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Integration of Multivariate Data Streams With Bandpower Signals

Authors
Daehne, SvenBiessmann, FelixMeinecke, Frank C.Mehnert, JanFazli, SiamacMueller, Klaus-Robert
Issue Date
8월-2013
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
EEG; EEG-NIRS; multimodal; neuroimaging; NIRS
Citation
IEEE TRANSACTIONS ON MULTIMEDIA, v.15, no.5, pp.1001 - 1013
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON MULTIMEDIA
Volume
15
Number
5
Start Page
1001
End Page
1013
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/102508
DOI
10.1109/TMM.2013.2250267
ISSN
1520-9210
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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Graduate School > Department of Brain and Cognitive Engineering > 1. Journal Articles
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