Sleep spindles are bursts of rhythmic activity characterized by progressively increasing, then gradually decreasing amplitude, present predominantly in stages 2, 3 and 4 of the sleep electroencephalogram (EEG). Topographic analyses of sleep spindle incidence suggested the existence of two distinct sleep spindle types, “slow” and “fast” spindles at approximately 12 and 14 Hz respectively. There are indications that there exist at least two functionally separated spindle generators, corresponding to each frequency spectrum class. The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, in the ICA-reconstructed EEG, spindle “components” corresponding to separate EEG activity patterns, and to investigate the sources underlying these spindle components. Using 8-channel EEG recordings of sleep spindles of a single subject, source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied on the reconstructed EEGs. Results indicate separability and stability of sources related to sleep spindle components reconstructed from separate groups of Independent Components (ICs).