Multiscale permutation entropy analysis of the EEG in early stage alzheimer's patients

Alzheimer's Disease (AD) is a neurodegenerative disorder associated with a progressive loss of cognitive function. Early identification of AD, when symptoms are mild, can be difficult. Therefore, the development of clinically useful measures are necessary to improve diagnosis of the disease and to allow for early clinical intervention, as well as to aid in drug development. The aim of this study is to analyse the electroencephalography (EEG) of patients with mild AD while they were engaged in a memory task, and to contrast these results with those from cognitively healthy control subjects. We introduce a novel application of the Multiscale Permutation Entropy (MPE) analysis to the EEG signal of patients and controls during task execution, which allows us to compare the complexity of the underlying brain signals at multiple temporal scales. These complexity results are then correlated with cognitive behavioral measures to evaluate the correspondence between complexity and cognitive performance.