A preliminary Study for Nonlinear Dynamic Analysis of EEG in Patients with Dementia of Alzheimer

ABSTRACT

The changes of electroencephalogram(EEG) in patients with dementia of Alzheimer's type are most commonly studied by analyzing power or magnitude in traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to the chaos theory, irregular signals of EEG can be also resulted from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the largest Lyapunov exponent(L1). The authors have analyzed EEG epochs from three patients with dementia of Alzheimer's type and three matched control subjects. The largest L1 is calculated from EEG epochs consisting of 16.384 data points per channel in 15 channels. The results showed that patients with dementia of Alzheimer's type had significantly lower L1 than non-demented controls on 8 channels. Topographic analysis showed that the L1 were significantly lower in patients with Alzheimer's disease on all the frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer's type have a decreased chaotic quality of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating the L1 can be a promising tool for detecting relative changes in the complexity of brain dynamics.