a computational model of the fifth crayfish leg driven in real time by the experimentally recorded activity of the levator and depressor (Lev/Dep) nerves of an in vitro preparation of the crayfish thoracic nerve cord. Up and down movements of the model leg evoked by motor nerve activity released and stretched the model coxobasal chordotonal organ (CBCO); variations in the CBCO length were used to drive identical variations in the length of the live CBCO in the in vitro preparation. CBCO afferent responses provided proprioceptive feedback to affect the thoracic motor output. Experiments performed with this hybrid neuromechanical preparation were simulated with a neuromechanical model in which a computational circuit model represented the relevant thoracic circuitry. Model simulations were able to reproduce the hybrid neuromechanical experimental results to show that proposed circuit mechanisms with sensory feedback could account for resistance reflexes displayed in the quiescent state and for reflex reversal and spontaneous Lev/Dep bursting seen in the active state.

The effect of sensory feedback on crayfish posture and locomotion: I. Experimental analysis of closing the loop

The effect of proprioceptive feedback on the control of posture and locomotion was studied in the crayfish Procambarus clarkii (Girard). Sensory and motor nerves of an isolated crayfish thoracic nerve cord were connected to a computational neuromechanical model of the crayfish thorax and leg. Recorded levator (Lev) and depressor (Dep) nerve activity drove the model Lev and Dep muscles to move the leg up and down. These movements released and stretched a model stretch receptor, the coxobasal chordotonal organ (CBCO). Model CBCO length changes drove identical changes in the real CBCO; CBCO afferent responses completed the feedback loop. In a quiescent preparation, imposed model leg lifts evoked resistance reflexes in the Dep motor neurons that drove the leg back down. A muscarinic agonist, oxotremorine, induced an active state in which spontaneous Lev/Dep burst pairs occurred and an imposed leg lift excited a Lev assistance reflex followed by a Lev/Dep burst pair. When the feedback loop was intact, Lev/Dep burst pairs moved the leg up and down rhythmically at nearly three times the frequency of burst pairs when the feedback loop was open. The increased rate of rhythmic bursting appeared to result from the positive feedback produced by the assistance reflex.

A walking control strategy combining global sensory reflex and leg synchronization

Biped walking can be regarded as a global limit cycle whose stability is difficult to verify by only local sensory feedback. This paper presents a control strategy combining global sensory reflex and leg synchronization. The inverted pendulum angle is utilized as global motion feedback to ensure global stability, and joint synchronization between legs is designed to stabilize bifurcations. The proposed strategy can achieve a stable gait and stabilize bifurcations. The robustness of this approach was evaluated against external disturbances. Walking experiments of a biped actuated by pneumatic muscles were conducted to confirm the validity of the proposed method. Instead of tracking predetermined trajectories, this method uses sensory reflexes to activate motor neurons and coincides with the biological idea wherein inessential degrees-of-freedom are barely controlled rather than strictly controlled.

Reliability of nerve function assessments for people with peripheral neuropathy

Examining degenerative sensory and reflexive activity among people with peripheral neuropathy (PN) is important for clinical examinations and understanding relevant neural impairments. However, other than the test of presynaptic inhibition, the reliability of other related tests is largely unknown. The purpose of this project was to examine the test-retest reliability of lower extremity sensory and reflexive measures in people with PN. Twelve participants (8 women, 4 men, age = 72.5 ± 9.2 years) diagnosed with PN were assessed on two occasions at least 7 d apart. Plantar sensitivity, H-reflex and active and passive ankle proprioception (AAP and PAP) were tested. Paired student's t-test and Intraclass correlation coefficients (ICC) were used for statistical analysis. Significant difference was observed in AAP at 0º position (p = 0.04). No other significant differences were observed. Moderate to high reliability was observed at measures of Plantar sensitivity (0.92), peak to peak H (0.71) and M (0.84) waves, latency between H and M (0.78), H-Index (0.85), AAP (0.62) and PAP index (0.60). Low reliability was observed of other parameters. The measures of Hmax, Mmax, latency, H-Index, plantar sensitivity and AAP & PAP indices of proprioception tests can be measured reliably for further study in this population.

