Narrow Results

The dynamic profile of brain function has received much attention in recent years and is also a focus in the study of epilepsy. The present study aims to integrate the dynamics of temporal and spatial characteristics to provide comprehensive and novel understanding of epileptic dynamics. Resting state fMRI data were collected from eighty-three patients with idiopathic generalized epilepsy (IGE) and 87 healthy controls (HC). Specifically, we explored the temporal and spatial variation of functional connectivity density (tvFCD and svFCD) in the whole brain. Using a sliding-window approach, for a given region, the standard variation of the FCD series was calculated as the tvFCD and the variation of voxel-wise spatial distribution was calculated as the svFCD. We found primary, high-level, and sub-cortical networks demonstrated distinct tvFCD and svFCD patterns in HC. In general, the high-level networks showed the highest variation, the subcortical and primary networks showed moderate variation, and the limbic system showed the lowest variation. Relative to HC, the patients with IGE showed weaken temporal and enhanced spatial variation in the default mode network and weaken temporospatial variation in the subcortical network. Besides, enhanced temporospatial variation in sensorimotor and high-level networks was also observed in patients. The hyper-synchronization of specific brain networks was inferred to be associated with the phenomenon responsible for the intrinsic propensity of generation and propagation of epileptic activities. The disrupted dynamic characteristics of sensorimotor and high-level networks might potentially contribute to the driven motion and cognition phenotypes in patients. In all, presently provided evidence from the temporospatial variation of functional interaction shed light on the dynamics underlying neuropathological profiles of epilepsy.

In this paper, we introduce a technique to study the minimal wave speed in reaction-diffusion equations with temporal variability and apply it to two particular models for biological invasions. We use the exponential transform to avoid solving partial differential equations explicitly or finding inverse transforms. In a single reaction-diffusion equation with time-periodic coefficients, the minimal wave speed depends only on time-averages of each coefficient function. In a two-compartment system with mobile and stationary individuals, the invasion speed depends on the precise form of the coefficient functions and their temporal correlations; in some cases, a lower bound can be obtained. Our technique can be extended to more complex life histories of invading organisms.

Satellite remote sensing now allows for the collection of various physical and biological parameters at regional and global scales and at different temporal resolutions which are not accessible to other sampling methods. The first objective of the GlobCoast project (www.foresea.fr/globcoast/) is to assess and analyze the seasonal, inter-annual, and decadal evolution of the global coastal waters in terms of biogeochemical composition as revealed from satellite ocean colour observations. The present study focuses on the suspended particulate matter, SPM, over the global coastal ocean. A new global SPM algorithm, combined with a new atmospheric correction algorithm, have been developed, evaluated, and applied to the MERIS (2002-2012) archive. This unique data set, characterized by a great spatio-temporal coverage, thanks to the applied atmospheric correction algorithm, can then be used for many kind of research activities. Examples of global and regional patterns are then provided.