Assessment of functional recovery in animal models of PNI and SCI remains challenging due to the great variety of evaluation methods, each with individual advantages and disadvantages. Only few approaches have been tested and validated in multiple models of peripheral and central nervous injuries, although promising new techniques which combine motion tracking and machine learning might potentially propel neurobehavioral research to the next level of functional testing. We are convinced that cutting-edge methods broadly applicable to a wide variety of animal and injury models will soon emerge. In the light of these considerations, one of the advantages of AGA is the possibility to evaluate functional recovery in multiple models of nerve injury using only one device. Since the early 2000s this approach has been used in experimental models of PNI such as the sciatic37, peroneal38, and femoral nerve injury model22 as well as after root avulsion of both the lumbar39 and the brachial plexus40. Various central nervous injuries including spinal cord contusion injury have also been studied with the method41,42. With this paper, we presented a detailed protocol on how to induce three commonly studied nerve injuries as well as how to evaluate functional recovery afterwards. In our opinion, a hands-on-guideline for researchers interested in the area of experimental nerve injury, repair, and regeneration on how to make optimum use of the method’s advantageous features would be of great help.
Several authors have addressed the potential of AGA to evaluate functional recovery in rodents, highlighting the method’s advantage to simultaneously assess gait parameters related to motor and sensory reinnervation27,28. Additionally, comparison of data from an experimental paw, e.g., reconstructed nerve injury to an unoperated paw as was shown in both of the models presented allows inclusion of an intra-animal positive control. Inversely, an operated paw without surgical reconstruction or additional treatment could serve as an intra-animal negative control. It was also shown that it is possible to combine AGA with machine learning approaches43. In spite of the method’s advantages, it also has several limitations and drawbacks, such as the time-consuming training efforts, which are mandatory to accustom the animal to the acquisition procedure28,44. Another limitation of AGA is the maximum size of the animals eligible for testing due to the limited dimensions of the apparatus. Therefore, the use of AGA is currently limited to animals the size of rodents and ferrets45. Additionally, recently emerging neurobehavioral assessment approaches in the field of motion tracking capable of machine-learning may surpass AGA in both comprehensiveness as well as possible applications18,19,46. Most noteworthy, but in accordance with other evaluation methods, it seems that functional recovery as assessed by AGA is strongly limited—if even occurring—in models of sciatic nerve neurotmesis47,48. On the other hand, AGA allows for comprehensive evaluation of the course of functional recovery following femoral nerve neurotmesis as shown by our data. With this work, we demonstrated that Paw Print Area is a representative gait parameter assessable via AGA, which is exemplary for the course of functional recovery in the two aforementioned peripheral nerve injury models presented by us. While functional recovery ad integrum was observable after autograft repair of the femoral nerve, AGA parameters were still significantly changed from baseline at the end of the observation period following autograft repair of the sciatic nerve. It is noteworthy in this context that limb contractures are a common phenomenon in rats with sciatic nerve injury and caution is necessary not to confuse these signs of muscular imbalance and paralysis with the proceeding functional recovery32. This on the one hand underlines the AGA method’s inability to detect significant functional recovery following neurotmesis injury in this model. On the other hand, it raises the question whether it is feasible to evaluate the sciatic nerve injury model of the rat, which is still the most commonly used experimental nerve repair model, by means of gait analysis in general in case the nerve injury is more severe than axonotmesis48. Troubleshooting details are provided in Supplementary File 1.
We also provided exemplary data on use of the method to evaluate locomotor function in rats with Spinal Cord Injury, which is possible without any required changes of the hardware setup or acquisition procedure. The same principle applies to other rodent models of central nervous injury (CNI)26,49,50 and root avulsion injury. In contrast to isolated PNIs, injuries of the spinal cord are far more complex in their pathophysiological consequences, as a multitude of highly important structures are damaged, involving efferent pathways such as the corticospinal and rubrospinal tracts and afferent pathways such as the dorsal columns and spinothalamic tracts35. The challenge to adequately assess these pathological changes is reflected in the comprehensive armamentarium of behavioral tests, such as the Basso, Beattie, and Bresnahan (BBB) score36. The gait parameter Base of Support has been reported to increase following central nervous injuries, most probably to account for a resulting instable gait. Base of Support was significantly changed from baseline from WPO10 until WPO14 in our model, supporting our presumption that this parameter allows assessment of the course of functional recovery by AGA following thoracic spinal cord contusion injury.
We are convinced that AGA is a feasible tool to evaluate functional recovery in rodents with injuries of the nervous system. Nevertheless, we advise to reflect the observed changes of gait carefully and thoroughly in each respective experimental setup. Alterations in gait parameters, e.g., an increase in Print Area following an immediate postoperative decrement or a decrease in Swing Time proceeding an immediate postoperative elevation of this parameter, over the course of the observation period do not inevitably relate to functional recovery. Instead these changes can also be related to a possible functional adaption to maintain an inconspicuous gait, given that rats are a prey species and try to avoid showing pain or disability to potential predators51. It is, therefore, recommended to use automated gait analysis as a complementary tool to relate changes of gait to other outcome measures of peripheral nerve injury and regeneration21. As mentioned previously, we also believe that it should be carefully reflected if rodents with sciatic nerve neurotmesis should be investigated by means of AGA as our finding strongly indicates that functional recovery is severely limited in this case.
As shown in our work, AGA’s main asset is the possibility to study both motor and sensory reinnervation in a multitude of experimental PNI models as well as CNI while requiring only one setup. Therefore, the method is, in our opinion, a highly valuable tool for comprehensive neurobehavioral testing. One of AGA’s assets, which is the possibility to study motor and sensory reinnervation in various animal models of PNI and CNI while requiring only one setup, is in our opinion the method’s main advantage in comparison to other evaluation methods to study functional recovery, such as walking track analysis52, Von Frey testing53, or gait kinematics16. The potential to simultaneously evaluate changes of gait which do either correlate with results of electrophysiological investigations of reinnervated muscle22 or evaluation methods for sensory function54 is promising in regard to future applications of the method. We therefore recommend using AGA to investigate functional recovery in rodent models of forelimb PNI, such as the ulnar, radial, or median nerve, or experimental nerve transfer models55, which remain unstudied with this method yet.
We hereby provide a detailed protocol on how to use automated gait analysis to study functional recovery in three rodent models of nerve injury. While the method requires careful consideration of various key aspects such as adequate training and meticulous hard- and software calibration, it is a feasible and valuable complementary tool to evaluate nerve regeneration in rodent models of central and peripheral nerve injury.