Hierarchical modularity in human brain functional networks

The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions

Effect of imperfect competition on infrastructure charges

The text explores the optimal infrastructure charges of an unbundled activity where the infrastructure manager sells the use of the infrastructure to operators providing services to a downstream market made up of atomistic customers. This situation has been widely analysed under the assumption that the upstream market is competitive, but more rarely in the case of imperfect competition. Typical examples are the railways activity in Europe and air transport. Various market structures are considered, illustrated by situations encountered in the transport field: a single mode operated by a single operator, two operators competing within the same mode, and two modes competing in a Bertrand way. In each case, situations are analysed using analytic formulae with a simplified demand function and a simplified cost function, and performing simulations with sensible parameter values drawn from current average situations. The main result is that the analysed imperfections make a dramatic departure from the conventional Marginal Cost pricing doctrine. Conclusions are drawn regarding infrastructure charging policy

Modular and Hierarchically Modular Organization of Brain Networks

Brain networks are increasingly understood as one of a large class of information processing systems that share important organizational principles in common, including the property of a modular community structure. A module is topologically defined as a subset of highly inter-connected nodes which are relatively sparsely connected to nodes in other modules. In brain networks, topological modules are often made up of anatomically neighboring and/or functionally related cortical regions, and inter-modular connections tend to be relatively long distance. Moreover, brain networks and many other complex systems demonstrate the property of hierarchical modularity, or modularity on several topological scales: within each module there will be a set of sub-modules, and within each sub-module a set of sub-sub-modules, etc. There are several general advantages to modular and hierarchically modular network organization, including greater robustness, adaptivity, and evolvability of network function. In this context, we review some of the mathematical concepts available for quantitative analysis of (hierarchical) modularity in brain networks and we summarize some of the recent work investigating modularity of structural and functional brain networks derived from analysis of human neuroimaging data

Age-related functional reorganization, structural changes, and preserved cognition.

Although healthy aging is associated with general cognitive decline, there is considerable variability in the extent to which cognitive functions decline or are preserved. Preserved cognitive function in the context of age-related neuroanatomical and functional changes, has been attributed to compensatory mechanisms. However, the existing sparse evidence is largely focused on functions associated with the frontal cortex, leaving open the question of how wider age-related brain changes relate to compensation. We evaluated relationships between age-related neural and functional changes in the context of preserved cognitive function by combining measures of structure, function, and cognitive performance during spoken language comprehension using a paradigm that does not involve an explicit task. We used a graph theoretical approach to derive cognitive activation-related functional magnetic resonance imaging networks. Correlating network properties with age, neuroanatomical variations, and behavioral data, we found that decreased gray matter integrity was associated with decreased connectivity within key language regions but increased overall functional connectivity. However, this network reorganization was less efficient, suggesting that engagement of a more distributed network in aging might be triggered by reduced connectivity within specialized networks

Magnetic dephasing in mesoscopic spin glasses

We have measured Universal Conductance Fluctuations in the metallic spin glass Ag:Mn as a function of temperature and magnetic field. From this measurement, we can access the phase coherence time of the electrons in the spin glass. We show that this phase coherence time increases with both the inverse of the temperature and the magnetic field. From this we deduce that decoherence mechanisms are still active even deep in the spin glass phase

Double-walled carbon nanotubes trigger IL-1β release in human monocytes through Nlrp3 inflammasome activation

Because of their outstanding physical properties, carbon nanotubes (CNTs) are promising new materials in the field of nanotechnology. It is therefore imperative to assess their adverse effects on human health. Monocytes/macrophages that recognize and eliminate the inert particles constitute the main target of CNTs. In this article, we report our finding that double-walled CNTs (DWCNTs) synergize with Tolllike receptor agonists to enhance IL-1β release in human monocytes. We show that DWCNTs–induced IL-1β secretion is exclusively linked to caspase-1 and to Nlrp3 inflammasome activation in human monocytes. We also establish that this activation requires DWCNTs phagocytosis and potassium efflux, but not reactive oxygen specied (ROS) generation. Moreover, inhibition of lysosomal acidification or cathepsin-B activation reduces DWCNT-induced IL-1β secretion, suggesting that Nlrp3 inflammasome activation occurs via lysosomal destabilization. Thus, DWCNTs present a health hazard due to their capacity to activate Nlrp3 inflammasome, recalling the inflammation caused by asbestos and hence demonstrating that they should be used with caution. From the Clinical Editor: This is a very important biosafety/toxicity study regarding double walled carbon nanotubes. The investigators demonstrate that such nanotubes do represent a health hazard due to their capacity to activate Nlrp3 inflammasome, resembling the inflammation caused by asbestos. While further study of this phenomenon is definitely needed, the above findings clearly suggest that special precautions need to be taken when applying these nanoparticles in human disease research

Topological surface states of strained Mercury-Telluride probed by ARPES

The topological surface states of strained HgTe have been measured using high-resolution ARPES measurements. The dispersion of surface states form a Dirac cone, which origin is close to the top of the \ghh band: the top half of the Dirac cone is inside the stress-gap while the bottom half lies within the heavy hole bands and keeps a linear dispersion all the way to the X-point. The circular dichroism of the photo-emitted electron intensity has also been measured for all the bands.Comment: with supplementary materia

Activity time series of old stars from late F to early K VI. Exoplanet mass characterisation and detectability in radial velocity

Stellar variability impacts radial velocities at various timescales and therefore the detectability of exoplanets and the mass determination based on this technique. It is necessary to implement systematic studies, to delineate the current limitations of RV techniques to detect Earth-like planets. This paper aims are to investigate whether the targeted 10% mass uncertainty from RV follow-up of transits detected by PLATO can be reached, and to analyse and quantify Earth-like planet detectability for various spectral types. We implemented blind tests based on a large data set of realistic synthetic time series reproducing different phenomena leading to stellar variability such as complex magnetic activity patterns as well as flows, covering F6-K4 stars and a wide range of activity levels. The 10% mass uncertainty for a 1 MEarth in the habitable zone of a G2 star cannot be reached, even with an improved version of a usual correction of stellar activity and even for long-duration (ten years) well-sampled observations. This level can be reached for masses above 3 MEarth or for K4 stars alone. We quantify the maximum dispersion of the RV residuals needed to reach this 10% level, assuming the correction method and models do not affect the planetary signal. Several other methods were tested and do not allow a significantly improvement of this limited performance. Similarly, such low-mass planets in the habitable zone cannot be detected with a similar correction: blind tests lead to very low detection rates for 1 MEarth and a very high level of false positives. Very significant and new improvements with respect to methods based on activity indicators to correct for stellar activity must be devised at all timescales to reach the objective of 10% uncertainty on the mass or to detect such planets in RV. Methods based on the correlation with activity indicators are unlikely to be sufficient.Comment: Paper accepted in Astronomy and Astrophysic