P132. Microstates connectivity alterations in patients with early Alzheimer’s disease
Introduction EEG microstates and brain network analyses are known to differentiate patients with Alzheimer’s disease (AD) and healthy controls (HC) and are potential biomarkers of AD. Microstates correspond to defined states of brain activity, and connectivity patterns may change accordingly. To our knowledge, the two methods were not yet combined. Furthermore, little is known about their alterations in early AD. Objective/aims To compare brain network connectivities between early AD and age-matched HC in microstates. Methods 32 outpatients with early AD (mean age 77 ± 7, 47% male, MMS 24–30) and 32 HC were matched for age, gender and education. Diagnosis of AD was made after comprehensive neuropsychological and clinical examinations, and only patients with cognitive decline over 30 months were included. Resting state EEG was recorded with 256 electrodes and analyzed using Matlab®. Five microstates were defined and individual data fitted. After phase transformation, the phase lag index (PLI) was calculated for continuous data and for the five microstates in every subject. Networks were reduced to 22 nodes for statistical analysis. Results After correction for multiple comparisons, no significant differences in connectivities using continuous data were found. Using connectivities from microstates, significant differences in theta and alpha1 band were detected. Connectivities were higher in the AD than in the HC group. Conclusions The combination of microstates and connectivity analyses differentiates between HC and AD patients at the earliest stage of disease (MMS ⩾ 24). Adding microstates information to connectivity analysis may increase sensitivity of quantitative EEG characterization of AD.