Interneuron diversity and function in the spinal motor system

The organization of spinal neurons: Insights from single cell sequencing

To understand how the spinal cord enacts complex sensorimotor functions, researchers have studied, classified, and functionally probed it's many neuronal populations for over a century. Recent developments in single-cell RNA-sequencing can characterize the gene expression signatures of the entire set of spinal neuron types and can simultaneously provide an unbiased view of their relationships to each other. This approach has revealed that the location of neurons predicts transcriptomic variability, as dorsal spinal neurons become highly distinct over development as ventral spinal neurons become less so. Temporal specification is also a major source of gene expression variation, subdividing many of the canonical embryonic lineage domains. Together, birthdate and cell body location are fundamental organizing features of spinal neuron diversity.

Engineered human spinal cord-like tissues with dorsal and ventral neuronal progenitors for spinal cord injury repair in rats and monkeys

Transplanting human neural progenitor cells is a promising method of replenishing the lost neurons after spinal cord injury (SCI), but differentiating neural progenitor cells into the diverse types of mature functional spinal cord neurons in vivo is challenging. In this study, engineered human embryonic spinal cord-like tissues with dorsal and ventral neuronal characters (DV-SC) were generated by inducing human neural progenitor cells (hscNPCs) to differentiate into various types of dorsal and ventral neuronal cells on collagen scaffold in vitro. Transplantation of DV-SC into complete SCI models in rats and monkeys showed better therapeutic effects than undifferentiated hscNPCs, including pronounced cell survival and maturation. DV-SC formed a targeted connection with the host's ascending and descending axons, partially restored interrupted neural circuits, and improved motor evoked potentials and the hindlimb function of animals with SCI. This suggests that the transplantation of pre-differentiated hscNPCs with spinal cord dorsal and ventral neuronal characteristics could be a promising strategy for SCI repair.

A review of motor neural system robotic modeling approaches and instruments

In this review, we are considering an actively developing tool in neuroscience-robotic modeling. The new perspective and existing application fields, tools, and methods are discussed. We try to determine starting positions and approaches that are useful at the beginning of new research in this field. Among multiple directions of the research is robotic modeling on the level of muscles fibers and their afferents, skin surface sensors, muscles, and joints proprioceptors. Some examples of technical implementation for physical modeling are reviewed. They are software and hardware tools like event-related modeling algorithms, reduced neuron models, robotic drives constructions. We observe existing drives technologies and prospective electric motor types: switched reluctance and transverse flux motors. Next, we look at the existing examples and approaches for robotic modeling of the cerebellum and spinal cord neural networks. These examples show practical methods for the model neural network architecture and adaptation. Those methods allow the use of cortical and spinal cord reflexes for the network training and apply additional artificial blocks for data processing in other brain structures that transmit and receive data from biologically realistic models.

Ipsilateral and Contralateral Interactions in Spinal Locomotor Circuits Mediated by V1 Neurons: Insights from Computational Modeling

We describe and analyze a computational model of neural circuits in the mammalian spinal cord responsible for generating and shaping locomotor-like oscillations. The model represents interacting populations of spinal neurons, including the neurons that were genetically identified and characterized in a series of previous experimental studies. Here, we specifically focus on the ipsilaterally projecting V1 interneurons, their possible role in the spinal locomotor circuitry, and their involvement in the generation of locomotor oscillations. The proposed connections of these neurons and their involvement in different neuronal pathways in the spinal cord allow the model to reproduce the results of optogenetic manipulations of these neurons under different experimental conditions. We suggest the existence of two distinct populations of V1 interneurons mediating different ipsilateral and contralateral interactions within the spinal cord. The model proposes explanations for multiple experimental data concerning the effects of optogenetic silencing and activation of V1 interneurons on the frequency of locomotor oscillations in the intact cord and hemicord under different experimental conditions. Our simulations provide an important insight into the organization of locomotor circuitry in the mammalian spinal cord.

