Presenting tone triplets of identical stimuli preceded by silent intervals of 30 s produces a series of three N1 averaged event-related potentials (ERPs), the first being of greater amplitude (non-suppressed N1) than the second and third ones (suppressed N1). Maximal statistically independent components (ICs) of single-trial multi-electrode scalp EEG responses to triplets were obtained by ICA algorithm, and then each IC was searched for underlying brain structures by LORETA inverse solution, and for oscillatory contributions by time-frequency analysis. Non-suppressed N1 cortical mechanisms were broken down into five ICs, grouped in two time-windows (early-onset and late-onset) involving the participation of temporal, frontal and parietal structures, and sub-serving EEG oscillatory contributions of power enhancement and putative phase concentration of mainly theta, alpha and low beta bands. Suppressed N1 was due to the modulation of two above-mentioned early-onset ICs, involving temporal structures only, and mainly sub-serving oscillatory contributions of phase concentration of theta and alpha. Present results, showing quantifiable changes of IC descriptors – i.e. time window of activation, implied structures and oscillatory contributions – extracted from two distinct brain functional situations (non-suppressed versus suppressed N1), give support to the view that ICA is not merely a statistical “latent variables” model when applied to ERPs, but could help to capture underlying specific function subunits of brain dynamics.