Activity of leg motoneurons during single leg walking of the stick insect: From synaptic inputs to motor performance

In the single middle leg preparation of the stick insect, leg motoneurons were recorded intracellularly during stepping movements on a treadmill. This preparation allows investigating the synaptic drive from local sense organs and central pattern generating networks to motoneurons. The synaptic drive comprises rhythmic (�phasic�) excitation and inhibition and a sustained (�tonic�) depolarization. This general scheme was found to be true for all motoneurons innervating the muscles of the three major leg joints. A comparison e.g. with results obtained from deafferented and pharmacologically activated preparations of the stick insect suggests that both tonic depolarization and phasic inhibition originate from central networks, while the phasic excitation is mainly generated by local sense organs. Recruitment of motoneurons was studied on the flexor tibiae muscle as an example of a complexly innervated muscle. It is innervated by ~14 slow, semifast and fast motoneurons that are firing action potentials during the stance phase of the step cycle. During slow steps or steps under small load, less motoneurons are recruited than during fast steps or steps under high load. Fast flexor motoneurons are recruited later during stance phase than slow motoneurons. All motoneurons receive substantial common synaptic drive during walking. They are recruited in an orderly fashion due to the more negative resting membrane potential of the fast motoneurons, which thus require a larger and longer lasting depolarization to reach the threshold for the generation of action potentials. Because walking is not invariable but needs to be adjusted to the behavioral requirements, it was investigated how these adjustments are implemented at the motoneuronal level. The activity of flexor and extensor tibiae motoneurons was analyzed during steps with different velocities. Extensor motoneuron activity during the extension phase of the step cycle (i.e. swing phase) is rather stereotypic and invariant with stance velocity. Flexor motoneurons show two distinct periods of depolarization at the beginning of stance. The initial depolarization is also stereotypic and most likely generated by a release from inhibition that allows the underlying tonic excitation to depolarize the neuron. The subsequent depolarization is larger and faster during fast steps than during slow steps. This indicates that in the single insect leg during walking, mechanisms for altering stepping velocity are becoming effective only during already ongoing stance phase motor output. Since a large portion of the phasic excitation arises from sense organs, it is conceivable that for the generation of different stepping velocities the effectiveness of these pathways are centrally modulated, for example by variations in the degree of presynaptic inhibition

Adaptive Motor Control: Neuronal Mechanisms Underlying (Targeted) Searching Movements

