Muscle networks represent a series of interactions among muscles in the central nervous system's effort to reduce the redundancy of the musculoskeletal system in motor-control. How this occurs has only been investigated recently in healthy subjects with a novel technique exploring the functional connectivity between muscles through intermuscular coherence (IMC), yet the potential value of this method in characterizing the alteration of muscular networks after stroke remains unknown. In this study, muscle networks were assessed in post-stroke survivors and healthy controls to identify possible alterations in the neural oscillatory drive to muscles after stroke. Surface electromyography (sEMG) was collected from eight key upper extremity muscles to non-invasively determine the common neural input to the spinal motor neurons innervating muscle fibers. Coherence was computed between all possible muscle pairs and further decomposed by non-negative matrix factorization (NMF) to identify the common spectral patterns of coherence underlying the muscle networks. Results suggested that the number of identified muscle networks during dynamic force generation decreased after stroke. The findings in this study could provide a new prospective for understanding the motor control recovery during post-stroke rehabilitation.