eprintid: 4963
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/49/63
datestamp: 2023-11-09 16:16:40
lastmod: 2023-11-09 16:16:40
status_changed: 2023-11-09 16:00:03
type: conference_item
metadata_visibility: show
creators_name: Rasheed, W.
creators_name: Tang, T.B.
creators_name: Hamid, N.H.B.
title: Novel framework for small-world network connectivity analysis for MEG data
ispublished: pub
keywords: Brain mapping; Coherent light; Magnetoencephalography; Three dimensional computer graphics; Visualization, 3D Visualization; Elekta; FIF; MEG; Neuromag, Small-world networks
note: cited By 2; Conference of 2014 5th International Conference on Intelligent and Advanced Systems, ICIAS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:107042
abstract: 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.
date: 2014
publisher: IEEE Computer Society
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84906335947&doi=10.1109%2fICIAS.2014.6869458&partnerID=40&md5=df34aea0eb761bc237c07ab4c24f6033
id_number: 10.1109/ICIAS.2014.6869458
full_text_status: none
publication: 2014 5th International Conference on Intelligent and Advanced Systems: Technological Convergence for Sustainable Future, ICIAS 2014 - Proceedings
place_of_pub: Kuala Lumpur
refereed: TRUE
isbn: 9781479946549
citation:   Rasheed, W. and Tang, T.B. and Hamid, N.H.B.  (2014) Novel framework for small-world network connectivity analysis for MEG data.  In: UNSPECIFIED.