Tarsal intersegmental reflex responses in the locust hind leg

Locomotion is vital for vertebrates and invertebrates to survive. However, the mechanisms for locomotion are partially unknown. Central Pattern Generators and reflex systems have been shown to be the basis of most movements performed by arthropods. Much has been investigated lately on Central Pattern Generators, but little work has been done in reflex systems. Locomotion and motor output in feet (or tarsus in arthropods) has also been disregarded in research. Despite that feet are responsible for stability and agility in most animals, research on feet movements is scarce.In this thesis the tarsal intersegmental reflex of the locust hind leg is investigated. The tarsal reflex consists of a response in the tarsus when there is a change in the femoro-tibial joint. The main objective of the thesis is to describe the system and to develop mathematical and experimental methods to study, model and analyse it. Through a set of experiments is shown that as the knee joint is extended, the tarsus is depressed, and as the knee joint flexes, the tarsus levates. The experiments demonstrated that there is a purely neuronal link between the femoro-tibial joint position and the tibio-tarsal joint position. Moreover, it also reveals the effect of neuromodulatory compounds, such as dopamine, serotonin or octopamine. The tarsal reflex responses are fairly consistent across individuals, although significant variability across animals was found.To model a system where variability is an issue, a mathematical model with strong generalisation abilities is used: Artificial Neural Networks (ANNs). To design the ANNs, a metaheuristic algorithm has been implemented. The resulting ANNs are shown to be as accurate as other mathematical models used in physiology when used in a well known reflex system, the FETi responses. This results showed that ANNs are as good as Wiener methods in predicting responses and they outperform them in prediction of Gaussian inputs. Furthermore, they are able to predict responses in different animals, independently of the variability, with a more limited performance.New experimental methods are also designed to obtain accurate recordings of tarsal movements in response to knee joint changes. These experimental methods facilitate the data acquisition and its accuracy, reducing measurement errors. Using the mathematical methods validated, these responses are modelled and studied, showing responses to Gaussian and sinusoidal inputs, variability across individuals and effects of neuromodulators.With the tarsal reflex described and modelled, it can be used as a tool for further research in disciplines such as medicine, in the diagnose and treatment of euromuscular dysfunction or design of prosthesis and orthoses. This model can also be implemented in robotics to aid in stability when walking on irregular terrain

Locomotion grows up: The neuromechanical control of interlimb coordinating mechanisms in crayfish

Locomotion requires many dynamic interactions between organism and environment at several levels. It is not known how the nervous system controls all of these relationships to ultimately produce and guide locomotor behavior. Furthermore, it is not known whether the nervous system needs to recognize and control all of the possible body-environment interactions. In this study the crayfish (Procambarus clarkii) is used as a model system to test how size influences locomotor behavior and how a single, simplified neuromechanical system can accommodate these changes.;A set of behavioral experiments was conducted to characterize kinematics of freely walking juvenile crayfish to compare with adults. The purpose of these studies was to determine how crayfish adapt to a great change in size during their ontogeny. Juvenile and adult crayfish show differences in limb function and coordination. Although crayfish are decapods, the juveniles predominantly use the posterior legs and behave more like four-legged walkers. The difference in locomotor behavior can best be explained by differences in chelae size. Allometric relationships between juveniles and adults show limb and body morphologies scale proportionately. Adult chelae, or claws, are twice as long and contribute ∼20% more to the total body mass in fully mature crayfish. This increase in chelae size shifts the location of the center of mass anterior as crayfish grow. The result is a change in relative load distribution that appears to affect individual limb behavior and interlimb coordination. Shifting the center of mass in adults by amputating the chelae resulted in limb behavior and interlimb coordination more similar to that observed in juveniles. Likewise, applying load to the rostrum of juveniles altered behavior and changed limb function in the posterior legs similar to adults with large chelae. The results of these experiments suggest that crayfish of all sizes adapt to changes in load distribution by adjusting behavior of individual legs.;To test whether developmental influences have an effect on walking behavior, juveniles were induced to walk on a treadmill at various speeds. The animals showed more consistent limb coordination as walking speed increased, similar to adults. Selected legs were then amputated to test how gait was affected. Amputating legs removes sensory feedback from the distal leg to the central nervous system. The behavior of the stump is therefore more representative of the endogenous rhythmicity of the central pattern generator (CPG). Juveniles showed no differences in coordination in individual legs. Coordination between adjacent ipsilateral legs was also the same as that observed in adults following amputation. Furthermore, intact legs acquired new interlimb coordination similar to adults. These results suggested that juvenile and adult crayfish have functionally similar nervous systems controlling walking.;Finally, a 3-D virtual crayfish was built to test whether differences in walking between juveniles and adults could be due to mechanical influences alone. The model crayfish lacked direct connections between legs. The model responded to shifts in the center of mass by showing more consistent limb coordination in those legs nearest the center of mass. This was achieved through indirect mechanical coupling of the legs through the environment and body of the crayfish. This mechanism also produced realistic adaptive behavior when limbs were amputated. This showed that differences between adult and juvenile walking are due solely to mechanical influences associated with the changing center of mass as the animals grow. These results suggest further that organisms do not need high levels of control to produce coordinated behavior. Locomotor behavior arises through interactions between body, limb, and environment that are a function of the spatio-temporal dynamics of body morphology. The results may be applicable to a large number of walking systems

