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  Extraction of functional information from ongoing brain electrical activity: Extraction en temps-réel d'informations fonctionnelles à partir de l'activité électrique cérébrale

Besserve, M., & Martinerie, J. (2011). Extraction of functional information from ongoing brain electrical activity: Extraction en temps-réel d'informations fonctionnelles à partir de l'activité électrique cérébrale. IRBM, 32(1), 27-34. doi:10.1016/j.irbm.2011.01.001.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-BC88-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-8A75-E
Genre: Journal Article

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 Creators:
Besserve, M1, 2, Author              
Martinerie, J, Author
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The modern analysis of multivariate electrical brain signals requires advanced statistical tools to automatically extract and quantify their information content. These tools include machine learning techniques and information theory. They are currently used both in basic neuroscience and challenging applications such as brain computer interfaces. We review here how these methods have been used at the Laboratoire d’Électroencéphalographie et de Neurophysiologie Appliquée (LENA) to develop a general tool for the real time analysis of functional brain signals. We then give some perspectives on how these tools can help understanding the biological mechanisms of information processing.

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 Dates: 2011-02
 Publication Status: Published in print
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 Identifiers: DOI: 10.1016/j.irbm.2011.01.001
BibTex Citekey: BesserveM2011
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Title: IRBM
Source Genre: Journal
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Pages: - Volume / Issue: 32 (1) Sequence Number: - Start / End Page: 27 - 34 Identifier: ISSN: 1959-0318