Difference of quantitative EEG between Alzheimer's disease (AD) dementia and non‐dementia AD: Neuroimaging / New imaging methods. (7th December 2020)

• Record Type: Journal Article
• Authors: Kang, Seung Wan; Choi, Seong Hye; Jeong, Jee Hyang; Jang, Jae‐Won; Park, Kyung‐Won; Kim, Eun‐Joo; Kim, Hee Jin; Hong, Jin Yong; Yoon, Soo Jin; Yoon, Bora; Kang, Dong Won
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 4
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.044300
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD) is the most common cause of dementia. However, accumulation of beta amyloid plague in the brain which is main pathology of AD could show the various spectrum of cognitive functional stage from preclinical level to overt dementia. It is important to understand functional differences between dementia and non‐dementia of AD to predict progression forward to dementia at prodromal or preclinical stage of AD. Method: Nineteen channels of resting state EEGs were measured from 45 Alzheimer's disease subjects who were all confirmed by brain amyloid‐beta PET. Neurocognitive test, activity of daily living (ADL) and MRI were conducted for clinical diagnosis. EEG power spectrum analysis and band‐power ratio, cortical source current density estimated by standardized low resolution brain electromagnetic tomography(sLORETA), functional connectivity between 68 region of interest (ROI) based on imaginary coherence(iCoh) and complex brain networks were analyzed. Result: 20 AD subjects (age: 76.8±7.54) were assessed as dementia, and the other 25 (age: 72.1±6.89) as mild cognitive impairment (MCI) or subjective cognitive decline (SCD) depending on delayed recall memory score. Average CDR was 0.23 in non‐dementia and 1.15 in dementia group. There was no significant difference at delta, but theta power of AD dementia group was significantly increased at all 19 scalp channels. Mid frontal channel (Fz) showed the most distinctive enhancement of theta power. In other hands, beta1 (12∼15Hz) was significantly increased at both temporoparietal area in non‐dementia AD group. These patterns about theta increase and beta 1 decrease in AD dementia group were observed very similarly in cortical source current density. iCoh among ROIs of default mode network (DMN) was significantly decreased at alpha2 band (10∼12Hz). At bilateral frontal pole, rostral middle frontal, anterior cingulate, parahippocampus and precuneus, the degree centrality and characteristic path length significant increased at theta band. In contrast, theta of cluster coefficient and closeness centrality significantly decreased. Conclusion: AD dementia showed increase of theta and decrease of bet1 both at scalp and cortical level comparing to non‐dementia AD subjects. Both global and local network efficiencies via theta wave were significantly deteriorated in AD dementia. QEEG could well discriminate the differences between dementia and non‐dementia in ADs.