Functional ultrasound (fUS) imaging is a novel brain modality that relies on the high-sensitivity measure of cerebral blood volume achieved by ultrafast doppler angiography. As perfusion strongly linked to local neuronal activity, this technique allows whole-brain 3D mapping task-induced regional activation as well resting-state functional connectivity, non-invasively, with unmatched spatio-tem...

Quantifying hydrologic and ecological connectivity has contributed to understanding transport and dispersal processes and assessing ecosystem degradation or restoration potential. However, there has been little synthesis across disciplines. The growing field of ecohydrology and recent recognition that loss of hydrologic connectivity is leading to a global decline in biodiversity underscore the ...

BACKGROUND To reduce head movement during resting state functional magnetic resonance imaging, post-coma patients with disorders of consciousness (DOC) are frequently sedated with propofol. However, little is known about the effects of this sedation on the brain connectivity patterns in the damaged brain essential for differential diagnosis. In this study, we aimed to assess these effects. ME...

The application of Graph Theory to the brain connectivity patterns obtained from the analysis of neuroelectrical signals has provided an important step to the interpretation and statistical analysis of such functional networks. The properties of a network are derived from the adjacency matrix describing a connectivity pattern obtained by one of the available functional connectivity methods. How...

Characterisation of fractured rocks and evaluation of fracture connectivity are essential for the study of subsurface flow and transport in fractured rock aquifers. In this study, we use a new method to present fracture networks and analyse the connectivity of the fractures, based on the technique of randomly-generated realisations. The application of the method aims to provide more detailed in...

When we perform a cognitive task, multiple brain regions are engaged. Understanding how these regions interact is a fundamental step to uncover the neural bases of behavior. Most research on the interactions between brain regions has focused on the univariate responses in the regions. However, fine grained patterns of response encode important information, as shown by multivariate pattern analy...

Recent studies show that anatomical and functional brain networks exhibit similar small-world properties. However, the networks that are compared often differ in what the nodes represent (e.g. sensors or brain areas), what kind of connectivity is measured, and what temporal and spatial scales are probed. Here, I review studies of large-scale connectivity and recent results from a variety of rea...

Large datasets with interactions between objects are common to numerous scientific fields (i.e. social science, internet, biology. . . ). The interactions naturally define a graph and a common way to explore or summarize such dataset is graph clustering. Most techniques for clustering graph vertices just use the topology of connections ignoring informations in the vertices features. In this pap...

The random walk process underlies the description of a large number of real-world phenomena. Here we provide the study of random walk processes in time-varying networks in the regime of time-scale mixing, i.e., when the network connectivity pattern and the random walk process dynamics are unfolding on the same time scale. We consider a model for time-varying networks created from the activity p...

Sleep is necessary for the optimal consolidation of newly acquired procedural memories. However, the mechanisms by which motor memory traces develop during sleep remain controversial in humans, as this process has been mainly investigated indirectly by comparing pre- and post-sleep conditions. Here, we used functional magnetic resonance imaging and electroencephalography during sleep following ...