Social network architecture and the maintenance of deleterious cultural traits.

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Planning under partial observability by classical replanning: theory and experiments

Planning with partial observability can be formulated as a non-deterministic search problem in belief space. The problem is harder than classical planning as keeping track of beliefs is harder than keeping track of states, and searching for action policies is harder than searching for action sequences. In this work, we develop a framework for partial observability that avoids these limitations and leads to a planner that scales up to larger problems. For this, the class of problems is restricted to those in which 1) the non-unary clauses representing the uncertainty about the initial situation are nvariant, and 2) variables that are hidden in the initial situation do not appear in the body of conditional effects, which are all assumed to be deterministic. We show that such problems can be translated in linear time into equivalent fully observable non-deterministic planning problems, and that an slight extension of this translation renders the problem solvable by means of classical planners. The whole approach is sound and complete provided that in addition, the state-space is connected. Experiments are also reported.

Network characteristics of film tourism websites in Catalonia: an application of network analysis in tourism

This master thesis presents a research on the analysis of film tourism stakeholders in Catalonia applying the network analysis approach. The research aims to provide an analysis of the relations between local tourism stakeholders with local film offices through their websites. Therefore, the development of the present work involved the review of literature on the themes of film tourism and network analysis. Then the main stakeholders of film and tourism of Catalonia were identified and their websites analyzed. The measures indicators for network analysis such as centrality, closeness and betweenness degree have been applied on the analysis of the websites to determine the extent of the relations of film and tourism stakeholders in Catalonia. Results and conclusions are presented on the referred sections

The homeostatic psyche: Freudian theory and somatic markers.

After years of reciprocal lack of interest, if not opposition, neuroscience and psychoanalysis are poised for a renewed dialogue. This article discusses some aspects of the Freudian metapsychology and its link with specific biological mechanisms. It highlights in particular how the physiological concept of homeostasis resonates with certain fundamental concepts of psychoanalysis. Similarly, the authors underline how the Freud and Damasio theories of brain functioning display remarkable complementarities, especially through their common reference to Meynert and James. Furthermore, the Freudian theory of drives is discussed in the light of current neurobiological evidences of neural plasticity and trace formation and of their relationships with the processes of homeostasis. The ensuing dynamics between traces and homeostasis opens novel avenues to consider inner life in reference to the establishment of fantasies unique to each subject. The lack of determinism, within a context of determinism, implied by plasticity and reconsolidation participates in the emergence of singularity, the creation of uniqueness and the unpredictable future of the subject. There is a gap in determinism inherent to biology itself. Uniqueness and discontinuity: this should today be the focus of the questions raised in neuroscience. Neuroscience needs to establish the new bases of a "discontinuous" biology. Psychoanalysis can offer to neuroscience the possibility to think of discontinuity. Neuroscience and psychoanalysis meet thus in an unexpected way with regard to discontinuity and this is a new point of convergence between them.

Multidelayed random walks: Theory and application to the neolithic transition in Europe

We present a model in which particles (or individuals of a biological population) disperse with a rest time between consecutive motions (or migrations) which may take several possible values from a discrete set. Particles (or individuals) may also react (or reproduce). We derive a new equation for the effective rest time T˜ of the random walk. Application to the neolithic transition in Europe makes it possible to derive more realistic theoretical values for its wavefront speed than those following from the single-delayed framework presented previously [J. Fort and V. Méndez, Phys. Rev. Lett. 82, 867 (1999)]. The new results are consistent with the archaeological observations of this important historical process

Network governance and the domestic adoption of soft rules

European regulatory networks (ERNs) are in charge of producing and disseminating non-bindings standards, guidelines and recommendations in a number of important domains, such as banking and finance, electricity and gas, telecommunications, and competition regulation. The goal of these soft rules is to promote 'best practices', achieve co-ordination among regulatory authorities and ensure the consistent application of harmonized pro-competition rules across Europe. This contribution examines the domestic adoption of the soft rules developed within the four main ERNs. Different factors are expected to influence the process of domestic adoption: the resources of regulators; the existence of a review panel; and the interdependence of the issues at stake. The empirical analysis supports hypotheses about the relevance of network-level factors: monitoring and public reporting procedures increase the final level of adoption, while soft rules concerning highly interdependent policy areas are adopted earlier.

Analyzing dynamic intellectual capital: System-based theory and application

This research report presents an application of systems theory to evaluating intellectual capital (IC) as organization's ability for self-renewal. As renewal ability is a dynamic capability of an organization as a whole, rather than a static asset or an atomistic competence of separate individuals within the organization, it needs to be understood systemically. Consequently, renewal ability has to be measured with systemic methods that are based on a thorough conceptual analysis of systemic characteristics of organizations. The aim of this report is to demonstrate the theory and analysis methodology for grasping companies' systemic efficiency and renewal ability. The volume is divided into three parts. The first deals with the theory of organizations as self-renewing systems. In the second part, the principles of quantitative analysis of organizations are laid down. Finally, the detailed mathematics of the renewal indices are presented. We also assert that the indices produced by the analysis are an effective tool for the management and valuation of knowledge-intensive companies.