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Multimodal Imaging and BCI
Published on Dec 03, 20122739 Views
Each method for imaging brain activity has technical or physiological limits. Thus, combinations of neuroimaging modalities that can alleviate these limitations such as simultaneous recordings of neur
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Chapter list
Multimodal Imaging andBCI00:00
Multimodal Data00:49
Multimodal <-> Nonstationary04:27
Motivation: Shiftingdistributionswithinexperiment04:56
Changes are similar !06:13
Cartoon: learnfromadversenonstationarysubspaceacrosssubjects08:02
Algorithm08:39
Results09:31
Interpretation11:08
Feature distribution becomes stationary12:07
SummaryPart I12:42
NIRS-EEG Brain Computer Interfaces13:27
Experimental Setup and Paradigm13:53
Temporal Dependency of Classification in Executed Movements14:43
Temporal Dependency of Classification in Motor Imagery15:43
Combination of EEG and NIRS16:07
Feature Combination (1)17:01
Feature Combination (2)17:22
Feature Combination (3)17:28
Mutual Information17:55
DiscussionPart II19:26
Finding nonlinear correlations between NIRS &EEG21:56
Generative Model (1)22:44
Generative Model (2)24:37
Approaches tomultimodal dataanalysis (1)25:13
Approaches tomultimodal dataanalysis (2)27:07
Approaches tomultimodal dataanalysis (3)27:58
Multimodal sourcepower correlationanalysis(mSPoC)28:38
Multimodal analysis of simultaneously recorded EEG and NIRS32:25
mSPoC vs CCA (1)33:16
mSPoC vs CCA (2)33:38
Conclusion35:26
ThankstoBBCI coreteam37:40