High-Density EEG Signal Processing Based on Active-Source Reconstruction for Brain Network Analysis in Alzheimer’s Disease

Abstract

Alzheimer’s Disease (AD) is a neurological disorder characterized by a progressive deterioration of brain functions that affects, above all, older adults. It can be difficult to make an early diagnosis because its first symptoms are often associated with normal aging. Electroencephalography (EEG) can be used for evaluating the loss of brain functional connectivity in AD patients. The purpose of this paper is to study the brain network parameters through the estimation of Lagged Linear Connectivity (LLC), computed by eLORETA software, applied to High-Density EEG (HD-EEG) for 84 regions of interest (ROIs). The analysis involved three groups of subjects: 10 controls (CNT), 21 Mild Cognitive Impairment patients (MCI) and 9 AD patients. In particular, the purpose is to compare the results obtained using a 256-channel EEG, the corresponding 10–10 system 64-channel EEG and the corresponding 10–20 system 18-channel EEG, both of which are extracted from the 256-electrode configuration. The computation of the Characteristic Path Length, the Clustering Coefficient, and the Connection Density from HD-EEG configuration reveals a weakening of small-world properties of MCI and AD patients in comparison to healthy subjects. On the contrary, the variation of the network parameters was not detected correctly when we employed the standard 10–20 configuration. Only the results from HD-EEG are consistent with the expected behavior of the AD brain network.

Regional Disconnection in Alzheimer Dementia and Amyloid-Positive Mild Cognitive Impairment: Association Between EEG Functional Connectivity and Brain Glucose Metabolism

“…The second measure from LORETA toolbox, named lagged linear connectivity, measures the statistical linear dependence between cortical source activities after the instantaneous zero-lag contribution has been removed, and therefore eliminates volume conduction effect (Pascual-Marqui, 2007b ; Pascual-Marqui et al, 2011 ). Lagged linear connectivity measure, as estimated by LORETA software, has been successfully employed in several EEG studies on functional cortical connectivity in AD patients (Babiloni et al, 2018a ,b; Foresta et al, 2019 ).…”

Testing Graph Robustness Indexes for EEG Analysis in Alzheimer’s Disease Diagnosis

“…As for Alzheimer's Disease, brain networks are characterized by a weakening of the small-world properties as compared with healthy subjects [21][22][23]. Moreover, studies which compared healthy people, MCI, and AD patients have shown that MCI topological properties are intermediate [24][25][26]. Extensive reviews about graph theory applied to functional connectivity analysis in AD are provided in [27][28][29].…”

Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges

“…Frequently, it is used in the evaluation of Alzheimer's disease progress or even in its prognosis, since the brain activation related to cognitive performance is commonly altered in the disease's progression [63]. As such, eLORETA and connectivity analysis has been adopted for Alzheimer's disease diagnosis [64,65]. Another interesting approach is the use of ESI in localizing the origin of epileptic spikes using the differences created by non-Rapid Eye Movement (NREM) and Rapid Eye Movement (REM) sleep [66].…”