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.

Diversified physiological sensory input connectivity questions the existence of distinct classes of spinal interneurons

The spinal cord is engaged in all forms of motor performance but its functions are far from understood. Because network connectivity defines function, we explored the connectivity of muscular, tendon, and tactile sensory inputs among a wide population of spinal interneurons in the lower cervical segments. Using low noise intracellular whole cell recordings in the decerebrated, non-anesthetized cat in vivo, we could define mono-, di-, and trisynaptic inputs as well as the weights of each input. Whereas each neuron had a highly specific input, and each indirect input could moreover be explained by inputs in other recorded neurons, we unexpectedly also found the input connectivity of the spinal interneuron population to form a continuum. Our data hence contrasts with the currently widespread notion of distinct classes of interneurons. We argue that this suggested diversified physiological connectivity, which likely requires a major component of circuitry learning, implies a more flexible functionality.

A new biological central pattern generator model and its relationship with the motor units

The central pattern generator (CPG) is a key neural-circuit component of the locomotion control system. Recently, numerous molecular and genetic approaches have been proposed for investigating the CPG mechanisms. The rhythm in the CPG locomotor circuits comes from the activity in the ipsilateral excitatory neurons whose output is controlled by inter-neuron inhibitory connections. Conventional models for simulating the CPG mechanism are complex Hodgkin-Huxley-type models. Inspired by biological investigations and the continuous-time Matsuoka model, we propose new integral-order and fractional-order CPG models, which consider time delays and synaptic interfaces. The phase diagrams exhibit limit cycles and periodic solutions, in agreement with the CPG biological characteristics. As well, the fractional-order model shows state transitions with order variations. In addition, we investigate the relationship between the CPG and the motor units through the construction of integral-order and fractional-order coupling models. Simulations of these coupling models show that the states generated by the three motor units are in accordance with the experimentally-obtained states in previous studies. The proposed models reveal that the CPG can regulate limb locomotion patterns through connection weights and synaptic interfaces. Moreover, in comparison to the integral-order models, the fractional-order ones appear to be more effective, and hence more suitable for describing the dynamics of the CPG biological system.

The Temporal Mechanisms Guiding Interneuron Differentiation in the Spinal Cord

Neurogenesis timing is an essential developmental mechanism for neuronal diversity and organization throughout the central nervous system. In the mouse spinal cord, growing evidence is beginning to reveal that neurogenesis timing acts in tandem with spatial molecular controls to diversify molecularly and functionally distinct post-mitotic interneuron subpopulations. Particularly, in some cases, this temporal ordering of interneuron differentiation has been shown to instruct specific sensorimotor circuit wirings. In zebrafish, in vivo preparations have revealed that sequential neurogenesis waves of interneurons and motor neurons form speed-dependent locomotor circuits throughout the spinal cord and brainstem. In the present review, we discuss temporal principals of interneuron diversity taken from both mouse and zebrafish systems highlighting how each can lend illuminating insights to the other. Moving forward, it is important to combine the collective knowledge from different systems to eventually understand how temporally regulated subpopulation function differentially across speed- and/or state-dependent sensorimotor movement tasks.

The Effects of Mechanical Scale on Neural Control and the Regulation of Joint Stability

Recent work has demonstrated how the size of an animal can affect neural control strategies, showing that passive viscoelastic limb properties have a significant role in determining limb movements in small animals but are less important in large animals. We extend that work to consider effects of mechanical scaling on the maintenance of joint integrity; i.e., the prevention of aberrant contact forces within joints that might lead to joint dislocation or cartilage degradation. We first performed a literature review to evaluate how properties of ligaments responsible for joint integrity scale with animal size. Although we found that the cross-sectional area of the anterior cruciate ligament generally scaled with animal size, as expected, the effects of scale on the ligament’s mechanical properties were less clear, suggesting potential adaptations in passive contributions to the maintenance of joint integrity across species. We then analyzed how the neural control of joint stability is altered by body scale. We show how neural control strategies change across mechanical scales, how this scaling is affected by passive muscle properties and the cost function used to specify muscle activations, and the consequences of scaling on internal joint contact forces. This work provides insights into how scale affects the regulation of joint integrity by both passive and active processes and provides directions for studies examining how this regulation might be accomplished by neural systems.

