Electroencephalogram mutual information entropy analysis for Alzheimer's disease

To investigate the electroencephalogram (EEG) records in Chinese Han ethnic Alzheimer's disease (AD) patients, a nonlinear feature investigation of the resting EEG was carried out on local AD (NINCDS-ADRDA criteria) patients. The age matched normal elderly subjects served as controls. An estimator of mutual information entropy was introduced to quantify the nonlinear characteristics of time series of the recorded EEG data to address randomness and predictability of brain activities. Results showed that local AD patients exhibited abnormal nonlinear EEG patterns typical of decreased nonlinear dynamic characters with lower mutual information entropies in comparison to the normal, especially in those data collected from the electrode Fp1, Fp2, T3 and T4 (P<;0.05). The averaged amplitude of the entropy decreases was more than 20 percent in all these four electrode positions. The progresses in this study may provide some evidence of specific changes of EEG affected by AD in Chinese.