Response differences of intersegmental auditory neurons recorded close to or far away from the presumed spike-generating zone

Intracellular recordings may give valuable information about processing of a neuron and possibly its input from the network. Impalement with an electrode causes injury to the cell and depolarization from intrusion of extracellular fluid. Thus, penetration artefacts may contaminate recordings and conceal or even alter relevant information. These penetration artefacts may have the strongest impact close to the spike-generating zone near the dendrites. Recordings in axonal portions might therefore be less vulnerable while providing insufficient information about the synaptic input. In this study, we present data of five previously identified intersegmental auditory neurons of a bushcricket independently recorded in their dendrites (prothorax) and axon (brain). Generally, responses to acoustic pulses of the same parameter combination were similar within a neuronal class at the two recording sites. However, all neuronal classes showed significantly higher response variability and a tendency for higher spike activity when recorded in the dendrites. Unexpectedly, the combined activity of two neurons (Ascending Neurons 1 and 2) recorded in the brain provides a better fit to song recognition than when recorded in the thorax. Axonal recordings of T-shaped Neuron 1 revealed graded potentials originating in the brain and modulating its output in a potentially behaviourally relevant manner.

Neuropilar projections of the anterior gastric receptor neuron in the stomatogastric ganglion of the Jonah crab, Cancer borealis

Sensory neurons provide important feedback to pattern-generating motor systems. In the crustacean stomatogastric nervous system (STNS), feedback from the anterior gastric receptor (AGR), a muscle receptor neuron, shapes the activity of motor circuits in the stomatogastric ganglion (STG) via polysynaptic pathways involving anterior ganglia. The AGR soma is located in the dorsal ventricular nerve posterior to the STG and it has been thought that its axon passes through the STG without making contacts. Using high-resolution confocal microscopy with dye-filled neurons, we show here that AGR from the crab Cancer borealis also has local projections within the STG and that these projections form candidate contact sites with STG motor neurons or with descending input fibers from other ganglia. We develop and exploit a new masking method that allows us to potentially separate presynaptic and postsynaptic staining of synaptic markers. The AGR processes in the STG show diversity in shape, number of branches and branching structure. The number of AGR projections in the STG ranges from one to three simple to multiply branched processes. The projections come in close contact with gastric motor neurons and descending neurons and may also be electrically coupled to other neurons of the STNS. Thus, in addition to well described long-loop pathways, it is possible that AGR is involved in integration and pattern regulation directly in the STG.

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.

Spinal and pontine relay pathways mediating respiratory rhythm entrainment by limb proprioceptive inputs in the neonatal rat

The coordination of locomotion and respiration is widespread among mammals, although the underlying neural mechanisms are still only partially understood. It was previously found in neonatal rat that cyclic electrical stimulation of spinal cervical and lumbar dorsal roots (DRs) can fully entrain (1:1 coupling) spontaneous respiratory activity expressed by the isolated brainstem/spinal cord. Here, we used a variety of preparations to determine the type of spinal sensory inputs responsible for this respiratory rhythm entrainment, and to establish the extent to which limb movement-activated feedback influences the medullary respiratory networks via direct or relayed ascending pathways. During in vivo overground locomotion, respiratory rhythm slowed and became coupled 1:1 with locomotion. In hindlimb-attached semi-isolated preparations, passive flexion-extension movements applied to a single hindlimb led to entrainment of fictive respiratory rhythmicity recorded in phrenic motoneurons, indicating that the recruitment of limb proprioceptive afferents could participate in the locomotor-respiratory coupling. Furthermore, in correspondence with the regionalization of spinal locomotor rhythm-generating circuitry, the stimulation of DRs at different segmental levels in isolated preparations revealed that cervical and lumbosacral proprioceptive inputs are more effective in this entraining influence than thoracic afferent pathways. Finally, blocking spinal synaptic transmission and using a combination of electrophysiology, calcium imaging and specific brainstem lesioning indicated that the ascending entraining signals from the cervical or lumbar limb afferents are transmitted across first-order synapses, probably monosynaptic, in the spinal cord. They are then conveyed to the brainstem respiratory centers via a brainstem pontine relay located in the parabrachial/Kölliker-Fuse nuclear complex.

