Diagnostic Usefulness of Linear and Nonlinear Quantitative EEG Analysis in Alzheimer's Disease

Abstract

The sensitivity of the EEG in early AD is somewhat limited. In this respect spectral analysis is little better than visual assessment. In this study we address the question whether a new type of EEG analysis derived from chaos theory can improve the sensitivity of the EEG. EEGs were recorded in 15 control subjects and 15 patients with mild AD. The EEG recorded at 02 and 01 during eyes closed and eyes open conditions was subjected to spectral analysis (relative power) and nonlinear analysis (calculation of the correlation dimension D2). AD patients had more relative theta power and impaired reactivity in alpha, delta and theta bands. Also, reactivity of the D2 was impaired in AD subjects. For a specificity of 100%, relative theta power had the highest sensitivity (46.7%). Alpha band reactivity at O1 had a sensitivity of 40% and D2 reactivity at O1 had a sensitivity of 33.3%. Combining theta power with alpha reactivity resulted in a sensitivity of 53.3%; combining theta with D2 reactivity resulted in a sensitivity of 60%. Used in isolation, linear analysis was superior in differentiating AD patients from controls. The best results were obtained by combining linear with nonlinear measures. This approach does not seem practical yet, but deserves further study.

Electroencephalogram and Alzheimer’s Disease: Clinical and Research Approaches

“…This is the reason why some clinicians suggest that all AD patients should be subjected to an EEG at least once as well as to a MRI [5, 6]. On the other hand the rate of correctly identified AD cases by electrophysiological methods varies within a wide range, between 29% and 42% in the early and between 60% and 80% in the later stages [7]. …”

Quantitative EEG in early Alzheimer's disease patients — Power spectrum and complexity features

“…The rate of correctly identified AD-cases by electrophysiological methods varies within a wide range, between 29% and 42% in the early and between 60% and 80% in the later stage (Stam et al, 1996). The most frequently observed spectral change is the "slowing" of the EEG, which supposedly correlates with the degree of cognitive decline (Bennys et al, 2001).…”

Nonlinear EEG Analysis and Its Potential Role in Epileptology

“…Apart from physics, examples range from cardiology (20,21) to neurologic and psychiatric disorders such as Alzheimer's disease (22,23), Parkinson's disease (24,25), CreutzfeldJakob disease (26), and schizophrenia (27)(28)(29). In epileptology, NTSA of EEG data recorded in experimental animals has led to a better understanding of basic mechanisms (30)(31)(32).…”