Background and objectives: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the two most common neurodegenerative dementias. This study focused on changes of brain functional network in two types of dementia.
Methods: We investigated the changes of brain functional networks in two types of dementia using routine preprocessed electroencephalogram (EEG) resting seated state-closed eyes recordings obtained from the OpenNeuro public dataset. This dataset includes 36 patients with AD, 23 patients with FTD and 29 healthy controls (HC). We constructed a functional brain network by computingthe phase-lock value (PLV) in five frequency bands, and calculated topological parameters based on graph theory. The statistical analysis of these graph-theoretic parameters could be used to evaluate the changes of brain functional network in AD patients and FTD patients.
Results: The brain network connectivity of AD, FTD, and HC all increased first and then decreased with the increase of frequency, especially reaching the strongest in the alpha frequency band. Patients with AD and patients with FTD had a significantly weaker value of PLV in the alpha frequency band and showed severe global functional network alterations (lower mean node degree, clustering coefficient, global efficiency, local efficiency, and longer characteristic path length) compared those with controls. Furthermore, AD patients demonstrated a lower mean node degree, clustering coefficient, and local efficiency in all brain regions (frontal, temporal, parietal, occipital, and central lobes), while these changes were observed only in frontal, temporal, parietal, and central regions for FTD patients.
Conclusions: We observed abnormalities of functional network topology and connectivity in AD and FTD, which could contribute to understanding brain’s behavior and its dysfunction in AD and FTD. Futhormore, Patients with AD showed a loss of function in the whole brain, while patients with FTD retained the function of the occipital lobe, which may provide new insights into developing electrophysiological markers for the clinical diagnosis of AD and FTD.