Locomotor activity in spinal man: significance of afferent input from joint and load receptors

The aim of this study was to differentiate the effects of body load and joint movements on the leg muscle activation pattern during assisted locomotion in spinal man. Stepping movements were induced by a driven gait orthosis (DGO) on a treadmill in patients with complete para‐/tetraplegia and, for comparison, in healthy subjects. All subjects were unloaded by 70% of their body weight. EMG of upper and lower leg muscles and joint movements of the DGO of both legs were recorded. In the patients, normal stepping movements and those mainly restricted to the hips (blocked knees) were associated with a pattern of leg muscle EMG activity that corresponded to that of the healthy subjects, but the amplitude was smaller. Locomotor movements restricted to imposed ankle joint movements were followed by no, or only focal EMG responses in the stretched muscles. Unilateral locomotion in the patients was associated with a normal pattern of leg muscle EMG activity restricted to the moving side, while in the healthy subjects a bilateral activation occurred. This indicates that interlimb coordination depends on a supraspinal input. During locomotion with 100% body unloading in healthy subjects and patients, no EMG activity was present. Thus, it can be concluded that afferent input from hip joints, in combination with that from load receptors, plays a crucial role in the generation of locomotor activity in the isolated human spinal cord. This is in line with observations from infant stepping experiments and experiments in cats. Afferent feedback from knee and ankle joints may be involved largely in the control of focal movement

Neural Control of Interlimb Oscillations II. Biped and Quadruped Gaits and Bifurications

Behavioral data concerning animal and human gaits and gait transitions are simulated as emergent properties of a central pattern generator (CPG) model. The CPG model is a version of the Ellias-Grossberg oscillator. Its neurons obey Hodgkin-Huxley type equations whose excitatory signals operate on a faster time scale than their inhibitory signals in a recurrent on-center off-surround anatomy. A descending command or GO signal activates the gaits and triggers gait transitions as its amplitude increases. A single model CPG can generate both in-phase and anti-phase oscillations at different GO amplitudes. Phase transition from either in-phase to anti-phase oscillations, or from anti-phase to in-phase oscillations, can occur in different parameter ranges, as the GO signal increases. Quadruped vertebrate gaits, including the amble, the walk, all three pairwise gaits (trot, pace, and gallop), and the pronk are simulated using this property. Rapid gait transitions are simulated in the order walk, trot, pace, and gallop that occurs in the cat, along with the observed increase in oscillation frequency. Precise control of quadruped gait switching uses GO-dependent. modulation of inhibitory interactions, which generates a different functional anatomy at different arousal levels. The primary human gaits (the walk and the run) and elephant gaits (the amble and the walk) are simulated, without modulation, by oscillations with the same phase relationships but different waveform shapes at different GO signal levels, much as the duty cycles of the feet are longer in the walk than in the run. Relevant neural data from spinal cord, globus palliclus, and motor cortex, among other structures, are discussedArmy Research Office (DAAL03-88-K-0088); Advanced Research Projects Agency (90-0083); National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0499, F49620-92-J-0225, 90-0128

Analytical CPG model driven by limb velocity input generates accurate temporal locomotor dynamics

The ability of vertebrates to generate rhythm within their spinal neural networks is essential for walking, running, and other rhythmic behaviors. The central pattern generator (CPG) network responsible for these behaviors is well-characterized with experimental and theoretical studies, and it can be formulated as a nonlinear dynam- ical system. The underlying mechanism responsible for locomotor behavior can be expressed as the process of leaky integration with resetting states generating appropriate phases for changing body velocity. The low-dimensional input to the CPG model generates the bilateral pattern of swing and stance modulation for each limb and is consistent with the desired limb speed as the input command. To test the minimal configuration of required parameters for this model, we reduced the system of equations representing CPG for a single limb and provided the analytical solution with two complementary methods. The analytical and empirical cycle durations were similar (R2 = 0.99) for the full range of walking speeds. The structure of solution is consistent with the use of limb speed as the input domain for the CPG network. Moreover, the reciprocal interaction between two leaky integration processes representing a CPG for two limbs was sufficient to capture fundamental experimental dynamics associated with the control of heading direction. This analysis provides further support for the embedded velocity or limb speed representation within spinal neural pathways involved in rhythm generation

