Nonlinear dynamic analysis of resting EEG alpha activity for heroin addicts

Abstract

It has been reported that chronic heroin intake induces changes in central nervous system of human brain; however, few studies investigate the carry-over adverse effects on brain after heroin withdrawal. In this work we examined the alpha rhythms of resting-state Electroencephalogram (EEG) signals to measure the neuroelectrical differences between the heroin addicts after heroin withdrawal and normal control. Eyes-closed resting EEG signals from 20 heroin addicts with the abstinence length ranging from 4–16 months and 20 normal controls were recorded using 64 electrodes. Comparing the nonlinear characteristics of EEG signals, such as the correlation dimension, Kolmogorov entropy and Lempel-Ziv complexity, we found that the EEG signals from heroin addicts were significantly more irregular than those from normal controls. Furthermore, the topography of the each nonlinear feature was examined, and the abnormal changes were widely spread over the brain. These findings suggest that nonlinear methods may contribute to gain new insights into brain dysfunction in heroin addicts even after heroin abstinence.