Alzheimer Disease Progression in Patients With MCI Predicted by EEG, Language Deficits
Those with MCI and subsequent Alzheimer disease development had significantly diminished theta increase vs healthy controls.
Oscillatory changes in electroencephalogram (EEG) recordings as well as language deficits demonstrated during normal word processing may hold predictive value for Alzheimer disease in patients with mild cognitive impairment (MCI), according to an analysis published in NeuroImage: Clinical.
Investigators compared initial baseline EEG recordings of 25 patients with amnestic MCI with those of generally healthy elderly controls (n=11). The researchers obtained data from a previous study that specifically examined the ability of response patterns to predict dementia during a 3-year period.
Participants were asked to respond to an auditory category description with a visual target word to assess deficits in language processing.
As evidenced by EEG recordings, participants with MCI in whom Alzheimer disease developed at 3 years were more likely to demonstrate diminished theta increase compared with people in whom the disease did not develop (22% increase vs 50% increase, respectively; P =.046).
In addition, those with MCI and subsequent Alzheimer disease development had significantly diminished theta increase vs healthy controls (22% increase vs 59% increase, P =.004).
With regard to congruent vs incongruent target words, the researchers observed greater beta suppression among MCI converters than MCI nonconverters (-10% vs 3%, respectively; P =.017). Additionally, participants in whom MCI converted to Alzheimer disease demonstrated typical anomalies for meaning and lexical processing.
The findings of this study hint that the “breakdown of the brain network subserving language comprehension could be foretelling of the emergence of Alzheimer disease as well as the underlying memory failures observed in these patients in the prodromal stage of the disease.”
Mazaheri A, Segaert K, Olichney J, et al. EEG oscillations during word processing predict MCI conversion to Alzheimer's disease. NeuroImage: Clinical. 2018;17:188-197.