Development of motor circuits: From neuronal stem cells and neuronal diversity to motor circuit assembly

In this review, we discuss motor circuit assembly starting from neuronal stem cells. Until recently, studies of neuronal stem cells focused on how a relatively small pool of stem cells could give rise to a large diversity of different neuronal identities. Historically, neuronal identity has been assayed in embryos by gene expression, gross anatomical features, neurotransmitter expression, and physiological properties. However, these definitions of identity are largely unlinked to mature functional neuronal features relevant to motor circuits. Such mature neuronal features include presynaptic and postsynaptic partnerships, dendrite morphologies, as well as neuronal firing patterns and roles in behavior. This review focuses on recent work that links the specification of neuronal molecular identity in neuronal stem cells to mature, circuit-relevant identity specification. Specifically, these studies begin to address the question: to what extent are the decisions that occur during motor circuit assembly controlled by the same genetic information that generates diverse embryonic neuronal diversity? Much of the research addressing this question has been conducted using the Drosophila larval motor system. Here, we focus largely on Drosophila motor circuits and we point out parallels to other systems. And we highlight outstanding questions in the field. The main concepts addressed in this review are: (1) the description of temporal cohorts-novel units of developmental organization that link neuronal stem cell lineages to motor circuit configuration and (2) the discovery that temporal transcription factors expressed in neuronal stem cells control aspects of circuit assembly by controlling the size of temporal cohorts and influencing synaptic partner choice.

Exciting Complexity: The Role of Motor Circuit Elements in ALS Pathophysiology

Amyotrophic lateral sclerosis (ALS) is a fatal disease, characterized by the degeneration of both upper and lower motor neurons. Despite decades of research, we still to date lack a cure or disease modifying treatment, emphasizing the need for a much-improved insight into disease mechanisms and cell type vulnerability. Altered neuronal excitability is a common phenomenon reported in ALS patients, as well as in animal models of the disease, but the cellular and circuit processes involved, as well as the causal relevance of those observations to molecular alterations and final cell death, remain poorly understood. Here, we review evidence from clinical studies, cell type-specific electrophysiology, genetic manipulations and molecular characterizations in animal models and culture experiments, which argue for a causal involvement of complex alterations of structure, function and connectivity of different neuronal subtypes within the cortical and spinal cord motor circuitries. We also summarize the current knowledge regarding the detrimental role of astrocytes and reassess the frequently proposed hypothesis of glutamate-mediated excitotoxicity with respect to changes in neuronal excitability. Together, these findings suggest multifaceted cell type-, brain area- and disease stage- specific disturbances of the excitation/inhibition balance as a cardinal aspect of ALS pathophysiology.

Mapping Connectivity Amongst Interneuronal Components of the Locomotor CPG

The basic rhythmic activity characteristic of locomotion in mammals is generated by a neural network, located in the spinal cord, known as the locomotor central pattern generator (CPG). Although a great deal of effort has gone into the study of this neural circuit over the past century, identification and characterization of its component interneurons has proven to be challenging, largely due to their location and distribution. Recent work incorporating a molecular approach has provided a great deal of insight into the genetic identity of interneurons that make up this neural circuit, as well as the specific roles that they play during stepping. Despite this progress we still know relatively little regarding the manner in which these neuronal populations are interconnected. In this article we review the interneuronal populations shown to be involved in locomotor activity, briefly summarize their specific function, and focus on experimental work that provides insight into their synaptic connectivity. Finally, we discuss how recently developed viral approaches can potentially be incorporated to provide further insight into the network structure of this neural circuit.