Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer’s and Lewy Body Diseases

Abstract

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.

Quantitative EEG as a biomarker in mild cognitive impairment with Lewy bodies

“…These ndings are consistent with results from previous EEG studies at the dementia stage which generally report an increase in slow-wave activity and slowing of the dominant EEG rhythm in DLB [10,[19][20][21]. A slowing of the dominant frequency has also been reported in MCI-LB patients before [22].…”

“…Work in this eld will undoubtedly yield bene ts similar to those seen with CSF biomarkers for example [25]. More complex EEG analyses such as functional connectivity or source-reconstruction methods may provide better sensitivity for detecting differences between the two MCI groups as well as between MCI-AD patients and controls [22,26]. Furthermore, multimodal approaches including EEG features in addition to MIBG/FP-CIT or structural MRI markers may be another route by which it will be possible to achieve better accuracy for early distinction between AD and DLB at the MCI stage.…”

“…Another previous EEG study that attempted to differentiate MCI-AD from MCI-LB did not nd any EEG measures that reliably distinguished between the two MCI subgroups [22]. However, this was a retrospective study of selected MCI-AD and MCI-LB patients who were recruited using clinical criteria which differed across the several centers who supplied patient data.…”

“…However, this was a retrospective study of selected MCI-AD and MCI-LB patients who were recruited using clinical criteria which differed across the several centers who supplied patient data. Furthermore, participants from the different centers were also assessed using different EEG protocols which again makes comparison di cult [22].…”

Music Training, Working Memory, and Neural Oscillations: A Review

“…Alpha peak frequency could also serve as a potential biomarker for mild cognitive impairment (MCI) (Babiloni et al, 2018) as it is lower for the MCI population than for normal older adults, as well as being correlated with MMSE scores. Furthermore, APF in posterior sites is positively correlated with hippocampal volume, which is reduced in the mild cognitively impaired population (Garcés et al, 2013).…”