| Autor: |
Daniela Hernandez, Duque, Jordan M, Racca, Isaac V, Manzanera Esteve, Pai-Feng, Yang, John C, Gore, Li Min, Chen |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
SSRN Electronic Journal. |
| ISSN: |
1556-5068 |
| Popis: |
Comprehensive characterizations of hand grasping behaviors after cervical spinal cord injuries are fundamental for developing rehabilitation strategies to promote recovery in spinal-cord-injured primates. We used the machine-learning-based video analysis software, DeepLabCut, to sensitively quantify kinematic aspects of grasping behavioral deficits in squirrel monkeys with C5-level spinal cord injuries. Three squirrel monkeys were trained to grasp sugar pellets from wells of varying depths before and after a left unilateral lesion of the cervical dorsal column. Using DeepLabCut, we identified post-lesion deficits in kinematic grasping behavior that included changes in digit orientation, increased variance in vertical and horizontal digit movement, and longer time to complete the task. While video-based analyses of grasping behavior demonstrated deficits in fine-scale digit function that persisted through at least 14 weeks post-injury, traditional end-point behavioral analyses showed a recovery of global hand function as evidenced by recovery of the proportion of successful retrievals by approximately 14 weeks post-injury. The combination of traditional end-point and video-based kinematic analyses provides a more comprehensive characterization of grasping behavior and highlights that global grasping performance may recover despite persistent fine-scale kinematic deficits in digit function. Machine-learning-based video analysis of kinematic digit function, in conjunction with traditional end-point behavioral analyses of grasping behavior, provide sensitive and specific indices for monitoring recovery of fine-grained hand sensorimotor behavior after spinal cord injury that can aid future studies that seek to develop targeted therapeutic interventions for improving behavioral outcomes. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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