Journal of Computer Science & Systems Biology

Scalp-recorded-EEG-based BFCN for Diagnosing AD and FTD Patients and Observing their Prognoses: Preliminary Results

Abstract

Urata R, Toh T, Nakawatase A, Yamazaki T, Kuroiwa Y, Baba Y, Fujino K and Kurokawa T

In order to develop an easier and more inexpensive tool than using MEG and fMRI for diagnosing neurological diseases such as AD and FTD and checking their prognoses in future, we constructed scalp-recorded-EEGbased brain functional connectivity networks (BFCNs), and preliminarily compared Alzheimer’s disease (AD) and frontotemporal dementia (FTD) patients, their prognoses and control subjects by the BFCNs. The present comparison among AD, FTD and older controls roughly supported the previous findings for synchronization likelihood values, unweighted graphs, clustering coefficient and characteristic path length. However, there were reverse differences in small-worldness. For AD and FTD, there were several electrode positions with higher betweenness centrality than the older controls. It might be suggested that we should investigate the betweenness centrality in more details.