The human brain is a large-scale system of functionally connected brain regions. This
system can be modeled as a network, or graph, by dividing the brain into a set of regions, or …

The detection of mild cognitive impairment (MCI), the transitional stage between normal
cognitive changes of aging and the cognitive decline caused by AD, is of paramount clinical …

The decoding of conscious experience, based on non-invasive measurements, has become
feasible by tailoring machine learning techniques to analyse neuroimaging data. Recently …

Cross-frequency coupling (CFC) is thought to represent a basic mechanism of functional
integration of neural networks across distant brain regions. In this study, we analyzed CFC …

We analyse statistical and information-theoretical properties of EEG microstate sequences,
as seen through the lens of five different clustering algorithms. Microstate sequences are …

Functional connectivity (FC), defined as the statistical dependency between distinct brain
regions, has been an important tool in understanding cognitive brain processes. Most of the …

In the study of brain functional connectivity networks, it is assumed that a network is built
from a data window in which activity is stationary. However, brain activity is non-stationary …

The resting activity of the brain can be described by so-called intrinsic connectivity networks
(ICNs), which consist of spatially and temporally distributed, but functionally connected …

Recent years have seen a rapid growth in computational methods for a better understanding
of functional connectivity brain networks constructed from neuroimaging data. Most of the …

The brain at rest consists of spatially and temporal distributed but functionally connected
regions that called intrinsic connectivity networks (ICNs). Resting state …