The computational role of short-term plasticity and the balance of excitation and inhibition in neural microcircuits: experimental and theoretical analysis

The computations performed by the brain ultimately rely on the functional connectivity between neurons embedded in complex networks. It is well known that the neuronal connections, the synapses, are plastic, i.e. the contribution of each presynaptic neuron to the firing of a postsynaptic neuron can be independently adjusted. The modulation of effective synaptic strength can occur on time scales that range from tens or hundreds of milliseconds, to tens of minutes or hours, to days, and may involve pre- and/or post-synaptic modifications. The collection of these mechanisms is generally believed to underlie learning and memory and, hence, it is fundamental to understand their consequences in the behavior of neurons.(...)

Flippase (FLP) recombinase-mediated marker recycling in the dermatophyte Arthroderma vanbreuseghemii.

Biological processes can be elucidated by investigating complex networks of relevant factors and genes. However, this is not possible in species for which dominant selectable markers for genetic studies are unavailable. To overcome the limitation in selectable markers for the dermatophyte Arthroderma vanbreuseghemii (anamorph: Trichophyton mentagrophytes), we adapted the flippase (FLP) recombinase-recombination target (FRT) site-specific recombination system from the yeast Saccharomyces cerevisiae as a selectable marker recycling system for this fungus. Taking into account practical applicability, we designed FLP/FRT modules carrying two FRT sequences as well as the flp gene adapted to the pathogenic yeast Candida albicans (caflp) or a synthetic codon-optimized flp (avflp) gene with neomycin resistance (nptII) cassette for one-step marker excision. Both flp genes were under control of the Trichophyton rubrum copper-repressible promoter (PCTR4). Molecular analyses of resultant transformants showed that only the avflp-harbouring module was functional in A. vanbreuseghemii. Applying this system, we successfully produced the Ku80 recessive mutant strain devoid of any selectable markers. This strain was subsequently used as the recipient for sequential multiple disruptions of secreted metalloprotease (fungalysin) (MEP) or serine protease (SUB) genes, producing mutant strains with double MEP or triple SUB gene deletions. These results confirmed the feasibility of this system for broad-scale genetic manipulation of dermatophytes, advancing our understanding of functions and networks of individual genes in these fungi.

Differential regulation of RasGAPs in cancer

Ever since their discovery as cellular counterparts of viral oncogenes more than 25 years ago, much progress has been made in understanding the complex networks of signal transduction pathways activated by oncogenic Ras mutations in human cancers. The activity of Ras is regulated by nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs), and much emphasis has been put into the biochemical and structural analysis of the Ras/GAP complex. The mechanisms by which GAPs catalyze Ras-GTP hydrolysis have been clarified and revealed that oncogenic Ras mutations confer resistance to GAPs and remain constitutively active. However, it is yet unclear how cells coordinate the large and divergent GAP protein family to promote Ras inactivation and ensure a certain biological response. Different domain arrangements in GAPs to create differential protein-protein and protein-lipid interactions are probably key factors determining the inactivation of the 3 Ras isoforms H-, K-, and N-Ras and their effector pathways. In recent years, in vitro as well as cell- and animal-based studies examining GAP activity, localization, interaction partners, and expression profiles have provided further insights into Ras inactivation and revealed characteristics of several GAPs to exert specific and distinct functions. This review aims to summarize knowledge on the cell biology of RasGAP proteins that potentially contributes to differential regulation of spatiotemporal Ras signaling.

Optimal network topologies for local search with congestion

The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Impact of community structure on information transfer

The observation that real complex networks have internal structure has important implication for dynamic processes occurring on such topologies. Here we investigate the impact of community structure on a model of information transfer able to deal with both search and congestion simultaneously. We show that networks with fuzzy community structure are more efficient in terms of packet delivery than those with pronounced community structure. We also propose an alternative packet routing algorithm which takes advantage of the knowledge of communities to improve information transfer and show that in the context of the model an intermediate level of community structure is optimal. Finally, we show that in a hierarchical network setting, providing knowledge of communities at the level of highest modularity will improve network capacity by the largest amount.

Topology of the world trade web

Economy, and consequently trade, is a fundamental part of human social organization which, until now, has not been studied within the network modeling framework. Here we present the first, to the best of our knowledge, empirical characterization of the world trade web, that is, the network built upon the trade relationships between different countries in the world. This network displays the typical properties of complex networks, namely, scale-free degree distribution, the small-world property, a high clustering coefficient, and, in addition, degree-degree correlation between different vertices. All these properties make the world trade web a complex network, which is far from being well described through a classical random network description.

