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Modeling sparse connectivity between underlying brain sources for EEG/MEG
Stefan Haufe
*
, Ryota Tomioka
, Guido Nolte
,
Klaus Robert Müller
, Motoaki Kawanabe
*
Corresponding author for this work
Research output
:
Contribution to journal
›
Article
›
peer-review
90
Citations (Scopus)
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Keyphrases
Electroencephalography
100%
Brain Sources
100%
Magnetoencephalography
100%
Sparse Connectivity
100%
Source Analysis
66%
Multivariate Autoregressive Model
66%
Sparsely Connected
66%
Functional Connectivity
33%
Volume Conduction
33%
Overfitting
33%
Sparse Data
33%
Neural Data
33%
Novel Technique
33%
Existing Algorithms
33%
Linear Mixture
33%
Demixing
33%
Correlated Sources
33%
Functional Brain Connectivity
33%
Data-driven Model
33%
Autoregressive Parameters
33%
Group Lasso Penalty
33%
Mathematics
Simulated Data
100%
Functional Connectivity
100%
Autoregressive Model
100%
Data-Driven Model
100%
Computer Science
Simulated Data
100%
Functional Connectivity
100%
Linear Mixture
100%
Neuroscience
Functional Connectivity
100%
Autoregressive Process
50%
Medicine and Dentistry
Functional Connectivity
100%