Sleep spindles are bursts of quasi-rhythmic activity within the frequency band of 11-16 Hz, characterized by progressively increasing, then gradually decreasing amplitude, present in the sleep electroencephalogram (EEG). The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG and visual selection of Independent Components (ICs), spindle “components” (SCs) corresponding to separate EEG activity patterns during a spindle, and to investigate the intracerebral current sources underlying these SCs. Current source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied to the ICA-reconstructed EEGs. Results indicate that SCs can be extracted by reconstructing the EEG through back-projection of separate groups of ICs, based on temporal and spectral analysis of ICs. The current sources related to the SCs were spatially stable during the evolution of the spindles.