On the intrinsic control properties of muscle and relexes: exploring the interaction between neural and musculoskeletal dynamics in the framework of the equilbrium-point hypothesis

The aim of this thesis is to examine the relationship between the intrinsic dynamics of the body and its neural control. Specifically, it investigates the influence of musculoskeletal properties on the control signals needed for simple goal-directed movements in the framework of the equilibriumpoint (EP) hypothesis. To this end, muscle models of varying complexity are studied in isolation and when coupled to feedback laws derived from the EP hypothesis. It is demonstrated that the dynamical landscape formed by non-linear musculoskeletal models features a stable attractor in joint space whose properties, such as position, stiffness and viscosity, can be controlled through differential- and co-activation of antagonistic muscles. The emergence of this attractor creates a new level of control that reduces the system’s degrees of freedom and thus constitutes a low-level motor synergy. It is described how the properties of this stable equilibrium, as well as transient movement dynamics, depend on the various modelling assumptions underlying the muscle model. The EP hypothesis is then tested on a chosen musculoskeletal model by using an optimal feedback control approach: genetic algorithm optimisation is used to identify feedback gains that produce smooth single- and multijoint movements of varying amplitude and duration. The importance of different feedback components is studied for reproducing invariants observed in natural movement kinematics. The resulting controllers are demonstrated to cope with a plausible range of reflex delays, predict the use of velocity-error feedback for the fastest movements, and suggest that experimentally observed triphasic muscle bursts are an emergent feature rather than centrally planned. Also, control schemes which allow for simultaneous control of movement duration and distance are identified. Lastly, it is shown that the generic formulation of the EP hypothesis fails to account for the interaction torques arising in multijoint movements. Extensions are proposed which address this shortcoming while maintaining its two basic assumptions: control signals in positional rather than force-based frames of reference; and the primacy of control properties intrinsic to the body over internal models. It is concluded that the EP hypothesis cannot be rejected for single- or multijoint reaching movements based on claims that predicted movement kinematics are unrealistic

Spinal circuits can accommodate interaction torques during multijoint limb movements

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to centrally compute predicted interaction torques and their explicit compensation through anticipatory adjustment of descending motor commands. The alternative, based on the equilibrium-point hypothesis, claims that descending signals can be simple and related to the desired movement kinematics only, while spinal feedback mechanisms are responsible for the appropriate creation and coordination of dynamic muscle forces. Partial supporting evidence exists in each case. However, until now no model has explicitly shown, in the case of the second hypothesis, whether peripheral feedback is really sufficient on its own for coordinating the motion of several joints while at the same time accommodating intersegmental interaction torques. Here we propose a minimal computational model to examine this question. Using a biomechanics simulation of a two-joint arm controlled by spinal neural circuitry, we show for the first time that it is indeed possible for the neuromusculoskeletal system to transform simple descending control signals into muscle activation patterns that accommodate interaction forces depending on their direction and magnitude. This is achieved without the aid of any central predictive signal. Even though the model makes various simplifications and abstractions compared to the complexities involved in the control of human arm movements, the finding lends plausibility to the hypothesis that some multijoint movements can in principle be controlled even in the absence of internal models of intersegmental dynamics or learned compensatory motor signals.This work is funded by the project "eSMCs: Extending Sensorimotor Contingencies to Cognition," FP7-ICT-2009-6 no: 270212