Using individual-muscle specific instead of across-muscle mean data halves muscle simulation error

Hill-type parameter values measured in experiments on single muscles show large across-muscle variation. Using individual-muscle specific values instead of the more standard approach of across-muscle means might therefore improve muscle model performance. We show here that using mean values increased simulation normalized RMS error in all tested motor nerve stimulation paradigms in both isotonic and isometric conditions, doubling mean simulation error from 9 to 18 (different at p < 0.0001). These data suggest muscle-specific measurement of Hill-type model parameters is necessary in work requiring highly accurate muscle model construction. Maximum muscle force (F (max)) showed large (fourfold) across-muscle variation. To test the role of F (max) in model performance we compared the errors of models using mean F (max) and muscle-specific values for the other model parameters, and models using muscle-specific F (max) values and mean values for the other model parameters. Using muscle-specific F (max) values did not improve model performance compared to using mean values for all parameters, but using muscle-specific values for all parameters but F (max) did (to an error of 14, different from muscle-specific, mean all parameters, and mean only F (max) errors at p ≤ 0.014). Significantly improving model performance thus required muscle-specific values for at least a subset of parameters other than F (max), and best performance required muscle-specific values for this subset and F (max). Detailed consideration of model performance suggested that remaining model error likely stemmed from activation of both fast and slow motor neurons in our experiments and inadequate specification of model activation dynamics.

Lessons for circuit function from large insects: towards understanding the neural basis of motor flexibility

Motor behaviors result from information processing that occurs in multiple neural networks acting at all levels from the initial selection of the behavior to its final generation. A long-standing research interest is how single neural networks can help generate different motor behaviors, that is, the origin of motor flexibility. Modern experimental techniques allow studying neural network activity during the production of multiple motor behaviors. Recent data provide strong evidence that the neural networks controlling insect legs are individually modified in task-dependent and finely tuned fashions. Understanding the mechanistic basis of these neural network modifications will be of particular interest in the upcoming years.

Control of reflex reversal in stick insect walking: effects of intersegmental signals, changes in direction, and optomotor-induced turning

In many animals, the effects of sensory feedback on motor output change during locomotion. These changes can occur as reflex reversals in which sense organs that activate muscles to counter perturbations in posture control instead reinforce movements in walking. The mechanisms underlying these changes are only partially understood. As such, it is unclear whether reflex reversals are modulated when locomotion is adapted, such as during changes in walking direction or in turning movements. We investigated these questions in the stick insect Carausius morosus, where sensory signals from the femoral chordotonal organ are known to produce resistance reflexes at rest but assistive movements during walking. We studied how intersegmental signals from neighboring legs affect the generation of reflex reversals in a semi-intact preparation that allows free leg movement during walking. We found that reflex reversal was enhanced by stepping activity of the ipsilateral neighboring rostral leg, whereas stepping of contralateral legs had no effect. Furthermore, we found that the occurrence of reflex reversals was task-specific: in the front legs of animals with five legs walking, reflex reversal was generated only during forward and not backward walking. Similarly, during optomotor-induced curved walking, reflex reversal occurred only in the middle leg on the inside of the turn and not in the contralateral leg on the outside of the turn. Thus our results show for the first time that the nervous system modulates reflexes in individual legs in the adaptation of walking to specific tasks.

New moves in motor control

Motor behaviour results from information processing across multiple neural networks acting at all levels from initial selection of the behaviour to its final generation. Understanding how motor behaviour is produced requires identifying the constituent neurons of these networks, their cellular properties, and their pattern of synaptic connectivity. Neural networks have been traditionally studied with neurophysiological and neuroanatomical approaches. These approaches have been highly successful in particularly suitable 'model' preparations, typically ones in which the numbers of neurons in the networks were relatively small, neural network composition was unvarying across individual animals, and the preparations continued to produce fictive motor patterns in vitro. However, analysing networks without these characteristics, and analysing the complete ensemble of networks that cooperatively generate behaviours, is difficult with these approaches. Recently developed molecular and neurogenetic tools provide additional avenues for analysing motor networks by allowing individual or groups of neurons within networks to be manipulated in novel ways and allowing experiments to be performed not only in vitro but also in vivo. We review here some of the new insights into motor network function that these advances have provided and indicate how these advances might bridge gaps in our understanding of motor control. To these ends, we first review motor neural network organisation highlighting cross-phylum principles. We then use prominent examples from the field to show how neurogenetic approaches can complement classical physiological studies, and identify additional areas where these approaches could be advantageously applied.

