The objective of the present study was to elucidate evidence of and to revisit chaotic itinerancy in human brains by means of noninvasive scalp electroencephalogram (EEG) in normal subjects; with the assumed tenet that chaotic itinerancy occurs in sequences of cortical states marked by state transitions that appear as temporal discontinuities in neural activity patterns. The present study was based on unprecedented advances in spatial and temporal resolution of the phase of oscillations in scalp EEG. The EEG data was processed and modeled by the technique of curve fitting and temporal resolution was advanced by the use of Hilbert Transform (in Matlab version 7.0), which re-affirmed the variations in phase and amplitude in all scalp EEG electrical signals from 0 through 99 Hz frequencies. The numerical derivative of the analytic phase revealed plateaus in phase. The plateaus were bracketed by sudden jumps in phase. The widespread synchrony of the jumps in analytic phase manifests a metastable cortical state in accord with the theory of self-organized criticality. The jumps appear to be subcritical bifurcations. They reflect the aperiodic evolution of brain states through sequences of attractors that on access support the experience of remembering. State changes resembling phase transitions occur continually everywhere in cortex. Only the largest and longest-lasting state appears in scalp EEG, giving the appearance of chaotic itinerancy. The 1/fα spatial and temporal spectra of scalp EEG denote that brain maintains a state of self-organized criticality (SOC) as the basis of its capacity for rapid adjustment to environmental changes.