Unconditioned responses and functional fear networks in human classical conditioning.

Human imaging studies examining fear conditioning have mainly focused on the neural responses to conditioned cues. In contrast, the neural basis of the unconditioned response and the mechanisms by which fear modulates inter-regional functional coupling have received limited attention. We examined the neural responses to an unconditioned stimulus using a partial-reinforcement fear conditioning paradigm and functional MRI. The analysis focused on: (1) the effects of an unconditioned stimulus (an electric shock) that was either expected and actually delivered, or expected but not delivered, and (2) on how related brain activity changed across conditioning trials, and (3) how shock expectation influenced inter-regional coupling within the fear network. We found that: (1) the delivery of the shock engaged the red nucleus, amygdale, dorsal striatum, insula, somatosensory and cingulate cortices, (2) when the shock was expected but not delivered, only the red nucleus, the anterior insular and dorsal anterior cingulate cortices showed activity increases that were sustained across trials, and (3) psycho-physiological interaction analysis demonstrated that fear led to increased red nucleus coupling to insula but decreased hippocampus coupling to the red nucleus, thalamus and cerebellum. The hippocampus and the anterior insula may serve as hubs facilitating the switch between engagement of a defensive immediate fear network and a resting network.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Dynamic simulation of regulatory networks using SQUAD.

BACKGROUND: The ambition of most molecular biologists is the understanding of the intricate network of molecular interactions that control biological systems. As scientists uncover the components and the connectivity of these networks, it becomes possible to study their dynamical behavior as a whole and discover what is the specific role of each of their components. Since the behavior of a network is by no means intuitive, it becomes necessary to use computational models to understand its behavior and to be able to make predictions about it. Unfortunately, most current computational models describe small networks due to the scarcity of kinetic data available. To overcome this problem, we previously published a methodology to convert a signaling network into a dynamical system, even in the total absence of kinetic information. In this paper we present a software implementation of such methodology. RESULTS: We developed SQUAD, a software for the dynamic simulation of signaling networks using the standardized qualitative dynamical systems approach. SQUAD converts the network into a discrete dynamical system, and it uses a binary decision diagram algorithm to identify all the steady states of the system. Then, the software creates a continuous dynamical system and localizes its steady states which are located near the steady states of the discrete system. The software permits to make simulations on the continuous system, allowing for the modification of several parameters. Importantly, SQUAD includes a framework for perturbing networks in a manner similar to what is performed in experimental laboratory protocols, for example by activating receptors or knocking out molecular components. Using this software we have been able to successfully reproduce the behavior of the regulatory network implicated in T-helper cell differentiation. CONCLUSION: The simulation of regulatory networks aims at predicting the behavior of a whole system when subject to stimuli, such as drugs, or determine the role of specific components within the network. The predictions can then be used to interpret and/or drive laboratory experiments. SQUAD provides a user-friendly graphical interface, accessible to both computational and experimental biologists for the fast qualitative simulation of large regulatory networks for which kinetic data is not necessarily available.

Le code-switching comme ressource stratégique pour la gestion de l'interaction multilingue : coordination et leadership dans un groupe de travail

In this article, we analyze a multilingual interaction in a students' working group and hypothesize a correlation between management of languages in interaction and leadership. We consider Codeswitching as one of the most relevant observables in multilingual interaction and attempt to analyze how it is used by speakers. After a brief presentation of three theoretical and analytical conceptions of Code-switching in interaction (Auer, Mondada & Myers Scotton), we define Code-switching as an interactional, strategical, multilingual resource exploited by speakers to achieve various interactional and non interactional goals. We then show in two CA-like analysis how multilingual strategical resources occur in the interactional practices of the analyzed working group, and how they are exploited by speakers in order to organize interaction, work, tasks, and to construct one's leadership. We also consider the metadiscourses of the students about their own practices and multilingualism in general, in order to confront them to their actual multilingual practices. We draw the hypothesis that discrepancies observed between metadiscourses and practices can be explained through the development of (meta)discourses showing a unilingual conception in describing multilingual practices.

TNFα in synaptic function: switching gears.

