Analysis of spontaneous MEG activity in Alzheimer's disease using time-frequency parameters

The aim of this study was to explore the ability of several time-frequency parameters to discriminate between spontaneous magnetoencephalographic (MEG) oscillations from 20 Alzheimer's disease (AD) patients and 21 controls. The spectral crest factor (SCF) and the spectral turbulence (ST) were calculated from the time-frequency distribution of the normalized power spectral density averaged over all MEG sensors. Results revealed statistically significant higher SCF and ST mean values for AD patients than controls (p 0.05). This fact suggests a significant decrease in irregularity of AD patients' MEG activity. The standard deviation of SCF also provided significant differences (p 0.05). This result indicates that AD patients showed a significantly higher variability than controls. The highest accuracy of 85.4% (90.5% sensitivity, 80.0% specificity) was achieved using simultaneously the mean value and the standard deviation of the SCF. We conclude that the variability of the spectral parameters can yield complementary information to the mean values, useful to help in AD detection.