Swimming kinematics and performance of spinal transected lampreys with different levels of axon regeneration

Using deep reinforcement learning to investigate stretch feedback during swimming of the lamprey

Animals have to navigate complex environments and perform intricate swimming maneuvers in the real world. To conquer these challenges, animals evolved a variety of motion control strategies. While it is known that many factors contribute to motion control, we specifically focus on the role of stretch sensory feedback. We investigate how stretch feedback potentially serves as a way to coordinate locomotion, and how different stretch feedback topologies, such as networks spanning varying ranges along the spinal cord, impact the locomotion. We conduct our studies on a simulated robot model of the lamprey consisting of an articulated spine with eleven segments connected by actuated joints. The stretch feedback is modeled with neural networks trained with deep reinforcement learning. We find that the topology of the feedback influences the energy efficiency and smoothness of the swimming, along with various other metrics characterizing the locomotion, such as frequency, amplitude and stride length. By analyzing the learned feedback networks, we highlight the importances of very local, caudally-directed, as well as stretch derivative information. Our results deliver valuable insights into the potential mechanisms and benefits of stretch feedback control and inspire novel decentralized control strategies for complex robots.

Empirical Data-Driven Linear Model of a Swimming Robot Using the Complex Delay-Embedding DMD Technique

Anguilliform locomotion, an efficient aquatic locomotion mode where the whole body is engaged in fluid-body interaction, contains sophisticated physics. We hypothesized that data-driven modeling techniques may extract models or patterns of the swimmers' dynamics without implicitly measuring the hydrodynamic variables. This work proposes empirical kinematic control and data-driven modeling of a soft swimming robot. The robot comprises six serially connected segments that can individually bend with the segmental pneumatic artificial muscles. Kinematic equations and relations are proposed to measure the desired actuation to mimic anguilliform locomotion kinematics. The robot was tested experimentally and the position and velocities of spatially digitized points were collected using QualiSys® Tracking Manager (QTM) 1.6.0.1. The collected data were analyzed offline, proposing a new complex variable delay-embedding dynamic mode decomposition (CDE DMD) algorithm that combines complex state filtering and time embedding to extract a linear approximate model. While the experimental results exhibited exotic curves in phase plane and time series, the analysis results showed that the proposed algorithm extracts linear and chaotic modes contributing to the data. It is concluded that the robot dynamics can be described by the linearized model interrupted by chaotic modes. The technique successfully extracts coherent modes from limited measurements and linearizes the system dynamics.

Spontaneous regeneration of cholecystokinergic reticulospinal axons after a complete spinal cord injury in sea lampreys

In contrast to humans, lampreys spontaneously recover their swimming capacity after a complete spinal cord injury (SCI). This recovery process involves the regeneration of descending axons. Spontaneous axon regeneration in lampreys has been mainly studied in giant descending neurons. However, the regeneration of neurochemically distinct descending neuronal populations with small-caliber axons, as those found in mammals, has been less studied. Cholecystokinin (CCK) is a regulatory neuropeptide found in the brain and spinal cord that modulates several processes such as satiety, or locomotion. CCK shows high evolutionary conservation and is present in all vertebrate species. Work in lampreys has shown that all CCKergic spinal cord axons originate in a single neuronal population located in the caudal rhombencephalon. Here, we investigate the spontaneous regeneration of CCKergic descending axons in larval lampreys following a complete SCI. Using anti-CCK-8 immunofluorescence, confocal microscopy and lightning adaptive deconvolution, we demonstrate the partial regeneration of CCKergic axons (81% of the number of axonal profiles seen in controls) 10 weeks after the injury. Our data also revealed a preference for regeneration of CCKergic axons in lateral spinal cord regions. Regenerated CCKergic axons exhibit colocalization with synaptic vesicle marker SV2, indicative of functional synaptic connections. We also extracted swimming dynamics in injured animals by using DeepLabCut. Interestingly, the degree of CCKergic reinnervation correlated with improved swimming performance in injured animals, suggesting a potential role in locomotor recovery. These findings open avenues for further exploration into the role of specific neuropeptidergic systems in post-SCI spinal locomotor networks.

Mechanosensory Feedback in Lamprey Swimming Models and Applications in the Field of Spinal Cord Regeneration

The central pattern generator (CPG) in anguilliform swimming has served as a model for examining the neural basis of locomotion. This system has been particularly valuable for the development of mathematical models. As our biological understanding of the neural basis of locomotion has expanded, so too have these models. Recently, there have been significant advancements in our understanding of the critical role that mechanosensory feedback plays in robust locomotion. This work has led to a push in the field of mathematical modeling to incorporate mechanosensory feedback into CPG models. In this perspective piece, we review advances in the development of these models and discuss how newer complex models can support biological investigation. We highlight lamprey spinal cord regeneration as an area that can both inform these models and benefit from them.

Full regeneration of descending corticotropin-releasing hormone axons after a complete spinal cord injury in lampreys

Sea lampreys are a vertebrate model of interest for the study of spontaneous axon regeneration after spinal cord injury (SCI). Axon regeneration research in lampreys has focused on the study of giant descending neurons, but less so on neurochemically-distinct descending neuronal populations with small caliber axons. Corticotropin-releasing hormone (CRH) is a neuropeptide that regulates the stress response or locomotion. CRH is also a neuropeptide of interest in the SCI context because descending CRHergic projections from the Barrington's nucleus control micturition behavior in mammals. Recent work from our group revealed that in sea lampreys the CRHergic innervation of the spinal cord is only of descending origin. Thus, the lack of intrinsic CRH spinal cord neurons provides the opportunity to analyze the regeneration of this descending system by using immunofluorescence methods. Here, we used an antibody against the sea lamprey mature CRH peptide, confocal microscopy, lightning adaptive deconvolution, and ImageJ to analyze the regenerative capacity of the descending CRH-immunoreactive (-ir) axons of larval sea lampreys after a complete SCI at the level of the fifth gill. At 10 weeks post-lesion, when behavioral analyses showed that injured animals had recovered normal appearing locomotion, our results revealed a full recovery of the number of CRH-ir profiles (axons) at the level of the sixth gill. Thus, the CRH descending axons of lampreys fully regenerate after a complete SCI. Our study provides a new model to study spontaneous and successful axonal regeneration in a specific neuronal type with small caliber axons by using simple immunohistochemical methods.