Animals move through a complex environment and therefore constantly need to adapt their behavior to the surroundings. For this purpose, they use sensory information of various kind. As one strategy to gain tactile cues, animals perform leg searching movements when loosing foothold. The kinematics of these searching movements have been well investigated in the stick insect. In this thesis, the modification of stick insect searching movements following a tactile cue are explored as an example of a sensory-motor system that adapts to environmental conditions. Furthermore, the premotor neuronal network underlying the generation of searching behavior is investigated. Searching movements were studied in animals with a single intact leg that was free to move in the vertical plane. After several cycles of searching movements, a stick was introduced into the plane of movements such that animals would touch it with its distal leg. As is known from previous studies, in such a situation stick insects try to grasp the object that they touch. In my experiments, the stick was retracted as soon as a brief contact with the animals' leg had occurred. Therefore, animals could not grasp the stick. I could show that following this short tactile cue, stick insects modify their searching movements to target the former position of the object (PO). Targeting occurs by a change in two parameters of searching movements: animals (i) shift the average leg position of their searching movements towards the PO and (ii) confine searching movements to the PO by a reduction in movement amplitude. These two parameters, position and amplitude, can be changed independently of each other. Searching movements are flexibly adjusted to different locations of the object which demonstrates the targeted response to be a situation-dependent adaptive behavior. The targeted response outlasts the tactile stimulus by several seconds suggesting a simple form of short term memory of the PO as proposed for targeted movements of other insects. Vision is not necessary for a targeted response. Instead, tactile cues from leg sensory organs are important. Two proprioceptive organs, the trochanteral hairplate (trHP) and the femoral chordotonal organ (fCO), are crucial for targeting. Other sensory organs like tactile hairs and campaniform sensilla are dispensable. The brain is not necessary for a targeted response, therefore the adaptation of searching movements is likely to be mediated on the thoracic level. The premotor neuronal network underlying searching movement generation was investigated using the same single-leg preparation as described above. Nonspiking interneurons (NSIs) of the premotor network were recorded intracellularly during searching movements. Additionally, EMG recordings of the four main leg muscles that generate searching movements in the vertical plane were recorded. The membrane potential of previously described, as well as newly identified NSIs providing synaptic drive to leg motoneurons is shown to be phasically modulated during searching. Therefore, NSIs are part of the premotor network for the generation of searching movements. NSIs that were previously described to contribute to the generation of walking behavior are shown to contribute to the generation of searching behavior. When artificially de- or hyperpolarized by current injection, several NSIs are able to induce changes in searching movement parameters like position, amplitude, velocity of movements, or inter-joint coordination. One NSI is able to drive or stop searching movements. Each NSI acts on a specific set of parameters. The same NSIs that were recorded during searching also were recorded during walking behavior. In comparison, NSI membrane potential modulations during searching are smaller in amplitude and more undulated than during walking. In contrast, fast transitions in NSI membrane potential are closely coupled to step phase transitions during walking. The most prominent difference in NSI membrane potential occurs during step phase (when walking) as compared to flexion phase (during searching). This difference might be attributed to load signals from campaniform sensilla. Analogous to results of previous studies in the stick insect, this highlights the importance of sensory feedback in shaping the motor output. Finally, NSIs were recorded intracellularly while animals with their searching leg made contact with the stick that was introduced into the plane of movement. First results indicate that the response of a given NSI to this contact is characteristic and depends on the direction of touch

Role of local premotor nonspiking interneurons in walking pattern generation of the stick insect Carausius morosus

In the course of this thesis, neural mechanisms underlying the generation of single leg stepping in the stick insect Carausius morosus were investigated at the premotor level. Local nonspiking interneurons (NSIs) are important premotor elements within the leg muscle control system of insects, which integrate sensory signals from different sources and provide synaptic drive onto motoneurons (MNs). The single middle leg preparation used allows intracellular recordings from identified NSIs while the active animal performs stepping movements on a treadmill. For identification, NSIs were stained following physiological characterization by iontophoretical dye injection and viewed with a confocal laser scanning microscope. The alternating activity of flexor and extensor tibiae MNs during single middle leg stepping, which characterizes stance and swing phase, respectively, was monitored by extracellular recordings. In the first part of the thesis, the activity pattern of NSIs driving tibial MNs during single leg stepping was studied and their contribution to the generation of stepping motor output was revealed. With the initiation of stepping, modulations of membrane potential were generated in all NSIs that were closely related to the step cycle. The activity pattern comprised distinct excitatory or inhibitory phasic input, during at least one phase of the step cycle. Most NSI types showed an inversion of membrane potential polarization from one phase of the step cycle to the other. It was shown that the activity pattern of the individual NSIs during stepping was not predictable from the synaptic drive, i.e., excitatory or inhibitory, they provide onto MNs in the resting animal. Artificial alterations of membrane potential and measurements of local input resistance for individual NSIs revealed that phasic excitatory and inhibitory modulations of membrane potential during stepping results from true excitatory and inhibitory synaptic input. Current injections into NSI I1 immediately terminated stepping sequences, indicating an important role of I1 in the control of motor output for stepping. The amplitude of phasic membrane potential modulation of NSIs during stepping varied markedly. The maximum peak-to-peak amplitude of membrane potential modulation during stepping amounted to 16.9 ± 6.0 mV on average for all NSIs presented in this study and ranged from 5 to 34 mV for individual recordings. The time of peak and trough potential occurrence within a step cycle appears to contribute substantially to the patterning of motor output, since the extensor MN activity was closely correlated with the membrane potential of individual NSIs, e.g., E2/3, E4, E8 and I2. For the first time, it could be shown that the activity of NSIs during stepping can largely be explained by the state dependency of their inputs from the femoral chordotonal organ, one of the main leg sensors. Hence, the results presented here strongly support the notion that the motor response during the �active reaction� represents a part of the control regime for the generation of single leg stepping. In the second part of the thesis, the interest was to investigate neural mechanisms underlying adaptivity in locomotor systems. Therefore, it was examined which parameters contribute to alterations in stepping velocity. An important finding was that stepping velocity varies with membrane potential alterations of NSIs activated during stance phase, but not with NSIs activated during swing phase. Furthermore, the results suggest that the stance part of the locomotor network is stronger activated during fast stepping velocities and that the swing part is simultaneously inhibited to the same extent. However, investigation of extensor MN activity failed to show a correlation with stepping velocity. This finding implies that swing phase activity is independent of stepping velocity and, hence, corroborates the notion that the swing part of the premotor network does not contribute to alterations in stepping velocity. Finally, it was investigated whether there is a correlation between swing phase activation and stance phase velocity during single leg stepping. The results indicate that there is no influence between stance and swing phase activation in the single middle leg preparation, at least, not in the way that activation strength of stance would influence the subsequent activation of swing phase. The insights gained on premotor NSIs within the femur-tibia joint control system of the stick insect raise the assumption of a premotor network organized into functionally different and partly overlapping pools of NSIs. In the single middle leg preparation, individual NSI types appear to control the actual magnitude of stepping motor output (e.g., E2/3, E8, I2) or the stepping velocity (e.g., E1, I1, I2), while others seem to control step phase transitions (e.g., E2/3, E4, I4) or phase duration (e.g., I8, I1, E1)

