The overall goal of this work was to create a high-resolution MRI atlas of the lumbosacral enlargement of the spinal cord of the rat (Sprague–Dawley), cat, domestic pig, rhesus monkey, and human. These species were chosen because they are commonly used in basic and translational research in spinal cord injuries and diseases. Six spinal cord specimens from each of the studied species (total of 30 specimens) were fixed, extracted, and imaged. Sizes of the spinal cord segments, cross-sectional dimensions, and locations of the spinal cord gray and white matter were quantified and compared across species. The lumbar enlargement spans spinal cord levels L3-S1 in rats, L4-S1 in cats, L3-S1 in pigs, L2/L3-L7/S1 in monkeys, and T12/L1-S1/S2 in humans. The enlargements in pigs and humans are largest and most similar in size (length and cross-sectional area); followed by monkeys and cats; and followed by rats. The obtained atlas establishes a neuroanatomical reference for the intact lumbosacral spinal cord in these species. It can also be used to guide the planning of surgical procedures of the spinal cord and technology design and development of spinal cord neuroprostheses, as well as precise delivery of cells/drugs into target regions within the spinal cord parenchyma.

In this survey, various concepts and methodologies developed over the past two decades for varying and learning the impedance or admittance of robotic systems that physically interact with humans are explored. For this purpose, the assumptions and mathematical formulations for the online adjustment of impedance models and controllers for physical human–robot interaction (HRI) are categorized and compared. In this systematic review, studies on: 1) variation and 2) learning of appropriate impedance elements are taken into account. These strategies are classified and described in terms of their objectives, points of view (approaches), and signal requirements (including position, HRI force, and electromyography activity). Different methods involving linear/nonlinear analyses (e.g., optimal control design and nonlinear Lyapunov-based stability guarantee) and the Gaussian approximation algorithms (e.g., Gaussian mixture model-based and dynamic movement primitives-based strategies) are reviewed. Current challenges and research trends in physical HRI are finally discussed.

Intraspinal microstimulation (ISMS) may provide a means for improving motor function in people suffering from spinal cord injuries, head trauma, or stroke. The goal of this study was to determine whether microstimulation of the mammalian spinal cord could generate locomotor-like stepping and feedback-controlled movements of the hindlimbs. Under pentobarbital anesthesia, 24 insulated microwires were implanted in the lumbosacral cord of three adult cats. The cats were placed in a sling leaving all limbs pendent. Bilateral alternating stepping of the hindlimbs was achieved by stimulating through as few as two electrodes in each side of the spinal cord. Typical stride lengths were 23.5 cm, and ample foot clearance was achieved during swing. Mean ground reaction force during stance was 36.4 N, sufficient for load-bearing. Feedback-controlled movements of the cat's foot were achieved by reciprocally modulating the amplitude of stimuli delivered through two intraspinal electrodes generating ankle flexion and extension such that the distance between a sensor on the cat's foot and a free sensor moved back and forth by the investigators was minimized.. The foot tracked the displacements of the target sensor through its normal range of motion. Stimulation through electrodes with tips in or near lamina IX elicited movements most suitable for locomotion. In chronically implanted awake cats, stimulation through dorsally located electrodes generated paw shakes and flexion-withdrawals consistent with sensory perception but no weight-bearing extensor movements. These locations would not be suitable for ISMS in incomplete spinal cord injuries. Despite the complexity of the spinal neuronal networks, our results demonstrate that by stimulating through a few intraspinal microwires, near-normal bipedal locomotor-like stepping and feedback-controlled movements could be achieved.

In this article, a new learning-based time-varying impedance controller is proposed and tested to facilitate an autonomous physical human–robot interaction (pHRI). Novel adaptation laws are formulated for online adjustment of robot impedance based on human behavior. Two other sets of update rules are defined for intelligent coping with the robot’s structured and unstructured uncertainties. These rules ensure stability via Lyapunov’s theorem and provide uniform ultimate boundedness (UUB) of the closed-loop system’s response, without a need for HRI force/torque measurement. Accordingly, the convergence of response signals, including errors in tracking, online impedance learning, robot parameter adaptation, and controller gain variation, is proven to operate in a bounded region (compact set) in the presence of robot and human uncertainties and bounded disturbances. The performance of the developed intelligent impedance-varying control strategy is investigated through comprehensive experimental studies in a repetitive following task with a moving target.

We used computer simulations to study the dendritic spatial distribution of low voltage-activated L-type calcium (Ca_V1.3 type) channels, which mediate hysteretic persistent inward current (PIC) in spinal motoneurons. This study was prompted by the growing experimental evidence of the functional interactions between synaptic inputs and active conductances over the motoneuron dendritic tree. A compartmental cable model of an adult cat α-motoneuron was developed in NEURON simulation environment constituting the detailed morphology of type-identified triceps surae α-motoneuron and realistic distribution of group Ia afferent-to-motoneuron contacts. Simulations of different distributions of Ca_V1.3 channels were conducted and the resultant behavior was compared to experimental data. Our results suggest that Ca_V1.3 channels do not uniformly cover the whole motoneuron dendritic tree. Instead, their distribution is similar to that of synaptic contacts. We found that Ca_V1.3 channels are primarily localized to a wide intermediate band overlapping with the dendritic Ia-synaptic territory at dendritic distances of 300 to 850 μm (0.62 ± 0.21λ) from the soma in triceps surae α-motoneurons. These findings explain the functional interaction between synaptic inputs and the Ca_V1.3 channels over the motoneuron dendritic tree.