Intriguingly, recent studies have shown that EEG/MEG network topologies change over the course of a lifetime (Micheloyannis et al., 2009), and that individual differences in graph theoretic network properties may be related to intelligence (IQ) and cognitive performance (Micheloyannis et al., 2006b; Bassett et al., 2009). A number of recent papers have suggested that alterations in EEG network properties may be seen in various neuropsychiatric diseases. In Alzheimer’s disease, EEG functional connectivity (fcEEG) analysis has shown promise as a diagnostic aid in early stages of the disease (Dauwels et al., 2010). In another fcEEG study, the severity of cognitive dysfunction in Alzheimer’s disease was found to be a monotonically decreasing function of path length, while the average clustering coefficients were similar to control subjects, suggesting that Alzheimer’s dementia may be related to loss of “small-worldliness” (Stam et al., 2007). To a lesser degree, loss of small-worldliness and lower levels of synchronization within high frequency EEG rhythms (beta and gamma) has also been reported in normal aging (Micheloyannis et al., 2009). As another example, in patients presenting after a first seizure,
