Microstates and connectivity states reveal task-related network reorganization in Alzheimer's disease patients.

Objective: Microstates derived from EEG amplitude and connectivity states from EEG phase examine distinct aspects of the brain's dynamic organization. However, it is unclear how sensitive they are to changes in functional connectivity in Alzheimer's disease (AD). We examined pre- and post-task alterations of brain activity in AD patients to compare the ability of microstates and connectivity states to capture disease-related network dysfunction. Methods: Resting-state EEG (RS-EEG) was recorded before and after a memory task in fifteen patients with AD and fifteen healthy controls. During the memory task, either low-intensity repetitive transcranial magnetic stimulation (rTMS) over the parieto-occipital region or sham stimulation was applied. We quantified microstates and phase-based connectivity states in the alpha frequency range from the RS-EEG. Results: While microstates showed task-related alterations in healthy controls only, connectivity states were more sensitive to alterations in the AD group. rTMS appeared to reduce these task-related alterations in connectivity states. Connectivity states indicated a shift towards lower, more diffuse connectivity in AD patients. Connectivity states were correlated with memory task performance and amyloid-beta levels in the AD group. Conclusions: Connectivity states indicated decreased task-related network stability in AD patients, which correlated with memory task performance. The findings support the neural efficiency hypothesis, which states that more efficient brain network optimization during tasks is linked to better performance. Significance: Given the progressive decline of alpha power in AD patients, phase-based connectivity states provide valuable complementary information to microstates and may serve as a biomarker for assessing large-scale network alterations in relation to disease progression.