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Independent component approach to the analysis of EEG and MEG recordings

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Author(s): Vigário, Dr Ricardo; Särelä, Mr Jaakko; Jousmäki, Dr Veikko; Hämäläinen, Dr Matti; Oja, prof. Erkki
Source:
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)]
Subject Terms:
Neuroscience: Brain Imaging; Computer Science: Statistical Models; Computer Science: Machine Learning; Brain Imaging; Statistical Models; Machine Learning
Document Type:
Journal Article
Online Access:
http://cogprints.org/3639/

Additional Information
- Publication Information:
  Published
- Publication Date:
  2000
- Original Material:
  Journal (Paginated)
- Abstract:
  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.
- File Description:
  application/pdf
- Accession Number:
  edscog.3639

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