Inferring task-related networks using independent component analysis in magnetoencephalography

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 a...

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Detalles Bibliográficos
Autores principales: Luckhoo, H., Hale, J.R., Stokes, M.G., Nobre, A.C., Morris, P.G., Brookes, M.J., Woolrich, M.W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2012
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387383/
https://www.ncbi.nlm.nih.gov/pubmed/22569064
http://dx.doi.org/10.1016/j.neuroimage.2012.04.046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387383/
https://www.ncbi.nlm.nih.gov/pubmed/22569064
http://dx.doi.org/10.1016/j.neuroimage.2012.04.046

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