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  Integration of multivariate data streams with bandpower signals

Dähne, S., Bießmann, F., Meinecke, F. C., Mehnert, J., Fazli, S., & Müller, K.-R. (2013). Integration of multivariate data streams with bandpower signals. IEEE Transactions on Multimedia, 15(5), 1001-1013. doi:10.1109/TMM.2013.2250267.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0015-173A-1 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-CD5B-B
Genre: Journal Article

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 Creators:
Dähne, Sven1, 2, Author
Bießmann, Felix1, 3, Author
Meinecke, Frank C.1, Author
Mehnert, Jan1, 4, 5, 6, Author              
Fazli, Siamac1, 6, Author
Müller, Klaus-Robert1, 6, Author
Affiliations:
1Department of Machine Learning, TU Berlin, Germany, ou_persistent22              
2Bernstein Center for Computational Neuroscience, Berlin, Germany, ou_persistent22              
3Department of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ou_persistent22              
4Berlin Neuroimaging Center, Charité University Medicine Berlin, Germany, ou_persistent22              
5Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
6Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea, ou_persistent22              

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Free keywords: EEG; EEG-NIRS; NIRS; Multimodal; Neuroimaging
 Abstract: The urge to further our understanding of multimodal neural data has recently become an important topic due to the ever increasing availability of simultaneously recorded data from different neural imaging modalities. In case where EEG is one of the modalities, it is of interest to relate a nonlinear function of the raw EEG time-domain signal, say, EEG band power, to another modality such as the hemodynamic response, as measured with NIRS or fMRI. In this work we tackle exactly this problem defining a novel algorithm that we denote multimodal source power correlation analysis (mSPoC). The validity and high performance of the mSPoC framework is demonstrated for simulated and real-world multimodal data.

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Language(s): eng - English
 Dates: 2013-08
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: BibTex Citekey: dahne2013integration
DOI: 10.1109/TMM.2013.2250267
 Degree: -

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Title: IEEE Transactions on Multimedia
Source Genre: Journal
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Publ. Info: Piscataway, NJ : Institute of Electrical and Electronics Engineers
Pages: - Volume / Issue: 15 (5) Sequence Number: - Start / End Page: 1001 - 1013 Identifier: ISSN: 1520-9210
CoNE: https://pure.mpg.de/cone/journals/resource/958480152016