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

Responses of a Locust Looming Sensitive Neuron, Flight Muscle Activity and Body Orientation to Changes in Object Trajectory, Background Complexity, and Flight Condition

Survival is one of the highest priorities of any animal. Interaction in the environment with conspecifics, predators, or objects, is driven by evolution of systems that can efficiently and rapidly respond to potential collision with these stimuli. Flight introduces further complexity for a collision avoidance system, requiring an animal to compute air speed, wind speed, ground speed, as well as transverse and longitudinal image flow, all within the context of detecting an approaching object. Understanding the mechanisms underlying neural control and coordination of motor systems to produce behaviours in response to the natural environment is a main goal of neuroethology. Locusts have a tractable nervous system, and a robust, reproducible collision avoidance response to looming stimuli. This tractable system allows recording from the nerve cord and flight muscles with precision and reliability, allowing us to answer important questions regarding the neuronal control of muscle coordination and, in turn, collision avoidance behaviour during flight. In flight, a collision avoidance behaviour will most often be a turn away from the approaching stimulus. I tested the hypothesis that during loosely tethered flight, synchrony between flight muscles increases just prior to the initiation of a turn and that muscle synchronization would correlate with body orientation changes during flight steering. I found that hind and forewing flight muscle synchronization events correlated strongly with forewing flight muscle latency changes, and to pitch and roll body orientation changes in response to a lateral looming visual stimulus. These findings led me to investigate further the role of the looming-sensitive descending contralateral movement detector (DCMD) neuron in flight muscle coordination and the initiation of forewing asymmetry in rigidly tethered locusts that generate a flight-like rhythm. By conducting simultaneous recordings from the nerve cord, forewing flight muscles, and visually recording the wing positions within the same flying animal, I hypothesized that DCMD burst properties would correlate with flight muscle activity changes and the initiation of wing asymmetry associated with turning behaviour. Furthermore, I accessed the effect of manipulating background complexity of the locust’s visual environment, looming object trajectory, and the putative effect of mechanosensory feedback during flight, on DCMD burst firing rate properties. DCMD burst properties were affected by changes in background complexity and object trajectory, and most interestingly during flight. This suggests that reafferent feedback from the flight motor system modulates the DCMD signal, and therefore represents a more naturalistic representation of collision avoidance behaviour. A pivotal discovery in my study was the temporal role of bursting in collision avoidance behaviour. I found that the first burst in a DCMD spike train represents the earliest detectable neuronal event correlated with muscle activity changes and the creation of wing asymmetry. I found strong correlations across all object trajectories and background complexities, between the timing of the first bursts, flight muscle activity changes and the initiation of wing asymmetry. These findings reinforce the importance of the temporal properties of DCMD bursting in collision avoidance behaviour

