TY  - CONF
Y1  - 2017///
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781509008452
A1  - Rasheed, W.
A1  - Tang, T.B.
A1  - Hamid, N.H.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011976634&doi=10.1109%2fICIAS.2016.7824139&partnerID=40&md5=fcd0607ad1070a5062c8d2ac4d561b2b
AV  - none
N2  - Functional connectivity is becoming popular as a second opinion for neurosurgeons and specialists in order to decide on the need for surgical resection, or prescribing medication and appraise prognosis. Neuroimaging modalities such as fMRI, fNIRS, PET, and EEG provide functional connectivity estimation. MEG is the most recent trend in functional connectivity assessment research as it gives more accurate results. The magnetic signals are not disrupted by volume conduction, as in EEG. Besides a reasonable spatial resolution, it offers an extraordinary temporal resolution. However there is a need of a generalized model for default mode network connectivity using MEG. This paper presents a novel method for generating a generalized model and discusses significance of threshold levels in assessing synchronization of activity from various brain regions. © 2016 IEEE.
N1  - cited By 0; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970
ID  - scholars8965
TI  - Threshold for computing generalized model of default mode network connectivity
KW  - Brain; Brain mapping; Magnetoencephalography; Neuroimaging
KW  -  Default-mode networks; Functional connectivity; Generalized coherences; Generalized models; Spatial resolution; Surgical resection; Temporal resolution; Threshold
KW  -  Functional neuroimaging
ER  -