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Non-gaussian probabilistic MEG source localisation based on kernel density estimation

Abstract:

There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data. By providing a Bayesian formulation for ME...

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Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
Journal:
NeuroImage More from this journal
Volume:
87
Pages:
444-464
Publication date:
2014-02-15
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
Pubs id:
pubs:448252
UUID:
uuid:acb41eca-3d7f-4061-8243-ca098196aec0
Local pid:
pubs:448252
Source identifiers:
448252
Deposit date:
2014-02-14

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