Functional EEG connectivity alterations in Alzheimer’s disease

Abstract

Quantitative EEG analyses, especially connectivity and graph analyses, are promising biomarkers in neurodegenerative disorders such as Alzheimer’s disease. To develop reliable and valid biomarkers, many aspects in pre- and post-processing of EEG data are important. Artifact detection and segment selection are done by visual inspection or automated routines, both with specific advantages and difficulties. Inverse solution is an elegant way of solving the issue of common source but may be somewhat imprecise in the absence of defined graphoelements such as epileptiform discharges. Connectivity analyses allow a description of interactions between brain regions, which may represent one of the earliest signs of cognitive decline.