Temporal patterns recognized by a network of coordinated time delays and coincidence detectors

A computational model of a neuronal network is described which performs a fundamental task of general perception: recognition of temporal patterns in continuous and uncued neuronal spike trains. The presented network is able to recognize each pattern element (100 ms interval composed of sets of 10, 20, 30 and 40 ms interspike intervals combined in linear order) as it arrives. Its operation is based upon biologically plausible filtering mechanisms and population neurodynamics.     

Evolving patterns in a collaboration network of global R&D on monoclonal antibodies

We investigated the evolution process of collaborative inter-organizational network of the research and development (R&D) on monoclonal antibody (mAb) over the past 30 y. The annual detection of the collaboration network provides dynamics on network structures and relationship changes among different organizations. Our research showed continuous growth of the network's scale and complexity due to the constant entry of new organizations and the forging of new partnering relationships. The evolving topological features reveal a core-periphery structure that became clearer over time and an increasing heterogeneity within the collaborative mAb R&D network. As measured by the number of network participants, dedicated biotechnology firms (DBFs) were the dominant organization form in the field of mAb development, but their average centrality was reduced during the period of 2004–2009, when pharmaceutical companies took over the positions of DBFs. Along with the network evolution, 2 waves of substitution on the leading positions were driven by technological innovations and mergers and acquisitions (M&A). In addition, this study analyzed organizational-level behaviors to help understand the evolution of network structures over the field of mAb development across the different technologically innovative or economic contexts.     

ISBT 128: a global information standard

ISBT 128 is the global standard for the identification, labeling and information transfer of human blood, cell, tissue and organ products across international borders and disparate health care systems. The system has been designed and perfected over almost two decades to ensure accuracy, safety and efficiency for the benefit of donors, patients and health care workers worldwide. The use of the ISBT 128 standard has grown steadily since a blood bank in Estonia first implemented it in 1997. Today, more than 3,500 facility identifiers for the use of ISBT 128 have been assigned to organizations in 67 countries on six continents. The standard has been accepted by a variety of international standard setting organizations and government regulators. It is managed by ICCBBA, a not-for-profit organization based in the USA that is governed by an international volunteer board of directors. Members of the Board of Directors represent the fields of practice affected by the standard. Advisory groups comprising international experts guide the ongoing development of the ISBT 128 standard to ensure it continues to meet the needs of its users. While there is a cost associated with the implementation and use of the standard, the clear benefits in terms of improved patient safety and ability to meet regulatory traceability requirements justify the costs.     

Evidence for social role in a dolphin social network

Social animals have to take into consideration the behaviour of conspecifics when making decisions to go by their daily lives. These decisions affect their fitness and there is therefore an evolutionary pressure to try making the right choices. In many instances individuals will make their own choices and the behaviour of the group will be a democratic integration of everyone’s decision. However, in some instances it can be advantageous to follow the choice of a few individuals in the group if they have more information regarding the situation that has arisen. Here I provide early evidence that decisions about shifts in activity states in a population of bottlenose dolphin follow such a decision-making process. This unshared consensus is mediated by a non-vocal signal, which can be communicated globally within the dolphin school. These signals are emitted by individuals that tend to have more information about the behaviour of potential competitors because of their position in the social network. I hypothesise that this decision-making process emerged from the social structure of the population and the need to maintain mixed-sex schools.     

Temporal constraints of a gene regulatory network: Refining a qualitative simulation

The modelling of gene regulatory networks (GRNs) has classically been addressed through very different approaches. Among others, extensions of Thomas’s asynchronous Boolean approach have been proposed, to better fit the dynamics of biological systems: genes may reach different discrete expression levels, depending on the states of other genes, called the regulators: thus, activations and inhibitions are triggered conditionally on the proper expression levels of these regulators. In contrast, some fine-grained propositions have focused on the molecular level as modelling the evolution of biological compound concentrations through differential equation systems. Both approaches are limited. The first one leads to an oversimplification of the system, whereas the second is incapable to tackle large GRNs. In this context, hybrid paradigms, that mix discrete and continuous features underlying distinct biological properties, achieve significant advances for investigating biological properties. One of these hybrid formalisms proposes to focus, within a GRN abstraction, on the time delay to pass from a gene expression level to the next. Until now, no research work has been carried out, which attempts to benefit from the modelling of a GRN by differential equations, converting it into a multi-valued logical formalism of Thomas, with the aim of performing biological applications.     

