Electroencephalography has long served as a pivotal modality in the exploration of brain functions, particularly within the domains of motor imagery and motor execution. This investigation aimed to delineate commonalities and disparities in functional connectivity networks of motor imagery/execution by employing the weighted phase lag index for the analysis of EEG data across the mu and beta frequency bands. The results reveal that the topological configurations of brain networks at the functional level exhibit consistent characteristics, particularly with respect to leaf fraction, diameter, and maximum degree, in both motor imagery and execution tasks. In general, the findings highlight the critical need to incorporate multiple features and frequency bands in the evaluation of topological metrics within the realms of motor imagery and execution. These insights are poised to substantially advance our understanding of the neurological foundations of these motor activities and contribute to future scholarly inquiries and technological advancements in neurotechnology.