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).

Background. With the exponential increase in data dimension and methodological complexities, brain networks analysis with MEG and EEG has become an increasingly challenging and time-consuming endeavor. To date, performing all the data processing steps that are required for a complete MEG/EEG analysis pipeline often require the use of a multitude of software packages and in-house or custom tools (e.g. MRI segmentation, pre-processing, source reconstruction, graph theoretical analysis, statistics).

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.