Dominance of local sensory signals over inter-segmental effects in a motor system: experiments

Legged locomotion requires that information local to one leg, and inter-segmental signals coming from the other legs are processed appropriately to establish a coordinated walking pattern.However, very little is known about the relative importance of local and inter-segmental signals when they converge upon the central pattern generators (CPGs) of different leg joints.We investigated this question on the CPG of the middle leg coxa–trochanter (CTr)-joint of the stick insect which is responsible for lifting and lowering the leg.We used a semi-intact preparation with an intact front leg stepping on a treadmill, and simultaneously stimulated load sensors of the middle leg.We found that middle leg load signals induce bursts in the middle leg depressor motoneurons(MNs). The same local load signals could also elicit rhythmic activity in the CPG of the middle leg CTr-joint when the stimulation of middle leg load sensors coincided with front leg stepping. However, the influence of front leg stepping was generally weak such that front leg stepping alone was only rarely accompanied by switching between middle leg levator and depressor MN activity. We therefore conclude that the impact of the local sensory signals on the levator–depressor motor system is stronger than the inter-segmental influence through front leg stepping.

Good use and misuse of "genetic determinism"

After sequencing the human genome, scientists believed it would be possible to draw up a list of diseases, morphological characteristics and behavioral traits linked to each gene, but the post-genome era has shown that while links between genes and phenotypes, including behavioral phenotypes, do exist, they are more complex than was previously thought. There is no linear connection between genotype and brain and between brain and behavior; consequently, genomic and behavioral levels of organization are not isomorphous. There is no isomorphism because one gene plays many different roles, which means that the integrative processes needed for the development and functioning of an organism inevitably occurs in situations of non-linear multiple causality. Pleiotropy and epistasis, interactions between genes and the environment, alternative splicing and neuronal integration are all crucial mechanisms contributing to the many and varied aspects of brain-related genes.

Octopaminergic modulation of temporal frequency coding in an identified optic flow-processing interneuron

Flying generates predictably different patterns of optic flow compared with other locomotor states. A sensorimotor system tuned to rapid responses and a high bandwidth of optic flow would help the animal to avoid wasting energy through imprecise motor action. However, neural processing that covers a higher input bandwidth itself comes at higher energetic costs which would be a poor investment when the animal was not flying. How does the blowfly adjust the dynamic range of its optic flow-processing neurons to the locomotor state? Octopamine (OA) is a biogenic amine central to the initiation and maintenance of flight in insects. We used an OA agonist chlordimeform (CDM) to simulate the widespread OA release during flight and recorded the effects on the temporal frequency coding of the H2 cell. This cell is a visual interneuron known to be involved in flight stabilization reflexes. The application of CDM resulted in (i) an increase in the cell's spontaneous activity, expanding the inhibitory signaling range (ii) an initial response gain to moving gratings (20-60 ms post-stimulus) that depended on the temporal frequency of the grating and (iii) a reduction in the rate and magnitude of motion adaptation that was also temporal frequency-dependent. To our knowledge, this is the first demonstration that the application of a neuromodulator can induce velocity-dependent alterations in the gain of a wide-field optic flow-processing neuron. The observed changes in the cell's response properties resulted in a 33% increase of the cell's information rate when encoding random changes in temporal frequency of the stimulus. The increased signaling range and more rapid, longer lasting responses employed more spikes to encode each bit, and so consumed a greater amount of energy. It appears that for the fly investing more energy in sensory processing during flight is more efficient than wasting energy on under-performing motor control.

