LPVG analysis of the EEG activity in Alzheimer's disease patients

In this paper limited penetrable visibility graph (LPVG) approach is introduced to analyze the background electroencephalograph (EEG) activity in Alzheimer's disease (AD) patients. LPVG provides a measure of transforming the time series, i.e., EEG, into complex networks, which has become a research hotspot in the field of cognitive neurodynamics. So in this work, LPVG is chosen as the center method to transform every EEG signal of AD patients and normal controls into a complex network. Then distinction could be made between the two groups through the comparison of the GIC value and the topological features of the networks by statistical analysis. It is demonstrated that the complex network extracted from EEG signals of AD brain has been altered significantly. In particular, the small-world properties are weakened in AD group compared with the control group. These preliminary results may contribute to providing a new imaging marker in view of complex network for the clinical diagnosis of AD.