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Relationship between default mode network and resting-state electroencephalographic alpha rhythms in cognitively unimpaired seniors and patients with dementia due to alzheimer’s disease

Lookup NU author(s): Professor John-Paul TaylorORCiD, Julia SchumacherORCiD, Professor Ian McKeith

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

© The Author(s) 2023.Here we tested the hypothesis of a relationship between the cortical default mode network (DMN) structural integrity and the resting-state electroencephalographic (rsEEG) rhythms in patients with Alzheimer’s disease with dementia (ADD). Clinical and instrumental datasets in 45 ADD patients and 40 normal elderly (Nold) persons originated from the PDWAVES Consortium (www.pdwaves.eu). Individual rsEEG delta, theta, alpha, and fixed beta and gamma bands were considered. Freeware platforms served to derive (1) the (gray matter) volume of the DMN, dorsal attention (DAN), and sensorimotor (SMN) cortical networks and (2) the rsEEG cortical eLORETA source activities. We found a significant positive association between the DMN gray matter volume, the rsEEG alpha source activity estimated in the posterior DMN nodes (parietal and posterior cingulate cortex), and the global cognitive status in the Nold and ADD participants. Compared with the Nold, the ADD group showed lower DMN gray matter, lower rsEEG alpha source activity in those nodes, and lower global cognitive status. This effect was not observed in the DAN and SMN. These results suggest that the DMN structural integrity and the rsEEG alpha source activities in the DMN posterior hubs may be related and predict the global cognitive status in ADD and Nold persons.

Publication metadata

Author(s): Babiloni C, Lopez S, Noce G, Ferri R, Panerai S, Catania V, Soricelli A, Salvatore M, Nobili F, Arnaldi D, Fama F, Massa F, Buttinelli C, Giubilei F, Stocchi F, Vacca L, Marizzoni M, D'Antonio F, Bruno G, De Lena C, Guntekin B, Yildirim E, Hanoglu L, Yener G, Yerlikaya D, Paul Taylor J, Schumacher J, McKeith I, Bonanni L, Pantano P, Piervincenzi C, Petsas N, Frisoni GB, Del Percio C, Carducci F

Publication type: Article

Publication status: Published

Journal: Cerebral Cortex

Year: 2023

Volume: 33

Issue: 20

Pages: 10514-10527

Print publication date: 15/10/2023

Online publication date: 23/08/2023

Acceptance date: 27/07/2023

Date deposited: 14/11/2023

ISSN (print): 1047-3211

ISSN (electronic): 1460-2199

Publisher: Oxford University Press

URL: https://doi.org/10.1093/cercor/bhad300

DOI: 10.1093/cercor/bhad300

Data Access Statement: Datasets are available under scientific agreement with the corresponding author.

PubMed id: 37615301

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