Arbuscular mycorrhizal fungi mediate below-ground plant-herbivore interactions: a phylogenetic study

Ecological interactions are complex networks, but have typically been studied in a pairwise fashion. Examining how third-party species can modify the outcome of pairwise interactions may allow us to better predict their outcomes in realistic systems. For instance, arbuscular mycorrhizal fungi (AMF) can affect plant interactions with other organisms, including below-ground herbivores, but the mechanisms underlying these effects remain unclear. Here, we use a comparative, phylogenetically controlled approach to test the relative importance of mycorrhizal colonization and plant chemical defences (cardenolides) in predicting plant survival and the abundance of a generalist below-ground herbivore across 14 species of milkweeds (Asclepias spp.). Plants were inoculated with a mixture of four generalist AMF species or left uninoculated. After 1month, larvae of Bradysia sp. (Diptera: Sciaridae), a generalist below-ground herbivore, colonized plant roots. We performed phylogenetically controlled analyses to assess the influence of AMF colonization and toxic cardenolides on plant growth, mortality and infestation by fungus gnats. Overall, plants inoculated with AMF exhibited greater survival than did uninoculated plants. Additionally, surviving inoculated plants had lower numbers of larvae in their roots and fewer non-AM fungi than surviving uninoculated plants. In phylogenetic controlled regressions, gnat density in roots was better predicted by the extent of root colonized by AMF than by root cardenolide concentration. Taken as a whole, AMF modify the effect of below-ground herbivores on plants in a species-specific manner, independent of changes in chemical defence. This study adds to the growing body of literature demonstrating that mycorrhizal fungi may improve plant fitness by conferring protection against antagonists, rather than growth benefits. In addition, we advocate using comparative analyses to disentangle the roles of shared history and ecology in shaping trait expression and to better predict the outcomes of complex multitrophic interactions.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

A high-resolution anatomical atlas of the transcriptome in the mouse embryo.

Ascertaining when and where genes are expressed is of crucial importance to understanding or predicting the physiological role of genes and proteins and how they interact to form the complex networks that underlie organ development and function. It is, therefore, crucial to determine on a genome-wide level, the spatio-temporal gene expression profiles at cellular resolution. This information is provided by colorimetric RNA in situ hybridization that can elucidate expression of genes in their native context and does so at cellular resolution. We generated what is to our knowledge the first genome-wide transcriptome atlas by RNA in situ hybridization of an entire mammalian organism, the developing mouse at embryonic day 14.5. This digital transcriptome atlas, the Eurexpress atlas (http://www.eurexpress.org), consists of a searchable database of annotated images that can be interactively viewed. We generated anatomy-based expression profiles for over 18,000 coding genes and over 400 microRNAs. We identified 1,002 tissue-specific genes that are a source of novel tissue-specific markers for 37 different anatomical structures. The quality and the resolution of the data revealed novel molecular domains for several developing structures, such as the telencephalon, a novel organization for the hypothalamus, and insight on the Wnt network involved in renal epithelial differentiation during kidney development. The digital transcriptome atlas is a powerful resource to determine co-expression of genes, to identify cell populations and lineages, and to identify functional associations between genes relevant to development and disease.

Modelització i simulació de processos dinàmics en xarxes complexes adaptatives

El 1736, Leonhard Euler va ser pioner en l'estudi de la teoria de grafs, i des de llavorsmúltiples autors com Kirchoff, Seymour, etc. continuaren amb l'estudi de la teoria i topologiade grafs. La teoria de xarxes, part de la teoria de grafs, també ha estat estudiada abastament.D'altra banda, la dinàmica de xarxes fou popularitzada per Dan Gillespie el 1977, en el qual proposà un algorisme que permet la simulació discreta i estocàstica d'un sistema de partícules, el qual és la base del treball ja que serveix per dur a terme les simulacions de processos sobre les xarxes complexes. El camp de l'anàlisi de la dinàmica de xarxes, de fet, és un campemergent en l'actualitat; comprèn tant l'anàlisi estadística com la utilització de simulacions persolucionar problemes de la mateixa dinàmica.Les xarxes complexes (xarxes de característiques complexes, sovint xarxes reals) també sónobjecte d'estudi de l'actualitat, sobretot a causa de l'aparició de les xarxes socials. S'han convertiten un paradigma per l'estudi de processos dinàmics en sistemes formats per molts componentsque interactuen entre si de manera molt homogèniaL'objectiu del treball és triple:1. Estudiar i entendre els conceptes bàsics i la topologia de les xarxes complexes, així comdiferents tipus de dinàmiques de processos sobre elles.2. Programar un simulador estocàstic en llenguatge C++ capaç de generar trajectòries mitjantçant l'algorisme de Gillespie tant pel model epidèmic com pel model de dinàmicad'enllaços amb reconnexió.3. Utilitzar el simulador tant per estudiar casos que ja han estat tractats en la literatura comcasos nous que no han estat tractats i que poden ser assimilables a xarxes reals com, perexemple, xarxes socials

Emergence of assortative mixing between clusters of cultured neurons

The analysis of the activity of neuronal cultures is considered to be a good proxy of the functional connectivity of in vivo neuronal tissues. Thus, the functional complex network inferred from activity patterns is a promising way to unravel the interplay between structure and functionality of neuronal systems. Here, we monitor the spontaneous self-sustained dynamics in neuronal cultures formed by interconnected aggregates of neurons (clusters). Dynamics is characterized by the fast activation of groups of clusters in sequences termed bursts. The analysis of the time delays between clusters' activations within the bursts allows the reconstruction of the directed functional connectivity of the network. We propose a method to statistically infer this connectivity and analyze the resulting properties of the associated complex networks. Surprisingly enough, in contrast to what has been reported for many biological networks, the clustered neuronal cultures present assortative mixing connectivity values, meaning that there is a preference for clusters to link to other clusters that share similar functional connectivity, as well as a rich-club core, which shapes a"connectivity backbone" in the network. These results point out that the grouping of neurons and the assortative connectivity between clusters are intrinsic survival mechanisms of the culture.

