In our study we examined the linear and non-linear characteristics of EEG signals derived from patients with Alzheimer's disease (AD) with the future aim of developing a widely available method for monitoring therapy and the progression of the disease or to be used even for the purposes of differential diagnosis. EEG was recorded with eyes closed and eyes open conditions ("resting") in a group of patients with early-stage AD and in healthy control subjects matched by age. In addition to the conventional methods of analysis (frequency spectrum, coherence), the so-called complexity measures developed in recent years (Omega-complexity, synchronised probability) have also been determined. By means of frequency spectrum analysis, we managed to detect the slowdown of EEG in the early stage of dementia, a feature that so far has been associated with the later stages of AD. Coherence was reduced in the majority of frequency bands in the patient group; however, this difference could be observed only in some of the leads. Thus, resting EEG coherence is less suitable for separating various stages than the other methods. Complexity features have shown the most robust changes in Alzheimer's disease in our investigation. Besides the reduction in synchronised probability, significantly higher values of Omega-complexity were obtained in the patient group. This may be associated with the impairment of cortical afferentation (cholinergic and monoaminergic) and with the reduction in the number of neurons and synapses. Our methods have proved to be very sensitive to quantify these changes.
|Translated title of the contribution||Quantitative EEG analysis in Alzheimer's disease: spectral, coherence and complexity parameters|
|Number of pages||13|
|Journal||Psychiatria Hungarica : A Magyar Pszichiátriai Társaság tudományos folyóirata|
|Publication status||Published - 2006|
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