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Characterisation of the biomechanical, passive, and active properties of femur-tibia joint leg muscles in the stick insect Carausius morosus

The understanding of locomotive behaviour of an animal necessitates the knowledge not only about its neural activity but also about the transformation of this activity patterns into muscle activity. The stick insect is a well studied system with respect to its motor output which is shaped by the interplay between sensory signals, the central neural networks for each leg joint and the coordination between the legs. The muscles of the FT (femur-tibia) joint are described in their morphologies and their motoneuronal innervation patterns, however little is known about how motoneuronal stimulation affects their force development and shortening behaviour. One of the two muscles moving the joint is the extensor tibiae, which is particularly suitable for such an investigation as it features only three motoneurons that can be activated simultaneously, which comes close to a physiologically occuring activation pattern. Its antagonist, the flexor tibiae, has a more complex innervation and a biomechanical investigation is only reasonable at full motoneuronal recruitment. Muscle force and length changes were measured using a dual-mode lever system that was connected to the cut muscle tendon. Both tibial muscles of all legs were studied in terms of their geometry: extensor tibiae muscle length changes with the cosine of the FT joint angle, while flexor tibiae length changes with the negative cosine, except for extreme angles (close to 30° and 180°). For all three legs, effective flexor tibiae moment arm length (0.564 mm) is twice that of the extensor tibiae (0.282 mm). Flexor tibiae fibres are 1.5 times longer (2.11 mm) than extensor tibiae fibres (1.41 mm). Active isometric force measurements demonstrated that extensor tibiae single twitch force is notably smaller than its maximal tetanical force at 200 Hz (2-6 mN compared to 100-190 mN) and takes a long time to decrease completely (> 140 ms). Increasing either frequency or duration of the stimulation extends maximal force production and prolongs the relaxation time of the extensor tibiae. The muscle reveals `latch´ properties in response to a short-term increase in activation. Its working range is on the ascending limb of the force-length relationship (see Gordon et al. (1966b)) with a shift in maximum force development towards longer fibre lengths at lower activation. The passive static force increases exponentially with increasing stretch. Maximum forces of 5 mN for the extensor, and 15 mN for the flexor tibiae occur within the muscles´ working ranges. The combined passive torques of both muscles determine the rest position of the joint without any muscle activity. Dynamically generated forces of both muscles can become as large as 50-70 mN when stretch ramps mimick a fast middle leg swing phase. FT joint torques alone (with ablated muscles) do not depend on FT joint angle, but on deflection amplitude and velocity. Isotonic force experiments using physiological activation patterns demonstrate that the extensor tibiae acts like a low-pass filter by contracting smoothly to fast instantaneous stimulation frequency changes. Hill hyperbolas at 200 Hz vary a great deal with respect to maximal force (P0) but much less in terms of contraction velocity (V0) for both tibial muscles. Maximally stimulated flexor tibiae muscles are on average 2.7 times stronger than extensor tibiae muscles (415 mN and 151 mN), but contract only 1.4 times faster (6.05 mm/s and 4.39 mm/s). The dependence of extensor tibiae V0 and P0 on stimulation frequency can be described with an exponential saturation curve. V0 increases linearly with length within the muscle´s working range. Loaded release experiments characterise extensor and flexor tibiae series elastic components as quadratic springs. The mean spring constant of the flexor tibiae is 1.6 times larger than of the extensor tibiae at maximal stimulation. Extensor tibiae stretch and relaxation ramps show that muscle relaxation time constant slowly changes with muscle length, and thus muscle dynamics have a long-lasting dependence on muscle length history. High-speed video recordings show that changes in tibial movement dynamics match extensor tibiae relaxation changes at increasing stimulation duration

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)