EEG During Pedaling: Evidence for Cortical Control of Locomotor Tasks

Objective: This study characterized the brain electrical activity during pedaling, a locomotor-like task, in humans. We postulated that phasic brain activity would be associated with active pedaling, consistent with a cortical role in locomotor tasks. Methods: Sixty four channels of electroencephalogram (EEG) and 10 channels of electromyogram (EMG) data were recorded from 10 neurologically-intact volunteers while they performed active and passive (no effort) pedaling on a custom-designed stationary bicycle. Ensemble averaged waveforms, 2 dimensional topographic maps and amplitude of the β (13–35 Hz) frequency band were analyzed and compared between active and passive trials. Results: The peak-to-peak amplitude (peak positive–peak negative) of the EEG waveform recorded at the Cz electrode was higher in the passive than the active trials (p \u3c 0.01). β-band oscillations in electrodes overlying the leg representation area of the cortex were significantly desynchronized during active compared to the passive pedaling (p \u3c 0.01). A significant negative correlation was observed between the average EEG waveform for active trials and the composite EMG (summated EMG from both limbs for each muscle) of the rectus femoris (r = −0.77, p \u3c 0.01) the medial hamstrings (r = −0.85, p \u3c 0.01) and the tibialis anterior (r = −0.70, p \u3c 0.01) muscles. Conclusions: These results demonstrated that substantial sensorimotor processing occurs in the brain during pedaling in humans. Further, cortical activity seemed to be greatest during recruitment of the muscles critical for transitioning the legs from flexion to extension and vice versa. Significance: This is the first study demonstrating the feasibility of EEG recording during pedaling, and owing to similarities between pedaling and bipedal walking, may provide valuable insight into brain activity during locomotion in humans

Single joint perturbation during gait: neuronal control of movement trajectory

The aim of this study was to investigate the effect of single joint displacement on the pattern of leg muscle electromyographic (EMG) activity during locomotion. For the first time, unilateral rotational hip or knee joint displacements were applied by a driven orthotic device at three phases of swing during locomotion on a treadmill. The response pattern of bilateral leg muscle activation with respect to the timing and selection of muscles was almost identical for displacements of upper (hip joint) or lower (knee joint) leg. The leg muscle EMG responses were much stronger when the displacement was directed against the physiological movement trajectory, compared with when the displacement was reinforcing, especially during mid swing. It is suggested that these response patterns are designed to restore physiological movement trajectory rather than to correct a single joint position. Displacements released at initial or terminal swing, assisting or resisting the physiological movement trajectory, were followed by similar and rather unspecific response patterns. This was interpreted as being directed to stabilise body equilibriu

Preclinical evidence supporting the clinical development of central pattern generator-modulating therapies for chronic spinal cord-injured patients

Ambulation or walking is one of the main gaits of locomotion. In terrestrial animals, it may be defined as a series of rhythmic and bilaterally coordinated movement of the limbs which creates a forward movement of the body. This applies regardless of the number of limbs - from arthropods with six or more limbs to bipedal primates. These fundamental similarities among species may explain why comparable neural systems and cellular properties have been found, thus far, to control in similar ways locomotor rhythm generation in most animal models. The aim of this article is to provide a comprehensive review of the known structural and functional features associated with central nervous system (CNS) networks that are involved in the control of ambulation and other stereotyped motor patterns - specifically Central Pattern Generators (CPGs) that produce basic rhythmic patterned outputs for locomotion, micturition, ejaculation, and defecation. Although there is compelling evidence of their existence in humans, CPGs have been most studied in reduced models including in vitro isolated preparations, genetically-engineered mice and spinal cord-transected animals. Compared with other structures of the CNS, the spinal cord is generally considered as being well-preserved phylogenetically. As such, most animal models of SCI should be considered as valuable tools for the development of novel pharmacological strategies aimed at modulating spinal activity and restoring corresponding functions in chronic spinal cord-injured patients

