eprintid: 8362
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/83/62
datestamp: 2023-11-09 16:20:15
lastmod: 2023-11-09 16:20:15
status_changed: 2023-11-09 16:12:28
type: article
metadata_visibility: show
creators_name: Rasheed, W.
creators_name: Neoh, Y.Y.
creators_name: Bin Hamid, N.H.
creators_name: Reza, F.
creators_name: Idris, Z.
creators_name: Tang, T.B.
title: Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction
ispublished: pub
keywords: Brain; Brain mapping; Coherent light; Data mining; Data visualization; Electroencephalography; Electrophysiology; Magnetoencephalography; Neurons; Visualization, Default mode connectivity; Functional connectivity; Healthy population; Magnitude squared coherences; Neuroimaging techniques; Neuronal dysfunction; Personalized thresholds; Traumatic Brain Injuries, Population statistics, adult; alpha rhythm; Article; beta rhythm; brain region; brain tumor; clinical article; controlled study; contusion; delta rhythm; epilepsy; female; functional connectivity; functional neuroimaging; gamma rhythm; Glasgow coma scale; human; magnetoencephalography; male; middle aged; nerve cell plasticity; plasticity; priority journal; skull fracture; subdural hematoma; theta rhythm; traumatic brain injury; connectome; degenerative disease; diagnostic imaging; electroencephalography; epilepsy; information processing; pathophysiology; procedures; traumatic brain injury, Automatic Data Processing; Brain Injuries, Traumatic; Connectome; Electroencephalography; Epilepsy; Female; Humans; Magnetoencephalography; Male; Neurodegenerative Diseases
note: cited By 4
abstract: Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed. © 2017 Elsevier Ltd
date: 2017
publisher: Elsevier Ltd
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019644046&doi=10.1016%2fj.compbiomed.2017.05.005&partnerID=40&md5=b37a065bb02a9a8aa0e7c1e572a8be8e
id_number: 10.1016/j.compbiomed.2017.05.005
full_text_status: none
publication: Computers in Biology and Medicine
volume: 89
pagerange: 573-583
refereed: TRUE
issn: 00104825
citation:   Rasheed, W. and Neoh, Y.Y. and Bin Hamid, N.H. and Reza, F. and Idris, Z. and Tang, T.B.  (2017) Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction.  Computers in Biology and Medicine, 89.  pp. 573-583.  ISSN 00104825