Research Information System
JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING, vol.44, pp.894-902, 2024 (SCI-Expanded, Scopus)
https://link.springer.com/article/10.1007/s40846-024-00917-0
Purpose: The goal of the present study is to quantify
the close association between graph theoretic global brain connectivity
measures and Alzheimer's Disease (AD) in comparison to Controls.
Methods: International Mini-Mental State Examination
(MMSE) was used to evaluate cognitive and neuropsychological state of the
participants (AD, 12 men, 24 women, mean age = 66.4, sd = 7.9 and controls, 18
men, 11 women, mean age = 67.9, sd = 5.4). There are no comorbidities in
patients. Eyes-closed 19-channel surface EEG series were collected from the 2nd
Department of Neurology of AHEPA General Hospital of Thessaloniki by
experienced neurologists. 2 min long resting-state recordings have been
analyzed through non-overlapped sliding window of 1 second and graph theoretical
connectivity indices have been estimated by using Directed Transfer Function
(DTF) combined with Brain Connectivity Toolbox. EEG recordings and clinical
test scores of the individuals were both downloaded from a public dataset on
OpenNeuro platform (A dataset of EEG recordings from: Alzheimer's disease,
Frontotemporal dementia and Healthy subjects. https://doi.org/10.18112/openneuro.ds004504.v1.0.7.).
Results: AD provided the lower measures in terms of
Global Efficiency, Local Efficiency (LE) and Cluster Coefficients. LE
estimations provided meaningful and significant statistical difference between
patients and controls in theta (4.5-8 Hz), alpha (8.5-12 Hz), beta (12.5-30
Hz), gamma (30.5-45 Hz) sub-bands.
Conclusion: The patients provided the lower segregation
and integration measures than controls due to loss of connection. AD induces
the considerable decrease in segregation. The brain fails to integrate cortical
regions into effective networks since there is synaptic disconnection as
neuropathology of AD.