Document Type



Action selection (AS), or selection of an action from a set of alternatives, is an important movement preparation process that engages a frontal-parietal network. The addition of AS demands to arm training after stroke could be used to engage this motor planning process and the neural network that supports it. The purpose of this case series is to describe the feasibility and outcomes associated with task-oriented arm training aimed at engaging the AS behavioral process and the related neural network in three individuals with chronic stroke. Three participants with mild to moderate motor deficits completed 13 to 15 sessions of task-oriented arm training that included AS cues for each movement repetition; cues dictated movement direction, height, or distance. Before and after training, individuals completed an AS brain-behavior probe during functional MRI. AS behavioral performance improved after training (increased accuracy, decreased reaction time) in all participants while brain activation in the AS network (dorsal premotor, parietal, dorsolateral prefrontal cortices) decreased in two participants. Gains in motor function were also found in all three participants, especially on patient-reported measures of perceived difficulty and confidence to complete upper extremity functional tasks. It was feasible to target the AS behavioral process and the related neural network through the addition of AS demands to functional, task-oriented arm training in three individuals with mild to moderate motor dysfunction poststroke.

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APA Citation

Stewart, J. C., Handlery, K., Baird, J. F., Blanck, E. L., Pathak, G., & Fritz, S. L. (2020). Targeted engagement of the action selection network during task-oriented arm training after stroke. Neural Plasticity, 2020, 1–11.


© 2020 Jill Campbell Stewart et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.