A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA

Smith, E. E., Bel‐Bahar, T. S., & Kayser, J. (2022). A systematic data‐driven approach to analyze sensor‐level EEG connectivity: Identifying robust phase‐synchronized network components using surface Laplacian with spectral‐spatial PCA. Psychophysiology, 59(10). Portico. https://doi.org/10.1111/psyp.14080
Authors:
Ezra E. Smith
Tarik S. Bel-Bahar
Jürgen Kayser
Affiliated Authors:
Jürgen Kayser
Columbia Affiliation:
Subjects:
Brain Mapping (MeSH)
Electroencephalography (MeSH)
Author Keywords:
alpha
theta networks
current source density (csd)
functional connectivity (fc)
principal components analysis (pca)
resting eeg
alpha/theta networks
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Publication Type:
Article
Unique ID:
10.1111/psyp.14080
PMID:
35478408
DOI:
10.1111/psyp.14080
Journal:
Psychophysiology
Publication Date:
Data Source:
Scopus
Source Link:
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