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1. Operation regimes of spinal circuits controlling locomotion and the role of supraspinal drives and sensory feedback

   https://doi.org/10.7554/eLife.98841  

   Rybak, Ilya A; Shevtsova, Natalia A; Markin, Sergey N; Prilutsky, Boris I; Frigon, Alain (October 2024, eLife)

   Smith, Jeffrey C (Ed.)

   Locomotion in mammals is directly controlled by the spinal neuronal network, operating under the control of supraspinal signals and somatosensory feedback that interact with each other. However, the functional architecture of the spinal locomotor network, its operation regimes, and the role of supraspinal and sensory feedback in different locomotor behaviors, including at different speeds, remain unclear. We developed a computational model of spinal locomotor circuits receiving supraspinal drives and limb sensory feedback that could reproduce multiple experimental data obtained in intact and spinal-transected cats during tied-belt and split-belt treadmill locomotion. We provide evidence that the spinal locomotor network operates in different regimes depending on locomotor speed. In an intact system, at slow speeds (<0.4 m/s), the spinal network operates in a non-oscillating state-machine regime and requires sensory feedback or external inputs for phase transitions. Removing sensory feedback related to limb extension prevents locomotor oscillations at slow speeds. With increasing speed and supraspinal drives, the spinal network switches to a flexor-driven oscillatory regime and then to a classical half-center regime. Following spinal transection, the model predicts that the spinal network can only operate in the state-machine regime. Our results suggest that the spinal network operates in different regimes for slow exploratory and fast escape locomotor behaviors, making use of different control mechanisms. 

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2. Contribution of Afferent Feedback to Adaptive Hindlimb Walking in Cats: A Neuromusculoskeletal Modeling Study

   https://doi.org/10.3389/fbioe.2022.825149  

   Kim, Yongi; Aoi, Shinya; Fujiki, Soichiro; Danner, Simon M.; Markin, Sergey N.; Ausborn, Jessica; Rybak, Ilya A.; Yanagihara, Dai; Senda, Kei; Tsuchiya, Kazuo (April 2022, Frontiers in Bioengineering and Biotechnology)

   Mammalian locomotion is generated by central pattern generators (CPGs) in the spinal cord, which produce alternating flexor and extensor activities controlling the locomotor movements of each limb. Afferent feedback signals from the limbs are integrated by the CPGs to provide adaptive control of locomotion. Responses of CPG-generated neural activity to afferent feedback stimulation have been previously studied during fictive locomotion in immobilized cats. Yet, locomotion in awake, behaving animals involves dynamic interactions between central neuronal circuits, afferent feedback, musculoskeletal system, and environment. To study these complex interactions, we developed a model simulating interactions between a half-center CPG and the musculoskeletal system of a cat hindlimb. Then, we analyzed the role of afferent feedback in the locomotor adaptation from a dynamic viewpoint using the methods of dynamical systems theory and nullcline analysis. Our model reproduced limb movements during regular cat walking as well as adaptive changes of these movements when the foot steps into a hole. The model generates important insights into the mechanism for adaptive locomotion resulting from dynamic interactions between the CPG-based neural circuits, the musculoskeletal system, and the environment. 

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3. Control of mammalian locomotion by somatosensory feedback

   https://doi.org/10.1002/cphy.c210020  

   Frigon, A; Akay, T; Prilutsky, Boris I. (December 2021, Comprehensive physiology)

   When animals walk overground, mechanical stimuli activate various receptors located in muscles, joints, and skin. Afferents from these mechanoreceptors project to neuronal networks controlling locomotion in the spinal cord and brain. The dynamic interactions between the control systems at different levels of the neuraxis ensure that locomotion adjusts to its environment and meets task demands. In this article, we describe and discuss the essential contribution of somatosensory feedback to locomotion. We start with a discussion of how biomechanical properties of the body affect somatosensory feedback. We follow with the different types of mechanoreceptors and somatosensory afferents and their activity during locomotion. We then describe central projections to locomotor networks and the modulation of somatosensory feedback during locomotion and its mechanisms. We then discuss experimental approaches and animal models used to investigate the control of locomotion by somatosensory feedback before providing an overview of the different functional roles of somatosensory feedback for locomotion. Lastly, we briefly describe the role of somatosensory feedback in the recovery of locomotion after neurological injury. We highlight the fact that somatosensory feedback is an essential component of a highly integrated system for locomotor control. 

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4. Effect of spinal cord injury on neural encoding of spontaneous postural perturbations in the hindlimb sensorimotor cortex

   Jaimie B Dougherty (January 2021, Journal of neurophysiology)

   Capers, Miriam (Ed.)

   Supraspinal signals play a significant role in compensatory responses to postural perturbations after spinal cord injury (SCI). SCI disrupts descending motor control signals as well as ascending somatosensory information to and from below the lesion. In intact animals, While cortical signals are not necessary for basic postural tasks, but neurons in the motor cortex have been shown to respond to periodic postural perturbations in intact animals. However, the role of the cortex in postural control after spinal cord injury in response to unexpected postural perturbations has not been studied. To better understand how spinal lesions impact cortical encoding of information about unexpected postural perturbations, the activity of single neurons in the rat hindlimb sensorimotor cortex (HLSMC) were recorded during unexpected tilts before and after a complete midthoracic spinal transection. In a subset of animals, limb ground reaction forces were collected as well. Results show that responses in the HLSMC were modulated with changes in tilt severity (i.e. tilt velocity). As initial velocity of the tilt increased, more information was conveyed by the HLSMC neurons about the perturbation due to increases in both the number of recruited neurons and the magnitude of their response. After SCI hindlimb ground reaction forces were both attenuated and delayed, and the neural responses were delayed and less likely to respond to slower tilts. This resulted in a moderate decrease inan attenuation of the information conveyed by cortical neurons about the tilts, requiring more cells to convey the same amount of information as before the transection. Given that reorganization of the hindlimb sensorimotor cortex in response to therapy after complete mid-thoracic SCI is necessary for behavioral recovery, this sustained encoding of information after SCI could be a substrate for the reorganization that uses sensory information from above the lesion to control trunk muscles that permit weight-supported stepping and postural control. 

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5. Computational Modeling of Spinal Locomotor Circuitry in the Age of Molecular Genetics

   https://doi.org/10.3390/ijms22136835  

   Ausborn, Jessica; Shevtsova, Natalia A.; Danner, Simon M. (July 2021, International Journal of Molecular Sciences)

   Neuronal circuits in the spinal cord are essential for the control of locomotion. They integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. For several decades, computational modeling has complemented experimental studies by providing a mechanistic rationale for experimental observations and by deriving experimentally testable predictions. This symbiotic relationship between experimental and computational approaches has resulted in numerous fundamental insights. With recent advances in molecular and genetic methods, it has become possible to manipulate specific constituent elements of the spinal circuitry and relate them to locomotor behavior. This has led to computational modeling studies investigating mechanisms at the level of genetically defined neuronal populations and their interactions. We review literature on the spinal locomotor circuitry from a computational perspective. By reviewing examples leading up to and in the age of molecular genetics, we demonstrate the importance of computational modeling and its interactions with experiments. Moving forward, neuromechanical models with neuronal circuitry modeled at the level of genetically defined neuronal populations will be required to further unravel the mechanisms by which neuronal interactions lead to locomotor behavior. 

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