Abstract
A pattern of components from brain event-related potentials (ERPs) (cognitive non-invasive electrical brain measures) performed well in separating early-stage Alzheimer's disease (AD) subjects from normal-aging control subjects and shows promise for developing a clinical diagnostic for probable AD. A Number–Letter task elicited brain activity related to cognitive processes. In response to the task stimuli, brain activity was recorded as ERPs, whose components were measured by principal components analysis (PCA). The ERP component scores to relevant and irrelevant stimuli were used in discriminant analyses to develop functions that successfully classified individuals as belonging to an early-stage Alzheimer's disease group or a like-aged Control group, with probabilities of an individual belonging to each group. Applying the discriminant function to the developmental half of the data showed 92% of the subjects were correctly classified into either the AD group or the Control group with a sensitivity of 1.00. The two crossvalidation results were good with sensitivities of 0.83 and classification accuracies of 0.75–0.79. P3 and CNV components, as well as other, earlier ERP components, e.g. C145 and the memory “Storage” component, were useful in the discriminant functions.
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