The number of people affected by spinal cord injuries (SCI) ranges from 2.5 million to 4 million worldwide. Individuals with cervical SCI commonly experience difficulty in controlling hand function, largely due to a reduced ability to perform individuated finger movements that they may never fully recover. Specifically, impairment in the ability to accurately coordinate skilled hand actions is a well-established deficit of injury (e.g., precision grip between the thumb and index finger). Previous studies in both human and nonhuman primate models of SCI have demonstrated some recovery of these abilities over time through various compensatory pathways and mechanisms, including through neural regrowth or through physical rehabilitation with repetitive behavioral tasks.Behavioral tasks that require coordinated finger movements are important tools to examine functional recovery and potential effects of treatments after SCI. A tool used to evaluate precision hand gestures in nonhuman primates is the Brinkman board. These boards have surfaces with specially shaped grooves, called wells, that encourage the use of precision grip during a simple reach and grasp task. Performance is scored quantitatively based on gradations of the animal’s success or failure. This behavioral data provide an assessment of real-world ability, which can then be correlated with other metrics like neural regrowth. However, the change in ability after SCI may frustrate an animal who was previously able to complete the Brinkman board task with ease; they may not even attempt the task due to the task now being too difficult. Assessments must be challenging enough to be an accurate measure of ability, but a task that’s too difficult can cause the animal to give up, not just on the given task but on future similar measures or repeated assessments. Failure to participate with the Brinkman board task for any reason results in the same completion time score, conflating any distinction between simply not performing the task and trying but failing to complete it.

A primary objective of this study is to improve the quality of behavioral data collection by modifying existing Brinkman boards to expand the range and resolution of behavioral performance (floor behavior) for post-SCI animals to complete while providing comparable metrics to existing data. These modified Brinkman boards, Remedial Brinkman boards, were designed to be easier to complete and provide additional opportunities for food rewards to the animal. These additional opportunities in the Remedial Brinkman board task manifested in higher participation and performance in the Standard Brinkman board task, specifically by keeping the animal engaged with the task.Low resolution quantitative behavioral data collected through the Brinkman board task can be supplemented with a higher resolution quantitative method, such as motion tracking. These quantitative measures of finger movements could provide, higher resolution data that may allow additional insights into functional recovery. However, detailed temporal information of hand movement kinematics during recovery is lacking; there is little information on the precise timecourse during which this control improves. To begin to address this need, unimpaired animals’ hands were recorded from multiple angles during completion of the Brinkman board task. These recordings were partially annotated by hand, and then used to train a deep learning algorithm to automatically annotate all future recordings, providing a detailed quantitative measure of performance. These quantitative measures included movement velocity, the size of the aperture between the thumb (D1) and index digit (D2), the temporal relationship between velocity and maximum aperture, and finger extension of the index digit. Some of these metrics have been seen in previous human and nonhuman primate studies completing reach and grasp tasks. The second objective of this study was to devise a methodology in which behaviors before and after spinal cord injury can be systematically tracked (using high and low resolution quantitative data) in nonhuman primate models, and that could measure changes in their functional abilities.