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Inferring task-related networks using independent component analysis in magnetoencephalography.

Abstract:

A novel framework for analysing task-positive data in magnetoencephalography (MEG) is presented that can identify task-related networks. Techniques that combine beamforming, the Hilbert transform and temporal independent component analysis (ICA) have recently been applied to resting-state MEG data and have been shown to extract resting-state networks similar to those found in fMRI. Here we extend this approach in two ways. First, we systematically investigate optimisation of time-frequency wi...

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Publication status:
Published

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Institution:
University of Oxford
Department:
Oxford, MSD, Psychiatry
Role:
Author
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Institution:
University of Oxford
Department:
Oxford, MSD, Experimental Psychology
Role:
Author
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Journal:
NeuroImage
Volume:
62
Issue:
1
Pages:
530-541
Publication date:
2012-08-05
DOI:
EISSN:
1095-9572
ISSN:
1053-8119
URN:
uuid:1d8df227-fc7d-41a5-acfd-6d4a3b07799f
Source identifiers:
328994
Local pid:
pubs:328994

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