Critical elements underpinning the emergence of the medical game ecosystem: gamifying traumatic brain injury rehabilitation in Finland

The healthcare sector is currently in the verge of a reform and thus, the medical game research provide an interesting area of research. The aim of this study is to explore the critical elements underpinning the emergence of the medical game ecosystem with three sub-objectives: (1) to seek who are the key actors involved in the medical game ecosystem and identify their needs, (2) to scrutinise what types of resources are required in medical game development and what types of relationships are needed to secure those resources, and (3) to identify the existing institutions (‘the rules of the game’) affecting the emergence of the medical game ecosystem. The theoretical background consists of service ecosystems literature. The empirical study conducted is based on the semi-structured theme interviews of 25 experts in three relevant fields: games and technology, health and funding. The data was analysed through a theoretical framework that was designed based upon service ecosystems literature. The study proposes that the key actors are divided into five groups: medical game companies, customers, funders, regulatory parties and complementors. Their needs are linked to improving patient motivation and enhancing the healthcare processes resulting in lower costs. Several types of resources, especially skills and knowledge, are required to create a medical game. To gain access to those resources, medical game companies need to build complex networks of relationships. Proficiency in managing those value networks is crucial. In addition, the company should take into account the underlying institutions in the healthcare sector affecting the medical game ecosystem. Three crucial institutions were identified: validation, lack of innovation supporting structures in healthcare and the rising consumerisation. Based on the findings, medical games cannot be made in isolation. A developmental trajectory model of the emerging medical game ecosystem was created based on the empirical data. The relevancy of relationships and resources is dependent on the trajectory that the medical game company at that time resides. Furthermore, creating an official and documented database for clinically valdated medical games was proposed to establish the medical game market and ensure an adequate status for the effective medical games. Finally, ecosystems approach provides interesting future opportunities for research on medical game ecosystems.

Information management in aircraft maintenance

Well managed information promotes competitive advantage and economic value for the company. The challenge is to use information effectively in complex networks. Decision making in network is complicated due to many independent sources of information. The aim of the present study was to identify and map the internal information flows and used information resourced by functions and roles, to make proposals to the case organization to improve the information management and to improve the situational awareness and process flows. In the present study, an inductive approach was applied, with the aim to find out gaps and bottlenecks of information flow of an aircraft maintenance organization and its network. The empirical part was conducted with observing the processes and with questionnaires. Theoretical part of this study consists on reviewing relevant literature on maintenance management in aviation and information management in aviation. Together with empirical evidence and the literature used in the study the gaps were found and suggestions for improvements were done. The outcome of this study contributes the organization in its bigger goal to improve the productivity. The information management of the network is one actor in the field and will pave the way to smoother operation and situational awareness. The lack of rules and requirements for information management and spreading is a challenge in information management. The excessive data overburden may cause problem in the actors’ situation-awareness due to non-availability of the right information.

Critical elements underpinning the emergence of the medical game ecosystem:gamifying traumatic brain injury rehabilitation in Finland

The healthcare sector is currently in the verge of a reform and thus, the medical game research provide an interesting area of research. The aim of this study is to explore the critical elements underpinning the emergence of the medical game ecosystem with three sub-objectives: (1) to seek who are the key actors involved in the medical game ecosystem and identify their needs, (2) to scrutinise what types of resources are required in medical game development and what types of relationships are needed to secure those resources, and (3) to identify the existing institutions (‘the rules of the game’) affecting the emergence of the medical game ecosystem. The theoretical background consists of service ecosystems literature. The empirical study conducted is based on the semi-structured theme interviews of 25 experts in three relevant fields: games and technology, health and funding. The data was analysed through a theoretical framework that was designed based upon service ecosystems literature. The study proposes that the key actors are divided into five groups: medical game companies, customers, funders, regulatory parties and complementors. Their needs are linked to improving patient motivation and enhancing the healthcare processes resulting in lower costs. Several types of resources, especially skills and knowledge, are required to create a medical game. To gain access to those resources, medical game companies need to build complex networks of relationships. Proficiency in managing those value networks is crucial. In addition, the company should take into account the underlying institutions in the healthcare sector affecting the medical game ecosystem. Three crucial institutions were identified: validation, lack of innovation supporting structures in healthcare and the rising consumerisation. Based on the findings, medical games cannot be made in isolation. A developmental trajectory model of the emerging medical game ecosystem was created based on the empirical data. The relevancy of relationships and resources is dependent on the trajectory that the medical game company at that time resides. Furthermore, creating an official and documented database for clinically validated medical games was proposed to establish the medical game market and ensure an adequate status for the effective medical games. Finally, ecosystems approach provides interesting future opportunities for research on medical game ecosystems