Introduction : Neuroimaging studies have shown that in adults, the motor learning induced alterations of the functional connectivity assessed during Resting State Networks (RSN) is age-dependent (Mary et al., 2017). Motor learning relies on the build-up of new sensori-motor representations, which has been studied using the bar-man task in adults (Barlaam, Vaugoyeau, Fortin, Assaiante, & Schmitz, 2016; Paulignan, Dufossé, Hugon, & Massion, 1989) and in children (Schmitz et al, 2002).. The aim of this study was to investigate the modulations of functional connectivity after a motor learn

Biological systems tend to display complex behaviour with a power-law (1/f - like) distribution. In the brain, this translates into neural activity that exhibits scale-free, temporal or spatial, properties (He, 2014). Scaleinvariance has been observed across different neuroimaging modalities and conditions (Linkenkaer-Hansen, 2001; He, 2014; Ciuciu et al. 2012). Beyond previously used features, recent electrophysiology studies have shown the presence of long-range temporal correlations (LRTCs) in the amplitude dynamics of alpha and beta oscillations (Nikulin et al. 2012).

The highly conserved zinc finger CCCTC-binding factor (CTCF) regulates genomic imprinting and gene expression by acting as a transcriptional activator or repressor of promoters and insulator of enhancers. The multiple functions of CTCF are accomplished by co-association with other protein partners and are dependent on genomic context and tissue specificity. Despite the critical role of CTCF in the organization of genome structure, to date, only a subset of CTCF interaction partners have been identified.

Network flows and specifically water flow in open canals can be modeled by systems of balance laws defined on graphs. The shallow water or Saint-Venant system of balance laws is one of the most used model and present two phases: fluvial or sub-critical and torrential or super-critical. Phase transitions may occur within the same canal but transitions related to networks are less investigated. In this paper we provide a complete characterization of possible phase transitions for a case study of a simple scenario with two canals and one junction.

A special feature of Rayleigh-Taylor systems with chemical reactions is the competition between turbulent mixing and the "burning processes", which leads to a highly non-trivial dynamics. We studied the problem performing high resolution numerical simulations of a 2d system, using a thermal lattice Boltzmann (LB) model.

We propose numerical simulations of viscoelastic fluids based on a hybrid algorithm combining Lattice-Boltzmann models (LBM) and Finite Differences (FD) schemes, the former used to model the macroscopic hydrodynamic equations, and the latter used to model the polymer dynamics. The kinetics of the polymers is introduced using constitutive equations for viscoelastic fluids with finitely extensible non-linear elastic dumbbells with Peterlin's closure (FENE-P).

In this paper we present an implementation for the QPACE supercomputer of a Lattice Boltzmann model of a fluid-dynamics flow in 2 dimensions. QPACE is a massively parallel application-driven system powered by the Cell processor. We review the structure of the model, describe in details its implementation on QPACE and finally present performance data and preliminary physics results. (C) 2010 Published by Elsevier Ltd.