Stroke is a major cause of disability in veterans. Despite significant advances in stroke rehabilitation methods there continue to be substantial long-term disability. Importantly, quantitative assessments have found that a major contributor to motor impairments is the presence of fragmented movement control, characterized by a lack of smooth and fast transitions between sub-movements and inconsistency over multiple attempts. Furthermore, there is a deficit in learning new movement sequences. It remains unclear what is the precise circuit basis for such deficits. The central hypothesis of this proposal is that impaired task-dependent recruitment of the striatum contributes to fragmented movement control and poor learning. There has been a great focus on the role of perilesional cortex (PLC) in recovery. In the intact brain, however, cortical areas work in close concert with subcortical regions; interactions between M1 and the dorsolateral striatum (DLS) are known to play a critical role in learning and generating smooth and consistent skilled movements. Little is known about how the DLS might contribute to motor recovery after stroke. Our preliminary data shows that coordination between M1 and DLS is directly linked to “binding” of movement fragments to result in a smooth and fast skilled action. We further found that DLS is essential for such execution; inhibition of DLS increased movement fragmentation. Our data also demonstrates that DLS activity is affected by stroke and that its activity changes with recovery. We propose to pursue the following specific aims: 1) Determine the role of task-related oscillatory activity in the DLS in regulating movement fragmentation during spontaneous motor recovery after cortical stroke; 2) Determine the role of low-frequency coherence between areas during spontaneous recovery in the setting of a stroke that involves both cortex and striatum; 3) Determine if paired stimulation can increase coordination and thereby improve motor outcomes. Completion of these aims will provide critical information for designing therapeutic approaches that specifically target cortico-striatal activity. Focusing on targeted neuromodulation of such dynamic neural network interactions represents a new direction that could transform our ability to augment recovery of upper extremity function following stroke.