Nonlinear EEG analysis in early Alzheimer's disease

Nonlinear EEG analysis attempts to characterize the dynamics of neural netw orks in the brain. Abnormalities in nonlinear EEG measures have been found repeatedly in Alzheimer's disease (AD). The present study was undertaken to investigate whether these abnormalities could already be found in the earl y stage of AD. In a representative sample of 49 community-dwelling elderly, Alzheimer's disease was diagnosed in 7 subjects. Correlation dimension (D- 2) and nonlinear prediction were measured at 16 electrodes and in two diffe rent activational states. Also, 10 surrogate data sets were generated for e ach EEG epoch in order to investigate the presence of nonlinear dynamics. D ifferences between nonlinear statistics derived from original and from surr ogate data sets were expressed as Z-scores. We found lower D-2 and higher p redictability in the demented subjects compared to the normal subjects. The results obtained with the Z-scores pointed to changed nonlinear dynamics i n frontal and temporal areas in demented subjects. However, the major diffe rences between demented and healthy subjects are not due to nonlinearity. F rom this it appears that linear dynamics change first in the course of AD, followed by changes in nonlinear dynamics.