Threshold for computing generalized model of default mode network connectivity
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 estimat...
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| Main Authors: | , , |
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| Format: | Article |
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Institute of Electrical and Electronics Engineers Inc.
2017
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011976634&doi=10.1109%2fICIAS.2016.7824139&partnerID=40&md5=fcd0607ad1070a5062c8d2ac4d561b2b http://eprints.utp.edu.my/20180/ |
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| Summary: | 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. |
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