Recent advances in the field of human brain imaging by electrophysiological recordings allow to reliably quantify the connectivity patterns of spontaneous oscillatory activity. This has provided novel tools to investigate the neural basis underlying complex human behavior and to unravel the mechanisms of brain function and reorganization in response to neurological diseases. In this context, we present a pipeline integrating high-density electroencephalography (hd-EEG) analysis and graph theory. To test our pipeline, we conducted a feasibility study on hd-EEG analysis to recordings from healthy individuals, examining the frequency-specific small-world organization of brain connectivity. Here we present the preliminary results on a small sample size. The ultimate goal of our study is to extract graph-theory related metrics, such as small-worldness index, from injured patients and use them as electrophysiological biomarkers of the recovery.