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Independent Components of Magnetoencephalography: Localization
2002
Neural Computation
Independent component analysis (ICA) is a class of decomposition methods that separate sources from mixtures of signals. In this chapter, we used second order blind identification (SOBI), one of the ICA method, to demonstrate its advantages in identifying magnetic signals associated with neural information processing. Using 122-channel MEG data collected during both simple sensory activation and complex cognitive tasks, we explored SOBI's ability to help isolate and localize underlying neuronal
doi:10.1162/089976602760128036
pmid:12180404
fatcat:zrj2pbssvffureyzgwx6lavezy