- 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-...
Expand abstract - Publisher copy:
- 10.1089/brain.2011.0001
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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
- Language:
- English
- Keywords:
- Copyright date:
- 2011
Journal article
A signal-processing pipeline for magnetoencephalography resting-state networks.
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