Dexterity: A MATLAB-based analysis software suite for processing and visualizing data from tasks that measure arm or forelimb function.

BACKGROUND: Hand function is critical for independence, and neurological injury often impairs dexterity. To measure hand function in people or forelimb function in animals, sensors are employed to quantify manipulation. These sensors make assessment easier and more quantitative and allow automation of these tasks. While automated tasks improve objectivity and throughput, they also produce large amounts of data that can be burdensome to analyze. We created software called Dexterity that simplifies data analysis of automated reaching tasks. NEW METHOD: Dexterity is MATLAB software that enables quick analysis of data from forelimb tasks. Through a graphical user interface, files are loaded and data are identified and analyzed. These data can be annotated or graphed directly. Analysis is saved, and the graph and corresponding data can be exported. For additional analysis, Dexterity provides access to custom scripts created by other users. RESULTS: To determine the utility of Dexterity, we performed a study to evaluate the effects of task difficulty on the degree of impairment after injury. Dexterity analyzed two months of data and allowed new users to annotate the experiment, visualize results, and save and export data easily. COMPARISON WITH EXISTING METHOD(S): Previous analysis of tasks was performed with custom data analysis, requiring expertise with analysis software. Dexterity made the tools required to analyze, visualize and annotate data easy to use by investigators without data science experience. CONCLUSIONS: Dexterity increases accessibility to automated tasks that measure dexterity by making analysis of large data intuitive, robust, and efficient.

An Automated Test of Rat Forelimb Supination Quantifies Motor Function Loss and Recovery After Corticospinal Injury.

BACKGROUND: Rodents are the primary animal model of corticospinal injury and repair, yet current behavioral tests do not show the large deficits after injury observed in humans. Forearm supination is critical for hand function and is highly impaired by corticospinal injury in both humans and rats. Current tests of rodent forelimb function do not measure this movement. OBJECTIVE: To determine if quantification of forelimb supination in rats reveals large-scale functional loss and partial recovery after corticospinal injury. METHODS: We developed a knob supination device that quantifies supination using automated and objective methods. Rats in a reaching box have to grasp and turn a knob in supination in order to receive a food reward. Performance on this task and the single pellet reaching task were measured before and after 2 manipulations of the pyramidal tract: a cut lesion of 1 pyramid and inactivation of motor cortex using 2 different drug doses. RESULTS: A cut lesion of the corticospinal tract produced a large deficit in supination. In contrast, there was no change in pellet retrieval success. Supination function recovered partially over 6 weeks after injury, and a large deficit remained. Motor cortex inactivation produced a dose-dependent loss of knob supination; the effect on pellet reaching was more subtle. CONCLUSIONS: The knob supination task reveals in rodents 3 signature hand function changes observed in humans with corticospinal injury: (1) large-scale loss with injury, (2) partial recovery in the weeks after injury, and (3) loss proportional to degree of dysfunction.