Design of artificial neural oscillatory circuits for the control of lamprey- and salamander-like locomotion using evolutionary algorithms

This dissertation investigates the evolutionary design of oscillatory artificial neural networks for the control of animal-like locomotion. It is inspired by the neural organ¬ isation of locomotor circuitries in vertebrates, and explores in particular the control of undulatory swimming and walking. The difficulty with designing such controllers is to find mechanisms which can transform commands concerning the direction and the speed of motion into the multiple rhythmic signals sent to the multiple actuators typically involved in animal-like locomotion. In vertebrates, such control mechanisms are provided by central pattern generators which are neural circuits capable of pro¬ ducing the patterns of oscillations necessary for locomotion without oscillatory input from higher control centres or from sensory feedback. This thesis explores the space of possible neural configurations for the control of undulatory locomotion, and addresses the problem of how biologically plausible neural controllers can be automatically generated.Evolutionary algorithms are used to design connectionist models of central pattern generators for the motion of simulated lampreys and salamanders. This work is inspired by Ekeberg's neuronal and mechanical simulation of the lamprey [Ekeberg 93]. The first part of the thesis consists of developing alternative neural controllers for a similar mechanical simulation. Using a genetic algorithm and an incremental approach, a variety of controllers other than the biological configuration are successfully developed which can control swimming with at least the same efficiency. The same method is then used to generate synaptic weights for a controller which has the observed biological connectivity in order to illustrate how the genetic algorithm could be used for developing neurobiological models. Biologically plausible controllers are evolved which better fit physiological observations than Ekeberg's hand-crafted model. Finally, in collaboration with Jerome Kodjabachian, swimming controllers are designed using a developmental encoding scheme, in which developmental programs are evolved which determine how neurons divide and get connected to each other on a two-dimensional substrate.The second part of this dissertation examines the control of salamander-like swimming and trotting. Salamanders swim like lampreys but, on the ground, they switch to a trotting gait in which the trunk performs a standing wave with the nodes at the girdles. Little is known about the locomotion circuitry of the salamander, but neurobiologists have hypothesised that it is based on a lamprey-like organisation. A mechanical sim¬ ulation of a salamander-like animat is developed, and neural controllers capable of exhibiting the two types of gaits are evolved. The controllers are made of two neural oscillators projecting to the limb motoneurons and to lamprey-like trunk circuitry. By modulating the tonic input applied to the networks, the type of gait, the speed and the direction of motion can be varied.By developing neural controllers for lamprey- and salamander-like locomotion, this thesis provides insights into the biological control of undulatory swimming and walking, and shows how evolutionary algorithms can be used for developing neurobiological models and for generating neural controllers for locomotion. Such a method could potentially be used for designing controllers for swimming or walking robots, for instance

The role of the femoral chordotonal organ in motor control, interleg coordination, and leg kinematics in Drosophila melanogaster

