Spectral and non-linear analyses of spontaneous magnetoencephalographic activity in Alzheimer's disease

Abstract

Alzheimer's Disease (AD) is considered the most prevalent form of dementia. A definite AD diagnosis is established after examination of brain tissue. However, an accurate identification should be attempted to effectively apply therapeutic strategies. The aim of the present study was to perform regional analysis of spontaneous magnetoencephalographic (MEG) activity to describe brain dynamics in AD. Several spectral and non-linear parameters were calculated to obtain a comprehensive description of the spatial abnormalities in brain dynamics. Our findings showed a significant global slowing of MEG activity in AD, as well as a significant loss of irregularity and complexity in several brain regions. Spectral and non-linear parameters reached classification accuracies of around 80%. The results suggest the potential usefulness of spectral and non-linear parameters to characterize the cognitive and functional abnormalities of dementia. These parameters can yield information useful in clinical AD diagnosis and provide further insights on underlying brain dynamics.