Non-linear canonical correlation for joint analysis of MEG signals from two subjects

Non-linear canonical correlation for joint analysis of MEG signals from two subjects

We consider the problem of analysing magnetoencephalography (MEG) data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA), which provides linear tr...

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Bibliographic Details
Main Authors: Cristina eCampi, Lauri Tapio Parkkonen, Riitta eHari, Aapo eHyvärinen
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-06-01
Series:Frontiers in Neuroscience
Subjects:
social interaction
Magnetoencephalography (MEG)
canonical correlation anaysis (CCA)
non-linear CCA
brain signal processing
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00107/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00107/full

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