The electrophysiological data from a study of source memory in young and older adults were analyzed in the frequency domain in order to find functional networks of alpha band activity related to source memory performance and cortical reorganization with age. Participants were instructed to remember noun pairs embedded in sentences, with sentences grouped into two temporally distinct lists. At test, in response to noun probes, participants made old/new, followed by source (i.e., list) judgments. Lower band alpha electroencephalography (EEG) recorded during recognition and source retrieval epochs was analyzed using spatial covariance analysis [Hum. Brain Mapp. 2 (1994) 79; J.R. Moeller, C. Ghez, A. Antonini, M.F. Ghilardi, V. Dhawan, K. Kazumata, D. Eidelberg, Brain networks of motor behavior assessed by principal component analysis, in: R.E. Carson, M.E. Daube-Witherspoon, P. Herscovitch (Eds.), Quantitative Functional Brain Imaging with Positron Emission Tomography, Academic, San Diego, 1998]: significant activation patterns were found in source retrieval epochs. For young subjects, the regional covariance pattern involved coactivation of right anterior and left posterior electrode sites. Source retrieval performance was predicted by the subject difference in pattern expression between epochs involving correct and incorrect source attribution. The older adults also exhibited significant coactivation of the right anterior and left posterior electrode sites. However, no compensatory activation sites were identified for these elders who performed near chance in source retrieval. In this regard, we replicated the main functional difference between good and poor performing elders reported in a recent O-15 PET study of source retrieval in young and older subjects [Neuroimage 17 (2002) 1394]. These alpha band and O-15 PET findings complement the age group differences found in the time-domain (ERP) analysis of our EEG data [Psychol. Aging 14 (1999) 390]. We suggest that spatial covariance analyses of spectral EEG and MEG data will reveal new information about functional brain activity relevant to normal aging.