Legged locomotion in terrestrial animals is often essential for mating and survival, and locomotor behavior must be robust and adaptable in order to be successful. The behavioral plasticity demonstrated by animals’ ability to locomote across diverse types of terrains and to change their locomotion in a task-dependent manner highlights the flexible and modular nature of locomotor networks. The six legs of insects are under the multi-level control of local networks for each limb and limb joint in addition to over-arching central control of the local networks. These networks, consisting of pattern-generating groups of interneurons, motor neurons, and muscles, receive modifying and reinforcing feedback from sensory structures that encode motor output. Proprioceptors in the limbs monitoring their position and movement provide information to these networks that is essential for the adaptability and robustness of locomotor behavior. In insects, proprioceptors are highly diverse, and the exact role of each type in motor control has yet to be determined. Chordotonal organs, analogous to vertebrate muscle spindles, are proprioceptive stretch receptors that span joints and encode specific parameters of relative movement between body segments. In insects, when leg chordotonal organs are disabled or manipulated, interleg coordination and walking are affected, but the simple behavior of straight walking on a flat surface can still be performed. The femoral chordotonal organ (fCO) is the largest leg proprioceptor and monitors the position and movements of the tibia relative to the femur. It has long been studied for its importance in locomotor and postural control. In Drosophila melanogaster, an ideal model organism due its genetic tractability, investigations into the composition, connectivity, and function of the fCO are still in their infancy. The fCO in Drosophila contains anatomical subgroups, and the neurons within a subgroup demonstrate similar responses to movements about the femur-tibia joint. Collectively, the experiments laid out in this dissertation provide a multi-faceted analysis of the anatomy, connectivity, and functional importance of subgroups of fCO neurons in D. melanogaster. The dissertation is divided into four chapters, representing different aspects of this complex and intriguing system. First, I present a detailed analysis of the composition of the fCO and its connectivity within the peripheral and central nervous systems. I demonstrate that the fCO is made up of anatomically distinct groups of neurons, each with their own unique features in the legs and ventral nerve cord. Second, I investigated the neuropeptide profile of the fCO and demonstrate that some fCO neurons express a susbtance that is known to act as a neuromodulator. Third, I demonstrate the sufficiency of subsets of fCO neurons to elicit reflex responses, highlighting the role of the Drosophila fCO in postural control. Lastly, I take this a step further and look into the functional necessity of these neuronal subsets for intra- and interleg coordination during walking. The importance of the fCO in motor control in D. melanogaster has been considered rather minor, though research into the topic is very limited. In the work laid out herein, I highlight the complexity of the Drosophila fCO and its role in the determination of locomotor behavior

Controlling underwater robots with electronic nervous systems

We are developing robot controllers based on biomimetic design principles. The goal is to realise the adaptive capabilities of the animal models in natural environments. We report feasibility studies of a hybrid architecture that instantiates a command and coordinating level with computed discrete-time map-based (DTM) neuronal networks and the central pattern generators with analogue VLSI (Very Large Scale Integration) electronic neuron (aVLSI) networks. DTM networks are realised using neurons based on a 1-D or 2-D Map with two additional parameters that define silent, spiking and bursting regimes. Electronic neurons (ENs) based on Hindmarsh-Rose (HR) dynamics can be instantiated in analogue VLSI and exhibit similar behaviour to those based on discrete components. We have constructed locomotor central pattern generators (CPGs) with aVLSI networks that can be modulated to select different behaviours on the basis of selective command input. The two technologies can be fused by interfacing the signals from the DTM circuits directly to the aVLSI CPGs. Using DTMs, we have been able to simulate complex sensory fusion for rheotaxic behaviour based on both hydrodynamic and optical flow senses. We will illustrate aspects of controllers for ambulatory biomimetic robots. These studies indicate that it is feasible to fabricate an electronic nervous system controller integrating both aVLSI CPGs and layered DTM exteroceptive reflexes

The Role of Reflexes Versus Central Pattern Generators

Animals execute locomotor behaviors and more with ease. They have evolved these breath-taking abilities over millions of years. Cheetahs can run, dolphins can swim and flies can fly like no artificial technology can. It is often argued that if human technology could mimic nature, then biological-like performance would follow. Unfortunately, the blind copying or mimicking of a part of nature [Ritzmann et al., 2000] does not often lead to the best design for a variety of reasons [Vogel, 1998]. Evolution works on the just good enough principle. Optimal designs are not the necessary end product of evolution. Multiple satisfactory solutions can result in similar performances. Animals do bring to our attention amazing designs, but these designs carry with them the baggage of their history. Moreover, natural design is constrained by factors that may have no relationship to human engineered designs. Animals must be able to grow over time, but still function along the way. Finally, animals are complex and their parts serve multiple functions, not simply the one we happen to examine. In short, in their daunting complexity and integrated function, understanding animal behaviors remains as intractable as their capabilities are tantalizing

