Emergence of a small-world functional network in cultured neurons

The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

The world at one's fingertips: interactive interpretation of environmental data

This chapter introduces the latest practices and technologies in the interactive interpretation of environmental data. With environmental data becoming ever larger, more diverse and more complex, there is a need for a new generation of tools that provides new capabilities over and above those of the standard workhorses of science. These new tools aid the scientist in discovering interesting new features (and also problems) in large datasets by allowing the data to be explored interactively using simple, intuitive graphical tools. In this way, new discoveries are made that are commonly missed by automated batch data processing. This chapter discusses the characteristics of environmental science data, common current practice in data analysis and the supporting tools and infrastructure. New approaches are introduced and illustrated from the points of view of both the end user and the underlying technology. We conclude by speculating as to future developments in the field and what must be achieved to fulfil this vision.

Potential of legume-based grassland-livestock systems in Europe

European grassland-based livestock production systems are challenged to produce more milk and meat to meet increasing world demand and to achieve this by using fewer resources. Legumes offer great potential for coping with such requests. They have numerous features that can act together at different stages in the soil-plant-animal-atmosphere system and these are most effective in mixed swards with a legume abundance of 30-50%. The resulting benefits are a reduced dependency on fossil energy and industrial N fertilizer, lower quantities of harmful emissions to the environment (greenhouse gases and nitrate), lower production costs, higher productivity and increased protein self-sufficiency. Some legume species offer opportunities for improving animal health with less medication due to bioactive secondary metabolites. In addition, legumes may offer an option for adapting to higher atmospheric CO2 concentrations and to climate change. Legumes generate these benefits at the level of the managed land area unit and also at the level of the final product unit. However, legumes suffer from some limitations, and suggestions are made for future research in order to exploit more fully the opportunities that legumes can offer. In conclusion, the development of legume-based grassland-livestock systems undoubtedly constitutes one of the pillars for more sustainable and competitive ruminant production systems, and it can only be expected that legumes will become more important in the future.