Functional contribution of the mesencephalic locomotor region to locomotion

Parce qu'il est naturel et facile de marcher, il peut sembler que cet acte soit produit aussi facilement qu'il est accompli. Au contraire, la locomotion nécessite une interaction neurale complexe entre les neurones supraspinaux, spinaux et périphériques pour obtenir une locomotion fluide et adaptée à l'environnement. La région locomotrice mésencéphalique (MLR) est un centre locomoteur supraspinal situé dans le tronc cérébral qui a notamment pour rôle d'initier la locomotion et d'induire une transition entre les allures locomotrices. Cependant, bien que cette région ait initialement été identifiée comme le noyau cunéiforme (CnF), un groupe de neurones glutamatergiques, et le noyau pédonculopontin (PPN), un groupe de neurones glutamatergiques et cholinergiques, son corrélat anatomique est encore un sujet de débat. Et alors qu'il a été prouvé que, que ce soit lors d’une stimulation de la MLR ou pour augmenter la vitesse locomotrice, la plupart des quadrupèdes présentent un large éventail d'allures locomotrices allant de la marche, au trot, jusqu’au galop, la gamme exacte des allures locomotrices chez la souris est encore inconnue. Ici, en utilisant l'analyse cinématique, nous avons d'abord décidé d'identifier d’évaluer les allures locomotrices des souris C57BL / 6. Sur la base de la symétrie de la démarche et du couplage inter-membres, nous avons identifié et caractérisé 8 allures utilisées à travers un continuum de fréquences locomotrices allant de la marche au trot puis galopant avec différents sous-types d'allures allant du plus lent au plus rapide. Certaines allures sont apparues comme attractrices d’autres sont apparues comme transitionnelles. En utilisant une analyse graphique, nous avons également démontré que les transitions entre les allures n'étaient pas aléatoires mais entièrement prévisibles. Nous avons ensuite décidé d'analyser et de caractériser les contributions fonctionnelles des populations neuronales de CnF et PPN au contrôle locomoteur. En utilisant des souris transgéniques exprimant une opsine répondant à la lumière dans les neurones glutamatergiques (Glut) ou cholinergiques (CHAT), nous avons photostimulé (ou photo-inhibé) les neurones glutamatergiques du CnF ou du PPN ou les neurones cholinergiques du PPN. Nous avons découvert que les neurones glutamatergiques du CnF initient et modulent l’allure locomotrice et accélèrent le rythme, tandis que les neurones glutamatergiques et cholinergiques du PPN le ralentissent. En initiant, modulant et en accélérant la locomotion, notre étude identifie et caractérise des populations neuronales distinctes de la MLR. Définir et décrire en profondeur la MLR semble d’autant plus urgent qu’elle est devenue récemment une cible pour traiter les symptômes survenant après une lésion de la moelle épinière ou liés à la maladie de Parkinson.Because it is natural and easy to walk, it could seem that this act is produced as easily as it is accomplished. On the contrary, locomotion requires an intricate and complex neural interaction between the supraspinal, spinal and peripheric neurons to obtain a locomotion that is smooth and adapted to the environment. The Mesencephalic Locomotor Region (MLR) is a supraspinal brainstem locomotor center that has the particular role of initiating locomotion and inducing a transition between locomotor gaits. However, although this region was initially identified as the cuneiform nucleus (CnF), a cluster of glutamatergic neurons, and the pedunculopontine nucleus (PPN), a cluster of glutamatergic and cholinergic neurons, its anatomical correlate is still a matter of debate. And while it is proven that, either under MLR stimulation or in order to increase locomotor speed, most quadrupeds exhibit a wide range of locomotor gaits from walk, to trot, to gallop, the exact range of locomotor gaits in the mouse is still unknown. Here, using kinematic analysis we first decided to identify to assess locomotor gaits C57BL/6 mice. Based on the symmetry of the gait and the inter-limb coupling, we identified and characterized 8 gaits during locomotion displayed through a continuum of locomotor frequencies, ranging from walk to trot and then to gallop with various sub-types of gaits at the slowest and highest speeds that appeared as attractors or transitional gaits. Using graph analysis, we also demonstrated that transitions between gaits were not random but entirely predictable. Then we decided to analyze and characterize the functional contributions of the CnF and PPN’s neuronal populations to locomotor control. Using transgenic mice expressing opsin in either glutamatergic (Glut) or cholinergic (CHAT) neurons, we photostimulated (or photoinhibited) glutamatergic neurons of the CnF or PPN or cholinergic neurons of the PPN. We discovered that glutamatergic CnF neurons initiate and modulate the locomotor pattern, and accelerate the rhythm, while glutamatergic and cholinergic PPN neurons decelerate it. By initiating, modulating, and accelerating locomotion, our study identifies and characterizes distinct neuronal populations of the MLR. Describing and defining thoroughly the MLR seems all the more urgent since it has recently become a target for spinal cord injury and Parkinson’s disease treatment

Examining Lower Extremity Motor Activity Using Magnetoencephalography

The role of the cortex during locomotion remains unclear, but recent advances in neural imaging technologies have aided in developing ways to measure brain activity during motor tasks. One method is by measuring activations produced by neural oscillations which have been associated with a variety of human behaviors, from sleep and rest to cognitive actions and movement. The physiological and functional methods in which oscillations contribute to cortical control are still largely unknown. In this study, we aim to expand that knowledge by examining human cortical activity in the sensory and motor cortices during pedaling using magnetoencephalography (MEG). We hypothesized that, if the sensory and motor cortices are important for controlling locomotion, then the MEG signal would differ during pedaling as compared to rest and would be modulated with the phase of the pedaling cycle. Moreover, if locomotor-related brain activity is solely caused by sensory feedback, then the MEG signal would be the same during active and passive pedaling. We scanned eight healthy subjects using MEG while they pedaled a custom-made pedaling device. The subjects’ magnetocortical activity was measured in two minute recordings during rest, continuous, self-paced active pedaling, and passive pedaling. The passive condition consisted of the subject relaxing their leg muscles while the experimenter pedaled the device for them at a velocity matching that subject’s active pedaling bout. Task-dependent magnetocortical activity was examined in the primary sensorimotor cortex (M1 and S1), supplemental motor area (SMA), and premotor area (PMA). The power spectrum of the MEG signal during the different tasks was extracted using a Welch periodogram to examine the frequency content throughout each task. The power in the alpha and beta bands of all regions of interest decreased significantly during active and passive pedaling as compared to rest. No significant difference was found between any of the tasks in the gamma band. The temporal pattern of the beta frequency band was also examined across the pedaling cycle by performing a time-frequency decomposition using a Morlet wavelet. Both pedaling conditions demonstrated modulation of the beta band at twice the pedaling frequency. These fluctuations were not found in the rest condition. Our results showed that the brain becomes engaged during pedaling as compared to rest. The magnetocortical activity is different across the movement cycle, suggesting that the brain has input into the regulation of locomotor-like movement. There is also a strong sensory component during movement since the active and passive pedaling conditions are similar