Cargando…
Multi-session statistics on beamformed MEG data()
Beamforming has been widely adopted as a source reconstruction technique in the analysis of magnetoencephalography data. Most beamforming implementations incorporate a spatially-varying rescaling (which we term weights normalisation) to correct for the inherent depth bias in raw beamformer estimates...
Autores principales: | Luckhoo, Henry T., Brookes, Matthew J., Woolrich, Mark W. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Academic Press
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4073650/ https://www.ncbi.nlm.nih.gov/pubmed/24412400 http://dx.doi.org/10.1016/j.neuroimage.2013.12.026 |
Ejemplares similares
-
Optimising beamformer regions of interest analysis
por: Oswal, Ashwini, et al.
Publicado: (2014) -
Using generative models to make probabilistic statements about hippocampal engagement in MEG
por: Meyer, Sofie S., et al.
Publicado: (2017) -
Measuring functional connectivity in MEG: A multivariate approach insensitive to linear source leakage
por: Brookes, M.J., et al.
Publicado: (2012) -
How reliable are MEG resting-state connectivity metrics?
por: Colclough, G.L., et al.
Publicado: (2016) -
Dynamic state allocation for MEG source reconstruction
por: Woolrich, Mark W., et al.
Publicado: (2013)