Kin in space: social viscosity in a spatially and genetically substructured network

Population substructuring is a fundamental aspect of animal societies. A growing number of theoretical studies recognize that who-meets-whom is not random, but rather determined by spatial relationships or illustrated by social networks. Structural properties of large highly dynamic social systems are notoriously difficult to unravel. Network approaches provide powerful ways to analyse the intricate relationships between social behaviour, dispersal strategies and genetic structure. Applying network analytical tools to a colony of the highly gregarious Galápagos sea lion (Zalophus wollebaeki), we find several genetic clusters that correspond to spatially determined 'network communities'. Overall relatedness was low, and genetic structure in the network can be interpreted as an emergent property of philopatry and seems not to be primarily driven by targeted interactions among highly related individuals in family groups. Nevertheless, social relationships between directly adjacent individuals in the network were stronger among genetically more similar individuals. Taken together, these results suggest that even small differences in the degree of relatedness can influence behavioural decisions. This raises the fascinating prospect that kin selection may also apply to low levels of relatedness within densely packed animal groups where less obvious co-operative interactions such as increased tolerance and stress reduction are important.     

Temporal patterns of animal development

A summary of studies on temporal characteristics of animal development performed during last 30 years using dimensionless unit as a parameter of development duration is presented. This approach allowed to introduce time as a parameter in comparative embryological studies. Thus the time of development became a subject of the embryological studies. Perspectives for the future work are defined.     

Strength of social tie predicts cooperative investment in a human social network

Social networks--diagrams which reflect the social structure of animal groups--are increasingly viewed as useful tools in behavioural ecology and evolutionary biology. Network structure may be especially relevant to the study of cooperation, because the action of mechanisms which affect the cost:benefit ratio of cooperating (e.g. reciprocity, punishment, image scoring) is likely to be mediated by the relative position of actor and recipient in the network. Social proximity could thus affect cooperation in a similar manner to biological relatedness. To test this hypothesis, we recruited members of a real-world social group and used a questionnaire to reveal their network. Participants were asked to endure physical discomfort in order to earn money for themselves and other group members, allowing us to explore relationships between willingness to suffer a cost on another's behalf and the relative social position of donor and recipient. Cost endured was positively correlated with the strength of the social tie between donor and recipient. Further, donors suffered greater costs when a relationship was reciprocated. Interestingly, participants regularly suffered greater discomfort for very close peers than for themselves. Our results provide new insight into the effect of social structure on the direct benefits of cooperation.     

Exploring global distortions of biological macromolecules and assemblies from low-resolution structural information and elastic network theory

A theory of elastic normal modes is described for the exploration of global distortions of biological structures and their assemblies based upon low-resolution image data. Structural information at low resolution, e.g. from density maps measured by cryogenic electron microscopy (cryo-EM), is used to construct discrete multi-resolution models for the electron density using the techniques of vector quantization. The elastic normal modes computed based on these discretized low-resolution models are found to compare well with the normal modes obtained at atomic resolution. The quality of the normal modes describing global displacements of the molecular system is found to depend on the resolution of the synthetic EM data and the extent of reductionism in the discretized representation. However, models that reproduce the functional rearrangements of our test set of molecules are achieved for realistic values of experimental resolution. Thus large conformational changes as occur during the functioning of biological macromolecules and assemblies can be elucidated directly from low-resolution structural data through the application of elastic normal mode theory and vector quantization.     

Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis

Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT). As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR) to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate). Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree) increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity). We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications). We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement). The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities. The findings support investment in infrastructure-building and intersectoral mobilization in addressing disparities and highlight the benefits of using CBPR approaches for such work.     

