Background and Objective. Kinematic analysis of reaching movements is increasingly used to evaluate upper extremity function after cerebrovascular insults in humans and has also been applied to rodent models. Such analyses can require time-consuming frame-by-frame inspections and are affected by the experimenter's bias. In this study, we introduce a semi-automated algorithm for tracking forepaw movements in mice. This methodology allows us to calculate several kinematic measures for the quantitative assessment of performance in a skilled reaching task before and after a focal cortical stroke. Methods. Mice were trained to reach for food pellets with their preferred paw until asymptotic performance was achieved. Photothrombosis was then applied to induce a focal ischemic injury in the motor cortex, contralateral to the trained limb. Mice were tested again once a week for 30 days. A high frame rate camera was used to record the movements of the paw, which was painted with a nontoxic dye. An algorithm was then applied off-line to track the trajectories and to compute kinematic measures for motor performance evaluation. Results. The tracking algorithm proved to be fast, accurate, and robust. A number of kinematic measures were identified as sensitive indicators of poststroke modifications. Based on end-point measures, ischemic mice appeared to improve their motor performance after 2 weeks. However, kinematic analysis revealed the persistence of specific trajectory adjustments up to 30 days poststroke, indicating the use of compensatory strategies. Conclusions. These results support the use of kinematic analysis in mice as a tool for both detection of poststroke functional impairments and tracking of motor improvements following rehabilitation. Similar studies could be performed in parallel with human studies to exploit the translational value of this skilled reaching analysis.
Quantitative kinematic characterization of reaching impairments in mice after a stroke
Spalletti C;Caleo M;
2015
Abstract
Background and Objective. Kinematic analysis of reaching movements is increasingly used to evaluate upper extremity function after cerebrovascular insults in humans and has also been applied to rodent models. Such analyses can require time-consuming frame-by-frame inspections and are affected by the experimenter's bias. In this study, we introduce a semi-automated algorithm for tracking forepaw movements in mice. This methodology allows us to calculate several kinematic measures for the quantitative assessment of performance in a skilled reaching task before and after a focal cortical stroke. Methods. Mice were trained to reach for food pellets with their preferred paw until asymptotic performance was achieved. Photothrombosis was then applied to induce a focal ischemic injury in the motor cortex, contralateral to the trained limb. Mice were tested again once a week for 30 days. A high frame rate camera was used to record the movements of the paw, which was painted with a nontoxic dye. An algorithm was then applied off-line to track the trajectories and to compute kinematic measures for motor performance evaluation. Results. The tracking algorithm proved to be fast, accurate, and robust. A number of kinematic measures were identified as sensitive indicators of poststroke modifications. Based on end-point measures, ischemic mice appeared to improve their motor performance after 2 weeks. However, kinematic analysis revealed the persistence of specific trajectory adjustments up to 30 days poststroke, indicating the use of compensatory strategies. Conclusions. These results support the use of kinematic analysis in mice as a tool for both detection of poststroke functional impairments and tracking of motor improvements following rehabilitation. Similar studies could be performed in parallel with human studies to exploit the translational value of this skilled reaching analysis.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.