Default mode functional connectivity estimation and visualization framework for MEG data

Rasheed, W. and Tang, T.B. and Bin Hamid, N.H. (2015) Default mode functional connectivity estimation and visualization framework for MEG data. In: UNSPECIFIED.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Magnetoencephalography (MEG) is used for functional connectivity analysis, and can record brain signals from deep sources non-invasively. Modern MEG systems measure signals at a temporal resolution of milliseconds and at millimeter precision. However, there is a lack of standardization in the position and orientation of sensors, unlike the electroencephalography (EEG) that follows sensor positioning guidelines defined by international 10-20 10-10 or 10-5 systems. Mapping MEG sensor positioning to EEG's is essential to enable data fusion and comparison of both modalities. This paper reports the development of a novel framework for MEG data visualization and analysis. The strength of the proposed framework is demonstrated through input of sizeable data from multiple healthy subjects and generating default mode connectivity visualization from the most common and significantly active coherent brain regions. © 2015 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Impact Factor: cited By 0
Uncontrolled Keywords: Brain; Brain mapping; Data fusion; Electrophysiology; Magnetoencephalography; Sensor data fusion; Visualization, Brain regions; Functional connectivity; Healthy subjects; Position and orientations; Sensor positioning; Temporal resolution; Visualization and analysis; Visualization framework, Data visualization
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 30 Aug 2021 07:06
Last Modified: 30 Aug 2021 07:06
URI: http://scholars.utp.edu.my/id/eprint/26280

Actions (login required)

View Item
View Item