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A signal-processing pipeline for magnetoencephalography resting-state networks.

Abstract:

To study functional connectivity using magnetoencephalographic (MEG) data, the high-quality source-level reconstruction of brain activity constitutes a critical element. MEG resting-state networks (RSNs) have been documented by means of a dedicated processing pipeline: MEG recordings are decomposed by independent component analysis (ICA) into artifact and brain components (ICs); next, the channel maps associated with the latter ones are projected into the source space and the resulting voxel-...

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Publisher copy:
10.1089/brain.2011.0001

Authors


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Institution:
University of Oxford
Department:
Oxford, MSD, Experimental Psychology
Della Penna, S More by this author
Marzetti, L More by this author
de Pasquale, F More by this author
Pizzella, V More by this author
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Journal:
Brain connectivity
Volume:
1
Issue:
1
Pages:
49-59
Publication date:
2011
DOI:
EISSN:
2158-0022
ISSN:
2158-0014
URN:
uuid:8f83aad5-7547-409e-900b-2124965afd5e
Source identifiers:
364109
Local pid:
pubs:364109

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