Multimodal integration of electrophysiological and hemodynamic signals

Sven Dähne, Felix Bießmann, Frank C. Meinecke, Jan Mehnert, Siamac Fazli, Klaus Robert Müller

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)


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 the electroencephalogram (EEG) is one of the measurement modalities, it is of interest to relate a nonlinear function of the raw EEG time-domain signal, namely the dynamics of EEG bandpower, to another modality such as the hemodynamic response, as measured with near-infrared spectroscopy (NIRS) or functional magnetic resonance imaging (fMRI). In this work we tackle exactly this problem by defining a novel algorithm that we denote multimodal source power correlation analysis (mSPoC). The validity of the mSPoC approach is demonstrated for real-world multimodal data, obtained from a Brain-Computer Interface experiment, where mSPoC's ability to recover common sources from multimodal measurements is contrasted against an existing state-of-art approach represented by canonical correlation analysis (CCA).

Original languageEnglish
Publication statusPublished - Jan 1 2014
Externally publishedYes
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: Feb 17 2014Feb 19 2014


Conference2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Human Factors and Ergonomics


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