Alzhemimer’s Disease is Characterized by Lower Segregation in Resting-State Eyes-Closed EEG

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.