Analysis of spontaneous MEG activity in patients with Alzheimer's disease using spectral entropies.

The aim of this study was to explore the ability of several spectral entropies to discriminate between spontaneous magnetoencephalographic (MEG) oscillations from 20 Alzheimer's disease (AD) patients and 21 controls. Hence, the relative spectral power (RSP) in classical frequency bands was calculated from the averaged power spectral density. Given the fact that the RSP can be viewed as a probability distribution function, the Shannon spectral entropy, Tsallis spectral entropy, generalized escort-Tsallis spectral entropy and Rényi spectral entropy were calculated from the RSP. Significant differences for each parameter were assessed with Mann-Whitney U test, whereas classification performance was studied using binary logistic regression. Results revealed an increase in the RSP of control subjects at beta and gamma bands, while AD patients showed an increase in the RSP values at delta and theta bands. Entropies obtained statistically significant lower values for AD patients than for controls. This issue suggests a significant decrease in irregularity of AD patients' MEG activity.