Activity Patterns and Timing of Muscle Activity in the Forward Walking and Backward Walking Stick Insect Carausius morosus

Understanding how animals control locomotion in different behaviors requires understanding both the kinematics of leg movements and the neural activity underlying these movements. Stick insect leg kinematics differ in forward and backward walking. Describing leg muscle activity in these behaviors is a first step toward understanding the neuronal basis for these differences. We report here the phasing of EMG activities and latencies of first spikes relative to precise electrical measurements of middle leg tarsus touchdown and liftoff of three pairs ( protractor/retractor coxae, levator/depressor trochanteris, extensor/flexor tibiae) of stick insect middle leg antagonistic muscles that play central roles in generating leg movements during forward and backward straight walking. Forward walking stance phase muscle (depressor, flexor, and retractor) activities were tightly coupled to touchdown, beginning on average 93 ms prior to and 9 and 35 ms after touchdown, respectively. Forward walking swing phase muscle (levator, extensor, and protractor) activities were less tightly coupled to liftoff, beginning on average 100, 67, and 37 ms before liftoff, respectively. In backward walking the protractor/retractor muscles reversed their phasing compared with forward walking, with the retractor being active during swing and the protractor during stance. Comparison of intact animal and reduced two- and one-middle-leg preparations during forward straight walking showed only small alterations in overall EMG activity but changes in first spike latencies in most muscles. Changing body height, most likely due to changes in leg joint loading, altered the intensity, but not the timing, of depressor muscle activity.

A neuronal substrate for a state-dependent modulation of sensory inputs in the brainstem

Central networks modulate sensory transmission during motor behavior. Sensory inputs may thus have distinct impacts according to the state of activity of the central networks. Using an in-vitro isolated lamprey brainstem preparation, we investigated whether a brainstem locomotor center, the mesencephalic locomotor region (MLR), modulates sensory transmission. The synaptic responses of brainstem reticulospinal (RS) cells to electrical stimulation of the sensory trigeminal nerve were recorded before and after electrical stimulation of the MLR. The RS cell synaptic responses were significantly reduced by MLR stimulation and the reduction of the response increased with the stimulation intensity of the MLR. Bath perfusion of atropine prevented the depression of sensory transmission, indicating that muscarinic receptor activation is involved. Previous studies have shown that, upon stimulation of the MLR, behavioral activity switches from a resting state to an active-locomotor state. Therefore, our results suggest that a state-dependent modulation of sensory transmission to RS cells occurs in the behavioral context of locomotion and that muscarinic inputs from the MLR are involved.

A housefly sensory-motor integration laboratory

Insects have many interesting behaviors that can be observed in an introductory biology laboratory setting. In the present article, we describe several reflexes using the housefly Musca domestica that can be used to introduce students to sensory and motor responses and encourage them to think about the underlying neural circuits and integration of sensory information that mediate the behaviors.

Muscular coactivation (CA) around the knee reduces power production in elderly women

The main objective of this paper was to study the influence of muscular CA around the knee on the rate of force development (RFD) in older women. After personal invitation, 12 older women, participated in the study. Volunteers performed maximal voluntary isometric knee extension and flexion contractions (MVC) where the RFD was determined (considering the first 50, 100 and 200 ms after the force production onset; also, the time necessary to achieve 30% and 50% MVC was considered). Electromyography data from quadriceps and hamstrings were used to determine different CA indexes (CAIs). A correlation test was applied between CAI and RFD; different methods to determine CAI were also compared (Wilcoxon test). The CAI determination methods were not different one from another (p>0.05) and were significantly correlated with RFD (p<0.05) in special, when time to achieve 30% MVC and 50% MVC were considered (|r|=0.89 and r(2)=0.79; |r|=0.93 and r(2)=0.86; p<0.0001). These results clearly state the CA influence over the capacity to produce force in a short period of time in elderly women, what can increase falling risk, since it is essential to recover to gait disturbances and to unbalance.

A simple walking strategy for biped walking based on an intermittent sinusoidal oscillator

This paper presents a control algorithm for biped walking by extension of previous work in the fields of central pattern generator (CPG) and passive walking. The algorithm takes advantage of the passive dynamics of walking, assisting only when necessary with an intermittent sinusoidal oscillator. The parameterized oscillator is used to drive the hip joint; the triggering and ceasing of the oscillator during a walking cycle can be modulated by the sensory feedback. The results from simulation indicate a stable, efficient gait, and robustness against model inaccuracy and environmental variation. We also examine the effects of oscillator parameters and link parameters on the gait, and design a controller to suppress the bifurcation phenomenon based on the error of prior step periods.

