Sleep spindles are considered a hallmark of stage 2 of the sleep electroencephalogram (EEG) and are used both for sleep staging and for clinical studies of pharmacological agents. Analyses of sleep spindle topography, as well as intracranial source investigations provided evidence for the existence of two distinct sleep spindle types, “slow” and “fast” spindles at approximately 12 and 14 Hz, respectively. The aim of the present study was to apply Independent Component Analysis (ICA) to sleep spindles, for examining the possibility of extracting, through visual analysis of the spindle EEG and selection of Independent Components (ICs), spindle “components” corresponding to separate EEG activity patterns, and to investigate the sources underlying these spindle components. The inverse electromagnetic problem was solved using Low-Resolution Brain Electromagnetic Tomography (LORETA). Results indicate separability and stability of sources related to sleep spindle components reconstructed from separate groups of ICs.