Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm
Joint Authors
Zhang, Junpeng
Cui, Yuan
Deng, Lihua
He, Ling
Zhang, Junran
Zhang, Jing
Zhou, Qun
Liu, Qi
Zhang, Zhiguo
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-12-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper proposed a prewhitening invariance of noise space (PW-INN) as a new magnetoencephalography (MEG) source analysis method, which is particularly suitable for localizing closely spaced and highly correlated cortical sources under real MEG noise.
Conventional source localization methods, such as sLORETA and beamformer, cannot distinguish closely spaced cortical sources, especially under strong intersource correlation.
Our previous work proposed an invariance of noise space (INN) method to resolve closely spaced sources, but its performance is seriously degraded under correlated noise between MEG sensors.
The proposed PW-INN method largely mitigates the adverse influence of correlated MEG noise by projecting MEG data to a new space defined by the orthogonal complement of dominant eigenvectors of correlated MEG noise.
Simulation results showed that PW-INN is superior to INN, sLORETA, and beamformer in terms of localization accuracy for closely spaced and highly correlated sources.
Lastly, source connectivity between closely spaced sources can be satisfactorily constructed from source time courses estimated by PW-INN but not from results of other conventional methods.
Therefore, the proposed PW-INN method is a promising MEG source analysis to provide a high spatial-temporal characterization of cortical activity and connectivity, which is crucial for basic and clinical research of neural plasticity.
American Psychological Association (APA)
Zhang, Junpeng& Cui, Yuan& Deng, Lihua& He, Ling& Zhang, Junran& Zhang, Jing…[et al.]. 2015. Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm. Neural Plasticity،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1113161
Modern Language Association (MLA)
Zhang, Junpeng…[et al.]. Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm. Neural Plasticity No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1113161
American Medical Association (AMA)
Zhang, Junpeng& Cui, Yuan& Deng, Lihua& He, Ling& Zhang, Junran& Zhang, Jing…[et al.]. Closely Spaced MEG Source Localization and Functional Connectivity Analysis Using a New Prewhitening Invariance of Noise Space Algorithm. Neural Plasticity. 2015. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1113161
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1113161