Premotor Interneurons in the Local Control of Stepping Motor Output for the Stick Insect Single Middle Leg

In insect walking systems, nonspiking interneurons (NSIs) play an important role in the control of posture and movement. As such NSIs are known to contribute to state-dependent modifications in processing of proprioceptive signals from the legs. For example, NSIs process a flexion of the femur-tibia (FTi) joint signaled by the femoral chordotonal organ (fCO) such that the stance phase motor output is reinforced in the active locomotor system. This phenomenon representing a reflex reversal is the first part of the “active reaction” (AR) and was hypothesized to functionally represent a major control feature by which sensory feedback supports stance generation. As NSIs are known to contribute to the AR, the question arises, whether they serve similar functions during stepping and whether the AR is generally part of the control system for walking. We studied these issues in vivo, in a single leg preparation of Carausius morosus with the leg kinematics being confined to changes in one plane, along the coxa-trochanteral and the FTi-joint. Following kinematic analysis, identified NSIs (E1-E8, I1, I2, and I4) were recorded intracellularly during single leg stepping at different velocities. We detected clear similarities between the activity pattern of NSIs during single leg stepping and their responses to fCO-stimulation during the generation of the AR. This strongly supports the notion that the motor output generated during the AR reflects part of the control regime for stepping. Furthermore, our experiments revealed that alterations in stepping velocity result from modifications in the activity of the premotor NSIs involved in stance phase generation.

Recruitment in a heterogeneous population of motor neurons that innervates the depressor muscle of the crayfish walking leg muscle

According to the size principle the fine control of muscle tension depends on the orderly recruitment of motor neurons from a heterogeneous pool. We took advantage of the small number of excitatory motor neurons (about 12) that innervate the depressor muscle of the crayfish walking leg to determine if the size principle applies to this muscle. We found that in accordance with the size principle, when stimulated by proprioceptive input, neurons with small extracellular spikes were recruited before neurons with medium or large spikes. Because only a small fraction of the motor neurons responded strongly enough to sensory input to be recruited in this way, we extended our analysis to all neurons by characterizing properties that have classically been associated with recruitment order such as speed of axonal conduction and extracellular spike amplitude. Through a combination of physiological and anatomical criteria we were able to identify seven classes of excitatory depressor motor neurons. The majority of these classes responded to proprioceptive input with a resistance reflex, while a few responded with an assistance reflex, and yet others did not respond. Our results are in general agreement with the size principle. However, we found qualitative differences between neuronal classes in terms of synaptic input and neuronal structure that would in theory be unnecessary, according to a strict interpretation of the size principle. We speculate that the qualitative heterogeneity observed may be due to the fact that the depressor is a complex muscle, consisting of two muscle bundles that share a single insertion but have multiple origins.

Individual premotor drive pulses, not time-varying synergies, are the units of adjustment for limb trajectories constructed in spinal cord

Complex actions may arise by combining simple motor primitives. Our studies support individual premotor drive pulses or bursts as execution primitives in spinal cord. Alternatively, the fundamental execution primitives at the segmental level could be time-varying synergies. To distinguish these hypotheses, we examined sensory feedback effects during targeted wiping organized in spinal cord. This behavior comprises three bursts. We tested (1) whether feedback altered the structure of individual premotor drive bursts or primitives, and (2) whether feedback differentially modulated different drive bursts or pulses in the three burst sequence. At least two of the three bursts would need to always be comodulated to support a time-varying synergy. We used selective muscle vibration to control spindle feedback from a single muscle (biceps/iliofibularis). The structures of premotor drive bursts were conserved. However, biceps vibration (1) scaled the amplitudes of two bursts coactivated during the initial phase of wiping independently of one another without altering their phase, and (2) independently phase regulated the third burst but preserved its amplitude. Thus, all three bursts were regulated separately. Durations were unaffected. The independent effects depended on (1) time of vibration during wiping, (2) frequency of vibration, and (3) limb configuration. Because each of the three bursts was independently modulated, these data strongly support execution using individual premotor bursts rather than time-varying synergies at the spinal level of motor organization. Our data show that both sensory feedback and central systems of the spinal cord act in concert to adjust the individual premotor bursts in support of the straight and unimodal wiping trajectory.

