Elisabeth C. W. van Straaten

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We introduce a directed phase lag index to investigate the spatial and temporal pattern of phase relations of oscillatory activity in a model of macroscopic structural and functional brain networks. Direction of information flow was determined with the directed phase lag index (dPLI) defined as the probability that the instantaneous phase of X was smaller(More)
Age-related white matter changes (WMC) are thought to be a marker of vascular pathology, and have been associated with motor and cognitive deficits. In the present study, an optimized artificial neural network was used as an automatic segmentation method to produce probabilistic maps of WMC in a clinical multi-center study. The neural network uses(More)
Brain connectivity studies have revealed that highly connected 'hub' regions are particularly vulnerable to Alzheimer pathology: they show marked amyloid-β deposition at an early stage. Recently, excessive local neuronal activity has been shown to increase amyloid deposition. In this study we use a computational model to test the hypothesis that hub regions(More)
White matter hyperintensities (WMH) are a frequent finding on brain MRI of elderly subjects, and have been associated with various risk factors, as well as with development of cognitive and functional impairment. While an overall association between WMH load and risk factors is well described, possible spatially restricted vulnerability remains to be(More)
The brain is the characteristic of a complex structure. By representing brain function, measured with EEG, MEG, and fMRI, as an abstract network, methods for the study of complex systems can be applied. These network studies have revealed insights in the complex, yet organized, architecture that is evidently present in brain function. We will discuss some(More)
The objective of this study was to examine the differences in oscillatory brain dynamics in Alzheimer's disease (AD) according to age at onset using quantitative electroencephalography (EEG). We examined resting state electroencephalograms of 320 probable AD patients and 246 controls, both categorized into a young (≤ 65 years) and old (> 65 years) group.(More)
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