Multimodal Proprioceptive Integration in Sensorimotor Networks of an Insect Leg

An animal’s nervous system monitors the actions of the body using its sense of proprioception. This information is used for precise motor control and to enable coordinated interaction with the animal’s surroundings. Proprioception is a multimodal sense that includes feedback about limb movement and loading from various peripheral sense organs. The sensory information from distinct sense organs must be integrated by the network to form a coherent representation of the current proprioceptive state and to elicit appropriate motor behavior. By combining intra- and extracellular electrophysiological recording techniques with precise mechanical sensory stimulation paradigms, I studied multimodal proprioceptive integration in the sensorimotor network of the stick insect leg. The findings demonstrate where, when, and how sensory feedback from load-sensing campaniform sensilla (CS) is integrated with movement information from the femoral chordotonal organ (fCO) in the sensorimotor network controlling movement of the femur-tibia (FTi) joint. Proprioceptive information about distinct sensory modalities (load / movement) and from distinct sense organs of the same sensory modality (trochanterofemoral CS (tr/fCS) / tibial CS (tiCS)) was distributed into one network of local premotor nonspiking interneurons (NSIs). The NSIs’ processing of fCO, tr/fCS, and tiCS was antagonistic with respect to a given NSI’s effect on the motor output of extensor tibiae motor neurons (ExtTi MNs). Spatial summation of load and movement feedback occurred in the network of premotor NSIs, whereas temporal summation was shifted between sensory modalities. Load feedback (tr/fCS / tiCS) was consistently delayed relative to movement signals (fCO) throughout the sensorimotor pathways of sensory afferents, premotor NSIs, and ExtTi MNs. The connectivity between these neuron types was inferred using transmission times and followed distinct patterns for individual sense organs. At the motor output level of the system, the temporal shift of simultaneously elicited load and movement feedback caused load responses to be superimposed onto ongoing movement responses. These results raised the hypothesis that load could alter movement signal processing. Load (tiCS) affected movement (fCO) signal gain by presynaptic afferent inhibition. In postsynaptic premotor NSIs, this led to altered movement parameter dependence and nonlinear summation of load and movement signals. Specifically, the amplitude dependence of NSIs opposing ExtTi MN output was increased, and, consistently, the movement response gain of the slow ExtTi MN was decreased. Movement signal processing in the premotor network was altered depending on the proprioceptive context, i.e. the presence or absence of load feedback. Lateral presynaptic interactions between load (tiCS) and movement (fCO) afferents were reciprocal, i.e. existed from fCO to tiCS afferents and vice versa, and also occurred between sensory afferents of the same sense organ. Additionally, a new type of presynaptic interaction was identified. Load signals increased the gain of directional movement information by releasing unidirectionally velocity- or acceleration-sensitive fCO afferents from tonic presynaptic inhibition. Paired double recordings showed lateral connectivity also at the level of the premotor NSI network. NSIs interacted via reciprocal excitatory connections. Additionally, the activity of individual NSIs was correlated in the absence of external stimuli, and specific types of NSIs showed rhythmic 30 Hz oscillations of the resting membrane potential, indicating an underlying mechanism of network synchronization. Taken together, the results of this dissertation provide an understanding of the integration of multimodal proprioceptive feedback in the sensorimotor network by identifying neuronal pathways and mechanism underlying spatial and temporal signal summation. The local network uses multimodal signal integration for context-dependent sensory processing, thereby providing insights into the mechanism by which a local network can adapt sensory processing to the behavioral context. Initial results clearly highlight the necessity to consider lateral connections along sensorimotor pathways to unravel the complex computations underlying proprioceptive processing and motor control. The findings on the integration of proprioceptive signals, obtained in the resting animal, broaden our understanding of sensorimotor processing and motor control not only in the stationary, but also in the walking animal

