Integration of multivariate data streams with bandpower signals

Sven Dähne, Felix Biesßmann, Frank C. Meinecke, Jan Mehnert, Siamac Fazli, Klaus Muller

Research output: Contribution to journalArticle

24 Citations (Scopus)

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.

Original languageEnglish
Article number6472075
Pages (from-to)1001-1013
Number of pages13
JournalIEEE Transactions on Multimedia
Volume15
Issue number5
DOIs
Publication statusPublished - 2013 Aug 2

Keywords

  • EEG
  • EEG-NIRS
  • Multimodal
  • Neuroimaging
  • NIRS

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Signal Processing
  • Media Technology
  • Computer Science Applications

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  • Cite this

    Dähne, S., Biesßmann, F., Meinecke, F. C., Mehnert, J., Fazli, S., & Muller, K. (2013). Integration of multivariate data streams with bandpower signals. IEEE Transactions on Multimedia, 15(5), 1001-1013. [6472075]. https://doi.org/10.1109/TMM.2013.2250267