Differentiation of Dementia Phenotypes Based on EEG Spectral Parameters


  • Ajda Ogrin University of Ljubljana



Dementia is a neurodegenerative disorder characterized by a marked decline in various cognitive domains such as language, memory, attention, visuospatial and executive functions. The first and most frequent sign of dementia is memory loss, however, some patients present with more prominent impairments in other cognitive functions [1]. This cognitive heterogeneity has been shown in various studies and has been linked to various demographic, genetic and neuroimaging characteristics. The two most often identified phenotypic subgroups of dementia are the »amnestic« (patients with memory impairment) and the »non-amnestic« (patients with impairments in other domains) which have different clinical and pathophysiological representations [1, 2]. In terms of electroencephalography (EEG), one of the most described effect of dementia is the »slowing of the brain waves«, i.e. an increase in spectral power in the delta and theta band and a decrease in the alpha and beta [3]. The present study aims to explore whether different phenotypic subgroups of dementia, apart from differences in affected brain regions and demography, also show differences in EEG spectral parameters.


We will perform 24-channel resting state EEG recordings on 400 elderly participants between the ages of 60-90. Separately from EEG we will evaluate their cognitive functions with 4-5 different psychometric tests. Participants with probable dementia according to scores on psychometric tests will be clustered into more homogeneous subgroups in terms of their results on different tasks of psychometric tests given as an input for clustering. EEG recordings will be pre-processed and the selected EEG parameters will be calculated and compared within the clusters. Participants scoring high on psychometric tests will be used as a control.

Expected Results

Based on previous literature, we expect to get at least 2 subgroups from our clustering method, representing the amnestic and the non-amnestic group. Since the literature reports structural differences in affected brain regions between the two groups, we expect to detect some functional changes, i.e. differences in at least some of the selected EEG parameters.


[1] N. M. E. Scheltens et al., “Cognitive subtypes of probable Alzheimer’s disease robustly identified in four cohorts,” Alzheimer’s Dement., vol. 13, no. 11, pp. 1226–1236, 2017. Doi: 10.1016/j.jalz.2017.03.002

[2] J. Y. Park et al., “Robust Identification of Alzheimer’s Disease subtypes based on cortical atrophy patterns,” Sci. Rep., vol. 7, no. 1, pp. 1–14, 2017. Doi: 10.1038/srep43270

[3] F. Vecchio et al., “Resting state cortical EEG rhythms in Alzheimer’s disease: Toward EEG markers for clinical applications: A review,” Supplements to Clinical Neurophysiology, vol. 62, no. 9, pp. 223-236, 2013. Doi: 10.3233/JAD-121750