Automation of training and testing motor and related tasks in pre-clinical behavioural and rehabilitative neuroscience.

Testing and training animals in motor and related tasks is a cornerstone of pre-clinical behavioural and rehabilitative neuroscience. Yet manually testing and training animals in these tasks is time consuming and analyses are often subjective. Consequently, there have been many recent advances in automating both the administration and analyses of animal behavioural training and testing. This review is an in-depth appraisal of the history of, and recent developments in, the automation of animal behavioural assays used in neuroscience. We describe the use of common locomotor and non-locomotor tasks used for motor training and testing before and after nervous system injury. This includes a discussion of how these tasks help us to understand the underlying mechanisms of neurological repair and the utility of some tasks for the delivery of rehabilitative training to enhance recovery. We propose two general approaches to automation: automating the physical administration of behavioural tasks (i.e., devices used to facilitate task training, rehabilitative training, and motor testing) and leveraging the use of machine learning in behaviour analysis to generate large volumes of unbiased and comprehensive data. The advantages and disadvantages of automating various motor tasks as well as the limitations of machine learning analyses are examined. In closing, we provide a critical appraisal of the current state of automation in animal behavioural neuroscience and a prospective on some of the advances in machine learning we believe will dramatically enhance the usefulness of these approaches for behavioural neuroscientists.

Self-directed rehabilitation training intensity thresholds for efficient recovery of skilled forelimb function in rats with cervical spinal cord injury.

Task specific rehabilitation training is commonly used to treat motor dysfunction after neurological injures such as spinal cord injury (SCI), yet the use of task specific training in preclinical animal studies of SCI is not common. This is due in part to the difficulty in training animals to perform specific motor tasks, but also due to the lack of knowledge about optimal rehabilitation training parameters to maximize recovery. The single pellet reaching, grasping and retrieval (SPRGR) task (a.k.a. single pellet reaching task or Whishaw task) is a skilled forelimb motor task used to provide rehabilitation training and test motor recovery in rodents with cervical SCI. However, the relationships between the amount, duration, intensity, and timing of training remain poorly understood. In this study, using automated robots that allow rats with cervical SCI ad libitum access to self-directed SPRGR rehabilitation training, we show clear relationships between the total amount of rehabilitation training, the intensity of training (i.e., number of attempts/h), and performance in the task. Specifically, we found that rats naturally segregate into High and Low performance groups based on training strategy and performance in the task. Analysis of the different training strategies showed that more training (i.e., increased number of attempts in the SPRGR task throughout rehabilitation training) at higher intensities (i.e., number of attempts per hour) increased performance in the task, and that improved performance in the SPRGR task was linked to differences in corticospinal tract axon collateral densities in the injured spinal cords. Importantly, however, our data also indicate that rehabilitation training becomes progressively less efficient (i.e., less recovery for each attempt) as both the amount and intensity of rehabilitation training increases. Finally, we found that Low performing animals could increase their training intensity and transition to High performing animals in chronic SCI. These results highlight the rehabilitation training strategies that are most effective to regain skilled forelimb motor function after SCI, which will facilitate pre-clinical rehabilitation studies using animal models and could be beneficial in the development of more efficient clinical rehabilitation training strategies.

A Modular Adjustable Transhumeral Prosthetic Socket for Evaluating Myoelectric Control.

Novel myoelectric control strategies may yield more robust, capable prostheses which improve quality of life for those affected by upper-limb loss; however, the development and translation of such strategies from an experimental setting towards daily use by persons with limb loss is a slow and costly process. Since prosthesis functionality is highly dependent on the physical interface between the user's prosthetic socket and residual limb, assessment of such controllers under realistic (noisy) environmental conditions, integrated into prosthetic sockets, and with participants with amputation is essential for obtaining representative results. Unfortunately, this step is particularly difficult as participant- and control strategy-specific prosthetic sockets must be custom-designed and manufactured. There is thus a need for a system to reduce these burdens and facilitate this crucial phase of the development pipeline. This study aims to address this gap through the design and assessment of an inexpensive and easy-to-use 3D-printed Modular-Adjustable transhumeral Prosthetic Socket (MAPS). This 3D-printed, open-source socket was developed in consultation with prosthetists and compared with a participant-specific suction socket in a single-participant case-study. We conducted mechanical and functional assessments to ensure that the developed socket enabled similar performance compared to participant-specific sockets. Both socket systems yielded similar results in mechanical and functional assessments, as well as in self-reported user feedback. The MAPS system shows promise as a research tool which catalyzes the development and deployment of novel myoelectric control strategies by better-enabling comprehensive assessment involving participants with amputations.