MEG is an emerging clinical tool to gather insight on neuronal dysfunction inside the human brain. This paper analyzes data saved as FIF file format at a small-world level. Traditionally, operating cost is very high for artifact removal. Also, the absence of a standardization with availability of more than a dozen MEG recording device vendors makes it difficult to store and process data followed by its comparison. This paper proposes a framework to avoid computation overheads, while it takes care of MEG data file format and calculates coherence with ease and efficiency. Small-world network is analyzed and 3D visualization is obtained. © 2014 IEEE.