A model for self-organization of sensorimotor function: the spinal monosynaptic loop

Motor patterns of patients with spinal muscular atrophy suggestive of sensory and corticospinal contributions to the development of locomotor muscle synergies

Complex locomotor patterns are generated by combination of muscle synergies. How genetic processes, early sensorimotor experiences, and the developmental dynamics of neuronal circuits contribute to the expression of muscle synergies remains elusive. We shed light on the factors that influence development of muscle synergies by studying subjects with spinal muscular atrophy (SMA, types II/IIIa), a disorder associated with degeneration and deafferentation of motoneurons and possibly motor cortical and cerebellar abnormalities, from which the afflicted would have atypical sensorimotor histories around typical walking onset. Muscle synergies of children with SMA were identified from electromyographic signals recorded during active-assisted leg motions or walking, and compared with those of age-matched controls. We found that the earlier the SMA onset age, the more different the SMA synergies were from the normative. These alterations could not just be explained by the different degrees of uneven motoneuronal losses across muscles. The SMA-specific synergies had activations in muscles from multiple limb compartments, a finding reminiscent of the neonatal synergies of typically developing infants. Overall, while the synergies shared between SMA and control subjects may reflect components of a core modular infrastructure determined early in life, the SMA-specific synergies may be developmentally immature synergies that arise from inadequate activity-dependent interneuronal sculpting due to abnormal sensorimotor experience and other factors. Other mechanisms including SMA-induced intraspinal changes and altered cortical-spinal interactions may also contribute to synergy changes. Our interpretation highlights the roles of the sensory and descending systems to the typical and abnormal development of locomotor modules.NEW & NOTEWORTHY This is likely the first report of locomotor muscle synergies of children with spinal muscular atrophy (SMA), a subject group with atypical developmental sensorimotor experience. We found that the earlier the SMA onset age, the more the subjects' synergies deviated from those of age-matched controls. This result suggests contributions of the sensory/corticospinal activities to the typical expression of locomotor modules, and how their disruptions during a critical period of development may lead to abnormal motor modules.

The Bcm rule allows a spinal cord model to learn rhythmic movements

Currently, it is accepted that animal locomotion is controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current central pattern generator models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the Bienenstock-Cooper-Munro learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to central pattern generator models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Though our results are not in contradiction to current models, as existing neural mechanism and structures, not used in our model, can be expected to facilitate the kind of learning demonstrated here. Therefore, our model could be used to augment existing models.

Do Individuals with Spinal Cord Injury Benefit from Semi-Immersive Virtual Reality Cognitive Training? Preliminary Results from an Exploratory Study on an Underestimated Problem

A spinal cord injury (SCI) is damage to any part of the spinal cord, caused by traumatic or non-traumatic events. Clinically, SCI is associated with partial or complete loss of motor, sensory, and autonomic functions below the site of injury. However, cognitive alterations in specific domains can also occur. The aim of this study was to evaluate the effects of semi-immersive virtual reality (VR) cognitive training (using the BTS Nirvana, Italy) in promoting global functional recovery in patients with SCI. Forty-two SCI patients were included in this retrospective case-control study, and the analysis was carried out using an electronic data retrieval system. The enrolled patients were divided into two groups with the same demographic and medical characteristics: the control group (CG: 21 patients) participated in traditional therapy, whereas the experimental group (EG: 21 patients) received training using semi-immersive VR. In both groups, there were patients with A- or B-grade impairments according to the American Spinal Injury Association (ASIA) scale. Both study groups underwent the same amount of cognitive training (but using a different type of training: conventional vs. innovative), consisting of three weekly sessions for eight weeks (24 sessions in total), each session lasting approximately sixty minutes, as well as the same amount of physiotherapy. The effect of the two treatments (EG/CG) was significantly different in global cognitive functioning (MOCA: p = 0.001), mood (BDI: p = 0.006), and overall quality of life (SF12 Total: p < 0.001), especially in physical perception (SF12-Physics: p = 0.004). Our results suggest that SCI patients could benefit from cognitive training using semi-immersive VR. Indeed, the integration of cognitive exercises that require movement and provide increased feedback could allow for better motor and cognitive recovery in people with SCI.

Biological networks and complexity in early-onset motor neuron diseases

Motor neuron diseases (MNDs) are neuromuscular disorders where the spinal motor neurons-either the cell bodies themselves or their axons-are the primary cells affected. To date, there are 120 different genes that are lost or mutated in pediatric-onset MNDs. Most of these childhood-onset disorders, aside from spinal muscular atrophy (SMA), lack viable therapeutic options. Previous research on MNDs has focused on understanding the pathobiology of a single, specific gene mutation and targeting therapies to that pathobiology. This reductionist approach has yielded therapeutic options for a specific disorder, in this case SMA. Unfortunately, therapies specific for SMA have not been effective against other pediatric-onset MNDs. Pursuing the same approach for the other defined MNDs would require development of at least 120 independent treatments raising feasibility issues. We propose an alternative to this this type of reductionist approach by conceptualizing MNDs in a complex adaptive systems framework that will allow identification of common molecular and cellular pathways which form biological networks that are adversely affected in early-onset MNDs and thus MNDs with similar phenotypes despite diverse genotypes. This systems biology approach highlights the complexity and self-organization of the motor system as well as the ways in which it can be affected by these genetic disorders. Using this integrated approach to understand early-onset MNDs, we would be better poised to expand the therapeutic repertoire for multiple MNDs.

