Electroencephalographic (EEG) changes with normal aging have long been reported. Departures from age-expected changes have been observed in mild cognitive impairment and dementia, the magnitude of which correlates with the degree of cognitive impairment. Such abnormalities include increased delta and theta activity, decreased mean frequency, and changes in coherence. Similar findings have been reported using magnetoencephalography (MEG) at rest and during performance of mental tasks. Electrophysiological features have also been shown to be predictive of future decline in mild cognitive impairment (MCI) and Alzheimer's disease (AD). We have recently reported results from initial quantitative electroencephalography (QEEG) evaluations of normal elderly subjects (with only subjective reports of memory loss), predicting future cognitive decline or conversion to dementia, with high prediction accuracy (approximately 95%). In this report, source localization algorithms were used to identify the mathematically most probable underlying generators of abnormal features of the scalp-recorded EEG from these patients with differential outcomes. Using this QEEG method, abnormalities in brain regions identified in studies of AD using MEG, MRI, and positron emission tomography (PET) imaging were found in the premorbid recordings of those subjects who go on to decline or convert to dementia.