Recognition of partly occluded patterns: a neural network model

 Human beings are often able to read a letter or word partly occluded by contaminating ink stains. However, if the stains are completely erased and the occluded areas of the letter are changed to white, we usually have difficulty in reading the letter. In this article I propose a hypothesis explaining why a pattern is easier to recognize when it is occluded by visible objects than by invisible opaque objects. A neural network model is constructed based on this hypothesis. The visual system extracts various visual features from the input pattern and then attempts to recognize it. If the occluding objects are not visible, the visual system will have difficulty in distinguishing which features are relevant to the original pattern and which are newly generated by the occlusion. If the occluding objects are visible, however, the visual system can easily discriminate between relevant and irrelevant features and recognize the occluded pattern correctly. The proposed model is an extended version of the neocognitron model. The activity of the feature-extracting cells whose receptive fields cover the occluding objects is suppressed in an early stage of the hierarchical network. Since the irrelevant features generated by the occlusion are thus eliminated, the model can recognize occluded patterns correctly, provided the occlusion is not so large as to prevent recognition even by human beings. Received: 21 February 2000 / Accepted in revised form: 11 September 2000     

CytoITMprobe: a network information flow plugin for Cytoscape

ABSTRACT: BACKGROUND: Cytoscape is a well-developed flexible platform for visualization, integration and analysis of network data. Apart from the sophisticated graph layout and visualization routines, it hosts numerous user-developed plugins that significantly extend its core functionality. Earlier, we developed a network information flow framework and implemented it as a web application, called ITM Probe. Given a context consisting of one or more user-selected nodes, ITM Probe retrieves other network nodes most related to that context. It requires neither user restriction to subnetwork of interest nor additional and possibly noisy information. However, plugins for Cytoscape with these features do not yet exist. To provide the Cytoscape users the possibility of integrating ITM Probe into their workflows, we developed CytoITMprobe, a new Cytoscape plugin. FINDINGS: CytoITMprobe maintains all the desirable features of ITM Probe and adds additional flexibility not achievable through its web service version. It provides access to ITM Probe either through a web server or locally. The input, consisting of a Cytoscape network, together with the desired origins and/or destinations of information and a dissipation coefficient, is specified through a query form. The results are shown as a subnetwork of significant nodes and several summary tables. Users can control the composition and appearance of the subnetwork and interchange their ITM Probe results with other software tools through tab-delimited files. CONCLUSIONS: The main strength of CytoITMprobe is its flexibility. It allows the user to specify as input any Cytoscape network, rather than being restricted to the pre-compiled protein-protein interaction networks available through the ITM Probe web service. Users may supply their own edge weights and directionalities. Consequently, as opposed to ITM Probe web service, CytoITMprobe can be applied to many other domains of network-based research beyond protein-networks. It also enables seamless integration of ITM Probe results with other Cytoscape plugins having complementary functionality for data analysis.     

Temporal patterns in a fish assemblage of a semiarid mangrove zone in Madagascar

Gillnet sampling was conducted for a year in a tropical mangrove creek (SW Madagascar), characterized by a limited freshwater influence, a high turbidity and a tidal range up to 3 m. Sixty species of juvenile fishes were caught, 44 species being of commercial interest. Catches were dominated by Gerreidae (27% of total abundance), Teraponidae (16%), Carangidae (13%) and Sparidae (12%). The temporary resident fishes in the mangrove zone represented 50% of the species and 97% of the total abundance, the other species being rare (less than five individuals). The species richness, abundance and biomass per netting were low in the middle of the cool season (July-August). Monthly changes in the fish assemblage were particularly complex, with three species groups displaying a clear seasonal pattern, some species succeeding one another in a rather unstructured way, and three species abundant throughout the year. There was no clear structuring effect of temperature, salinity and turbidity on the fish assemblage. However, tidal, lunar and diel effects on the composition of the fish assemblage were evident. The species overlap between the Sarodrano mangrove fauna and the adjacent coral reef fauna is particularly weak with six species in common and shows that the mangrove plays only a very limited nursery role for coral reef species.     

Noise induced complexity: patterns and collective phenomena in a small-world neuronal network

The effects of noise on patterns and collective phenomena are studied in a small-world neuronal network with the dynamics of each neuron being described by a two-dimensional Rulkov map neuron. It is shown that for intermediate noise levels, noise-induced ordered patterns emerge spatially, which supports the spatiotemporal coherence resonance. However, the inherent long range couplings of small-world networks can effectively disrupt the internal spatial scale of the media at small fraction of long-range couplings. The temporal order, characterized by the autocorrelation of a firing rate function, can be greatly enhanced by the introduction of small-world connectivity. There exists an optimal fraction of randomly rewired links, where the temporal order and synchronization can be optimized.