Information Rate and Spike-Timing Precision of Proprioceptive Afferents

Proprioception in the first two joints of crustacean limbs is mediated by chordotonal organs that utilize spike-mediated information coding and transmission and by nonspiking proprioceptive afferents that use graded transmission at information rates in excess of 2,500 bits/s. Chordotonal organs operate in parallel with the graded receptors, but the information rates of the spiking chordotonal afferents have not been previously determined. Lower-bound estimates of chordotonal afferent information rates were calculated using stimulus reconstruction, which assumes linear encoding of the stimulus. The information rate was also directly estimated from the spike train entropy, which makes no a priori assumptions with respect to the coding scheme used by the system. Lower-bound information rate estimates ranged from 43 to 69 bits/s, whereas the direct estimates ranged from 24 to 278 bits/s. Comparison of both estimates derived from the same data set indicates that a linear decoder could recover an average of 59% of the information from the spike train. Afferent spike timing was found to be extremely precise, with spikes evoked with an average timing jitter of 0.55 ms. Information rate was correlated with the mean jitter and the noise entropy of the spike train could be predicted from the mean firing rate and mean jitter. Direct stimulation of single afferents by current injection into the soma revealed that the average timing jitter was <0.1 ms, indicating that intrinsic membrane properties, spike generation, and mechanotransduction mechanisms are the major sources of timing jitter in this system.

Organizing network action for locomotion: insights from studying insect walking

The operational basis for the generation of a functional motor output during walking is formed by the interaction between central pattern generating networks, local feedback from sensory neurons about movements and forces generated in the locomotor organs and coordinating signals from neighboring segments or appendages. This review primarily addresses the current knowledge about network organization underlying the control of an insect walking leg and recent advances in understanding the ways by which modifications in the motor output for walking are generated. Here we focus especially on modifications of the walking motor pattern that are associated with changing walking speed and walking direction. We will place the current knowledge and new results into the broad context gained from other locomotor behaviors and organisms.

Muscle proprioceptive feedback and spinal networks

This review revolves primarily around segmental feedback systems established by muscle spindle and Golgi tendon organ afferents, as well as spinal recurrent inhibition via Renshaw cells. These networks are considered as to their potential contributions to the following functions: (i) generation of anti-gravity thrust during quiet upright stance and the stance phase of locomotion; (ii) timing of locomotor phases; (iii) linearization and correction for muscle nonlinearities; (iv) compensation for muscle lever-arm variations; (v) stabilization of inherently unstable systems; (vi) compensation for muscle fatigue; (vii) synergy formation; (viii) selection of appropriate responses to perturbations; (ix) correction for intersegmental interaction forces; (x) sensory-motor transformations; (xi) plasticity and motor learning. The scope will at times extend beyond the narrow confines of spinal circuits in order to integrate them into wider contexts and concepts.

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.

Invertebrate preparations and their contribution to neurobiology in the second half of the 20th century

This review summarized the contribution to neurobiology achieved through the use of invertebrate preparations in the second half of the 20th century. This fascinating period was preceded by pioneers who explored a wide variety of invertebrate phyla and developed various preparations appropriate for electrophysiological studies. Their work advanced general knowledge about neuronal properties (dendritic, somatic, and axonal excitability; pre- and postsynaptic mechanisms). The study of invertebrates made it possible to identify cell bodies in different ganglia, and monitor their operation in the course of behavior. In the 1970s, the details of central neural circuits in worms, molluscs, insects, and crustaceans were characterized for the first time and well before equivalent findings were made in vertebrate preparations. The concept and nature of a central pattern generator (CPG) have been studied in detail, and the stomatogastric nervous system (STNS) is a fine example, having led to many major developments since it was first examined. The final part of the review is a discussion of recent neuroethological studies that have addressed simple cognitive functions and confirmed the utility of invertebrate models. After presenting our invertebrate "mice," the worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, our conclusion, based on arguments very different from those used fifty years ago, is that invertebrate models are still essential for acquiring insight into the complexity of the brain.