Independent component approach to the analysis of EEG and MEG recordings

Vigário, Dr Ricardo and Särelä, Mr Jaakko and Jousmäki, Dr Veikko and Hämäläinen, Dr Matti and Oja, prof. Erkki (2000) Independent component approach to the analysis of EEG and MEG recordings. [Journal (Paginated)]

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Multichannel recordings of the electromagnetic fields emerging from neural currents in the brain generate large amounts of data. Suitable feature extraction methods are, therefore, useful to facilitate the representation and interpretation of the data. Recently developed independent component analysis (ICA) has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic (EEG) and magnetoen- cephalographic (MEG) recordings. In addition, ICA has been ap- plied to the analysis of brain signals evoked by sensory stimuli. This paper reviews our recent results in this field.

Item Type:Journal (Paginated)
Keywords:independent component analysis (ICA), blind source separation (BSS), unsupervised learning, electroencephalography (EEG), magnetoencephalography(MEG), artifact removal, auditory evoked field (AEF), somatosensory evoked field (SEF)
Subjects:Neuroscience > Brain Imaging
Computer Science > Statistical Models
Computer Science > Machine Learning
ID Code:3639
Deposited By: Särelä, Dr Jaakko
Deposited On:24 May 2004
Last Modified:11 Mar 2011 08:55


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