Brain activity during sleep is characterized by circuit-specific oscillations, including slow
waves, spindles and theta waves, which are nested in thalamocortical or hippocampal …

The brain must dynamically integrate, coordinate, and respond to internal and external
stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI …

Sleep stage classification is essential for sleep assessment and disease diagnosis.
Although previous attempts to classify sleep stages have achieved high classification …

Measurement of correlations between brain regions (functional connectivity) using blood
oxygen level dependent (BOLD) fMRI has proven to be a powerful tool for studying the …

The brain regulates information flow by balancing the segregation and integration of
incoming stimuli to facilitate flexible cognition and behaviour. The topological features of …

The temporal evolution of functional connectivity (FC) within the confines of individual scans
is nowadays often explored with functional neuroimaging. This is particularly true for resting …

Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …

The mining of huge databases of resting-state brain activity recordings represents state of
the art in the assessment of endogenous neuronal activity—and may be a promising tool in …

Traditionally studies of brain function have focused on task-evoked responses. By their very
nature such experiments tacitly encourage a reflexive view of brain function. While such an …

Abstract Machine learning techniques are increasingly being used in making relevant
predictions and inferences on individual subjects neuroimaging scan data. Previous studies …