Developing Intelligent Robots that Grasp Affordance

Humans and robots operating in unstructured environments both need to classify objects through haptic exploration and use them in various tasks, but currently they differ greatly in their strategies for acquiring such capabilities. This review explores nascent technologies that promise more convergence. A novel form of artificial intelligence classifies objects according to sensory percepts during active exploration and decides on efficient sequences of exploratory actions to identify objects. Representing objects according to the collective experience of manipulating them provides a substrate for discovering causality and affordances. Such concepts that generalize beyond explicit training experiences are an important aspect of human intelligence that has eluded robots. For robots to acquire such knowledge, they will need an extended period of active exploration and manipulation similar to that employed by infants. The efficacy, efficiency and safety of such behaviors depends on achieving smooth transitions between movements that change quickly from exploratory to executive to reflexive. Animals achieve such smoothness by using a hierarchical control scheme that is fundamentally different from those of conventional robotics. The lowest level of that hierarchy, the spinal cord, starts to self-organize during spontaneous movements in the fetus. This allows its connectivity to reflect the mechanics of the musculoskeletal plant, a bio-inspired process that could be used to adapt spinal-like middleware for robots. Implementation of these extended and essential stages of fetal and infant development is impractical, however, for mechatronic hardware that does not heal and replace itself like biological tissues. Instead such development can now be accomplished in silico and then cloned into physical robots, a strategy that could transcend human performance.

Whole Body Coordination for Self-Assistance in Locomotion

The dynamics of the human body can be described by the accelerations and masses of the different body parts (e.g., legs, arm, trunk). These body parts can exhibit specific coordination patterns with each other. In human walking, we found that the swing leg cooperates with the upper body and the stance leg in different ways (e.g., in-phase and out-of-phase in vertical and horizontal directions, respectively). Such patterns of self-assistance found in human locomotion could be of advantage in robotics design, in the design of any assistive device for patients with movement impairments. It can also shed light on several unexplained infrastructural features of the CNS motor control. Self-assistance means that distributed parts of the body contribute to an overlay of functions that are required to solve the underlying motor task. To draw advantage of self-assisting effects, precise and balanced spatiotemporal patterns of muscle activation are necessary. We show that the necessary neural connectivity infrastructure to achieve such muscle control exists in abundance in the spinocerebellar circuitry. We discuss how these connectivity patterns of the spinal interneurons appear to be present already perinatally but also likely are learned. We also discuss the importance of these insights into whole body locomotion for the successful design of future assistive devices and the sense of control that they could ideally confer to the user.

A Model for Self-Organization of Sensorimotor Function: Spinal Interneuronal Integration

Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. Particular connectivity patterns have been identified experimentally, and it has been suggested that these may result from the wide variety of transcriptional types that have been observed in spinal interneurons. We ask instead whether the details of these connectivity patterns (and perhaps many others) can arise as a consequence of Hebbian adaptation during early development. We constructed an anatomically simplified model plant system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both excitatory and inhibitory neurons endowed with Hebbian learning rules. We then generated a wide set of randomized muscle twitches typical of those described during fetal development and allowed the network to learn. Multiple simulations consistently resulted in diverse and stable patterns of activity and connectivity that included subsets of the interneurons that were similar to 'archetypical' interneurons described in the literature. We also found that such learning led to an increased degree of cooperativity between interneurons when performing larger limb movements on which it had not been trained. Hebbian learning gives rise to rich sets of diverse interneurons whose connectivity reflects the mechanical properties of the plant. At least some of the transcriptomic diversity may reflect the effects of this process rather than the cause of the connectivity. Such a learning process seems better suited to respond to the musculoskeletal mutations that underlie the evolution of new species.

Body Representation in Patients with Severe Spinal Cord Injury: A Pilot Study on the Promising Role of Powered Exoskeleton for Gait Training

Patients with spinal cord injury (SCI) complain of changes in body representation, potentially leading to negative physical and psychological consequences. The purpose of our study is to evaluate the effects of robotic training with the Ekso-GT on body representation (BR) and on the quality of life in patients with SCI. The trial was designed as a pilot, assessor-blinded study. Forty-two inpatients with a diagnosis of SCI, classified as either American Spinal Cord Injury Association Impairment Scale (AIS), were enrolled in this study and randomized into either a control (CG: n = 21) or an experimental (EG: n = 21) group. Patients in the EG received rehabilitation training with the Ekso-GT device, whereas the CG patients were trained with conventional physical therapy (CPT), which consisted of physical and occupational therapy and psychological support. We considered as a primary outcome the modified Body Uneasiness Test (MBUT), focusing on three specific subscales on the patient’s perception of BR, i.e., the Global Severity Index (MBUT-GSI), which is an indicator of body suffering; the Positive Symptom Distress Index (MBUT-PSDI) that expresses an individual’s psychological distress; and the Lower Limb MBUT (MBUT-LL), which indicates the subject’s perception of their thighs/legs. The Short-Form-12 Health Status Questionnaire (SF12) and the Beck’s Depression Inventory (BDI) were used as secondary outcomes to evaluate the effect of the training on the quality of life and the psychological status. Non-parametric statistical analysis showed that the effect of the two treatments was significantly different on MBUT (BR), SF-12 (quality of life), and, partially, BDI (mood). Particularly, patients belonging to the EG achieved a major improvement in nearly all test scores compared to those in the CG. Our data suggest that the Ekso-GT training could be helpful in achieving positive changes in BR in patients with chronic SCI, especially in reducing psychological distress (PSDI) and thigh/leg perception (MBUT-LL) with an overall improvement in quality of life (SF-12).