Neuronal mechanisms of feedback postural control

Different species maintain a basic body posture due to the activity of the postural control system. An efficient control of the body orientation, as well as the body configuration, is important for standing and during locomotion. A general goal of the present study was to analyze neuronal feedback mechanisms contributing to stabilization of the trunk orientation in space, as well as those controlling the body configuration. Two animal models of different complexity, the lamprey (a lower vertebrate) and the rabbit (a mammal), were used. Neuronal mechanisms underlying lateral stability were analyzed in rabbits. The dorsalside- up trunk orientation in standing quadrupeds is maintained by the postural system driven mainly by somatosensory inputs from the limbs. Postural limb reflexes (PLRs) represent a substantial component of this system. To characterize spinal neurons of the postural networks, in decerebrate rabbit, activity of individual spinal neurons in L4-L6 was recorded during PLRs caused by lateral tilts of the supporting platform. Spinal neurons mediating PLRs have been revealed, and different parameters of their activity were characterized. All neurons were classified into four types according to the combination of tilt-related sensory inputs to a neuron from the ipsi- and contralateral limb (determining the modulation of a neuron). A hypothesis about the role of different types of PLR-related neurons for trunk stabilization in different planes has been proposed. To reveal contribution of supraspinal influences to modulation of PLR-related neurons, the activity of individual spinal neurons was recorded during stimulation causing PLRs under two conditions: (i) when spinal neurons received supraspinal influences, and (ii) when these influences were temporarily abolished by a cold block of spike propagation in spinal pathways at T12 (“reversible spinalization”). The effects of reversible spinalization on individual neurons were diverse. Neurons, which did not receive supraspinal influences, were located mainly in the dorsal horn, whereas most neurons, receiving excitatory supraspinal influences were located in the intermediate zone and ventral horn. The population of PLRrelated neurons presumably responsible for disappearance of muscle tone and PLRs after spinalization was revealed. The effects of manipulation with the tonic supraspinal drive (by means of binaural galvanic vestibular stimulation, GVS) on the postural system were studied. GVS creates asymmetry in tonic supraspinal drive, resulting in a lateral body sway towards the anode. This new body orientation is actively stabilized. To reveal the underlying mechanisms, spinal neurons were recorded during PLRs with and without GVS. It was found that GVS enhanced PLRs on the cathode side and reduced them on the anode side. It was suggested that GVS changes the set-point of the postural system through the change of the gain in antagonistic PLRs. Two sub-groups of PLR-related neurons presumably mediating the effect of GVS on PLRs were found. An artificial feedback system was formed in which GVS-caused body sway was used to counteract the lateral body sway resulting from a mechanical perturbation of posture. It was demonstrated that the GVS-based artificial feedback was able to restore the postural function in rabbits with postural deficit. We suggested that such a control system could compensate for the loss of lateral stability of different etiology. Neuronal mechanisms underlying control of body configuration were analyzed in lampreys. The lamprey is capable of different forms of motor behavior: fast forward swimming (FFS), slow forward swimming (SFS), backward swimming (BS), forward and backward crawling, and lateral turns (LT). The amplitude of the body flexion (characterizing the body configuration) differs in different forms of motor behavior. In the lamprey, signals about the body configuration are provided by intraspinal stretch receptor neurons (SRNs). To clarify whether the networks generating different forms of motor behavior are located in the spinal cord, in chronic spinal lampreys, electrical stimulation of the spinal cord was performed. It was demonstrated that all forms of motor behavior are generated by the spinal networks. To study SRN-mediated reflexes and their contribution to the control of body configuration in different motor behaviors, in the in vitro preparation we recorded responses of reticulospinal (RS) neurons and motoneurons (MNs) to bending of the spinal cord in different planes and at different rostro-caudal levels during different forms of fictive motor behavior Bending in the pitch plane during FFS caused SRN-mediated reflexes. MNs on the convex side were activated by pitch bending in the mid-body region. These reflexes will reduce the bend, thus contributing to maintenance of rectilinear body axis in the pitch plane during FFS. It was found that bending in the yaw plane activated MNs on the convex side during FFS, but on the concave side during different forms of escape behavior (SFS, BS, LT). It was demonstrated that a reversal of reflex responses was due to ipsilateral supraspinal commands causing modifications of the spinal network located in the ipsi-hemicord. A population of RS neurons (residing in the middle rhombencephalic reticular nuclei) presumably transmitting these commands has been revealed. We suggest that modifications of SRN-mediated reflex responses will result in the decrease and increase of the lateral bending amplitude during FFS and escape behaviors, respectively, thus reinforcing movements generated in each specific behavior. Thus in the present study, for the first time, some neuronal mechanisms underlying reflex reversal in vertebrate animals have been revealed