Slow and fast EEG sleep spindle component extraction using Independent Component Analysis

Sleep spindles are groups of rhythmic activity, with a waxing-waning morphology, and are considered a hallmark of stage 2 of the sleep electroencephalogram (EEG). They are present predominantly in stages 2, 3 and 4 of the sleep EEG. Spatial analysis of sleep spindle scalp EEG and EEG inverse problem...

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Bibliographic Details
Main Authors: Ventouras, E.M., Ktonas, P.Y., Tsekou, H., Paparrigopoulos, T., Kalatzis, I., Soldatos, C.R.
Format: Conference Proceeding
Language:English
Subjects:
Data mining
Educational technology
Electroencephalography
Frequency
Independent component analysis
Inverse problems
Morphology
Scalp
Sleep
Tomography
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Summary:Sleep spindles are groups of rhythmic activity, with a waxing-waning morphology, and are considered a hallmark of stage 2 of the sleep electroencephalogram (EEG). They are present predominantly in stages 2, 3 and 4 of the sleep EEG. Spatial analysis of sleep spindle scalp EEG and EEG inverse problem solutions have provided evidence for the existence of two distinct sleep spindle types, ldquoslowrdquo and ldquofastrdquo spindles at approximately 12 and 14 Hz, respectively. The present study aimed at processing sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting spindle ldquocomponentsrdquo corresponding to separate EEG activity patterns. The EEG activity underlying the components was also investigated, using the Low-Resolution Brain Electromagnetic Tomography (LORETA) technique, inverting the 21-channel EEG recordings to cortical current sources. Results indicate separability and stability of current sources related to sleep spindle ldquocomponentsrdquo reconstructed from separate groups of Independent Components (ICs).
DOI:10.1109/BIBE.2008.4696821