Pathological brain states are known to induce massive production of proinflammatory cytokines, including tumor necrosis factor alpha (TNFα). At much lower levels, these cytokines are also present in the healthy brain, where it is increasingly being recognized that they exert regulatory influences. Recent studies suggest that TNFα plays important roles in controlling synaptic transmission and plasticity. Here, we discuss the evidence in support of synaptic regulation by TNFα and the underlying cellular mechanisms, including control of AMPA receptor trafficking and glutamate release from astrocytes. These findings suggest that increases in TNFα levels (caused by nervous system infection, injury, or disease) transform the physiological actions of the cytokine into deleterious ones. This functional switch may contribute to cognitive alterations in several brain pathologies.

The policy-making structure of European regulatory networks and the domestic adoption of standards

European regulatory networks (ERNs) constitute the main governance instrument for the informal co-ordination of public regulation at the European Union (EU) level. They are in charge of co-ordinating national regulators and ensuring the implementation of harmonized regulatory policies across the EU, while also offering sector-specific expertise to the Commission. To this aim, ERNs develop 'best practices' and benchmarking procedures in the form of standards, norms and guidelines to be adopted in member states. In this paper, we focus on the Committee of European Securities Regulators and examine the consequences of the policy-making structure of ERNs on the domestic adoption of standards. We find that the regulators of countries with larger financial industries tend to occupy more central positions in the network, especially among newer member states. In turn, network centrality is associated with a more prompt domestic adoption of standards.

MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks.

SUMMARY: MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the website's functionality. Availability and implementation: MetaNetX.org is available at http://metanetx.org. CONTACT: help@metanetx.org.

Patterns of recovery following focal hemispheric lesions : relationship between lasting deficit and damage to specialized networks

Rapport de synthèse : Objectif : Les déficits cognitifs présents dans la phase aiguë d'une lésion hémisphérique focale ont tendance à être de nature plus importante et plus générale que les déficits résiduels qui persistent dans la phase chronique de récupération. Nous avons investigué, dans le cadre de ce travail, les modèles de récupération auditive et la relation qui se dessine entre les déficits et les dommages relatifs à des réseaux spécifiques, pris comme modèle cognitif des fonctions auditives. De nombreuses études humaines dans les domaines de la neuropsychologie, de la psychophysique ainsi que des études d'activation suggèrent que les processus de reconnaissance et de localisation sonores sont effectués par l'intermédiaire de réseaux distincts tant sur le plan anatomique que fonctionnel : il s'agit des zones de traitement du «What» et du «Where », qui sont toutes deux présentes dans les deux hémisphères. Des études ont démontré que des lésions hémisphériques focales gauches ou droites, centrées sur ces réseaux, sont associées dans la phase chronique de récupération à des déficits correspondant en ce qui concerne la reconnaissance et/ou la localisation sonore. Méthode : Dans le cadre de ce travail, nous avons analysé les résultats concernant les performances auditives chez 24 patients ayant subi des lésions hémisphériques focales avec déficits secondaires dans des tâches de reconnaissance, de localisation et/ou de perception du mouvement sonore lors d'un premier testing effectué en phase aiguë (9 patients), en phase subaiguë (6 patients) ou en phase chronique précoce (9 patients). La totalité de ces patients ont bénéficié d'un second testing en phase chronique. Les observations effectuées ont servi à l'élaboration de patterns de récupération auditive. Résultats : Tous les 24 patients avaient initialement un déficit dans le domaine de la localisation et/ou de la perception du mouvement sonore. Dans la phase aiguë, ce déficit survenait sans atteinte spécifique du réseau «Where » chez presque la moitié des patients ; en revanche, cette situation n'était jamais observée chez les patients testés en phase chronique précoce. Une absence de récupération avait tendance à être associée à un dommage spécifique au réseau concerné ainsi qu'à la persistance d'un déficit au-delà de la phase aiguë. Les déficits résiduels n'étaient par ailleurs pas strictement en lien avec la taille lésionnelle ou l'étendue de l'atteinte du réseau spécifique. Conclusion : Nos résultats suggèrent que des mécanismes distincts sous-tendent la récupération et la plasticité à différentes périodes temporelles post-lésionnelles.

Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data

The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.