Patients With Alzheimer's Disease Dementia Show Partially Preserved Parietal 'hubs Modeled From Resting-State Alpha Electroencephalographic Rhythms
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Date
2023
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Frontiers Media Sa
Open Access Color
GOLD
Green Open Access
Yes
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Publicly Funded
No
Abstract
IntroductionGraph theory models a network by its nodes (the fundamental unit by which graphs are formed) and connections. 'Degree' hubs reflect node centrality (the connection rate), while 'connector' hubs are those linked to several clusters of nodes (mainly long-range connections). MethodsHere, we compared hubs modeled from measures of interdependencies of between-electrode resting-state eyes-closed electroencephalography (rsEEG) rhythms in normal elderly (Nold) and Alzheimer's disease dementia (ADD) participants. At least 5 min of rsEEG was recorded and analyzed. As ADD is considered a 'network disease' and is typically associated with abnormal rsEEG delta (<4 Hz) and alpha rhythms (8-12 Hz) over associative posterior areas, we tested the hypothesis of abnormal posterior hubs from measures of interdependencies of rsEEG rhythms from delta to gamma bands (2-40 Hz) using eLORETA bivariate and multivariate-directional techniques in ADD participants versus Nold participants. Three different definitions of 'connector' hub were used. ResultsConvergent results showed that in both the Nold and ADD groups there were significant parietal 'degree' and 'connector' hubs derived from alpha rhythms. These hubs had a prominent outward 'directionality' in the two groups, but that 'directionality' was lower in ADD participants than in Nold participants. DiscussionIn conclusion, independent methodologies and hub definitions suggest that ADD patients may be characterized by low outward 'directionality' of partially preserved parietal 'degree' and 'connector' hubs derived from rsEEG alpha rhythms.
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Keywords
resting-state eyes closed electroencephalographic (rseeg) rhythms, alzheimer's disease with dementia (add), interdependencies of rseeg rhythms, linear lagged connectivity, graph theory, hub topology, Mild Cognitive Impairment, Graph-Theoretical Analysis, White-Matter Lesions, Human Brain Networks, Lewy Body Diseases, Functional Connectivity, Eeg Coherence, Cortical Connectivity, Quantitative Eeg, Neural Synchronization, Interdependencies of Rseeg Rhythms, interdependencies of rseeg rhythms, graph theory, Aging Neuroscience, interdependencies of rseeg rhythm, Neurosciences. Biological psychiatry. Neuropsychiatry, Alzheimer’s Disease With Dementia (Add), Alzheimer’s Disease With Dementia (ADD), Linear Lagged Connectivity, resting-state eyes closed electroencephalographic (rseeg) rhythms, alzheimer’s disease with dementia (add), Resting-State Eyes Closed Electroencephalographic (Rseeg) Rhythms, Graph Theory, linear lagged connectivity, hub topology, Hub Topology, alzheimer’s disease with dementia (add); graph theory; hub topology; interdependencies of rseeg rhythms; linear lagged connectivity; resting-state eyes closed electroencephalographic (rseeg) rhythms, RC321-571
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Fields of Science
03 medical and health sciences, 0302 clinical medicine
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OpenCitations Citation Count
2
Source
Frontıers in Agıng Neuroscıence
Volume
15
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Scopus : 6
PubMed : 1
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