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

Degree of intervality of food webs: From body-size data to models

In food webs, the degree of intervality of consumers' diets is an indicator of the number of dimensions that are necessary to determine the niche of a species. Previous studies modeling food-web structure have shown that real networks are compatible with a high degree of diet contiguity. However, current models are also compatible with the opposite, namely that species' diets have relatively low contiguity. This is particularly true when one takes species' body size as a proxy for niche value, in which case the indeterminacy of diet contiguities provided by current models can be large. We propose a model that enables us to narrow down the range of possible values of diet contiguity. According to this model, we find that diet contiguity not only can be high, but must be high when species are ranked in ascending order of body size.This work was supported by a James S. Mc Donnell Foundation Research Award (R.G.), European Union Grant PIRG-GA-2010-277166 (R.G.), Spanish Ministerio de Ciencia e Innovación (MICINN) Grants FIS2009-13370-C02-01 A.A.), FIS2010-18639 (R.G.), PRODIEVO, and FIS2011-27569 (J.A.C.), Comunidad de Madrid Grant MODELICO-CM (J.A.C.) and by Generalitat de Catalunya 2009-SGR-838 (A.A.).Publicad

Optimal information transmission in organizations: Search and congestion

We propose a stylized model of a problem-solving organization whose internal communication structure is given by a fixed network. Problems arrive randomly anywhere in this network and must find their way to their respective “specialized solvers” by relying on local information alone. The organization handles multiple problems simultaneously. For this reason, the process may be subject to congestion. We provide a characterization of the threshold of collapse of the network and of the stock of foating problems (or average delay) that prevails below that threshold. We build upon this characterization to address a design problem: the determination of what kind of network architecture optimizes performance for any given problem arrival rate. We conclude that, for low arrival rates, the optimal network is very polarized (i.e. star-like or “centralized”), whereas it is largely homogenous (or “decentralized”) for high arrival rates. We also show that, if an auxiliary assumption holds, the transition between these two opposite structures is sharp and they are the only ones to ever qualify as optimal.Networks, information transmission, search, organization design

Optimal Information Transmission in Organizations: Search and Congestion

We propose a stylized model of a problem-solving organization whose internal communication structure is given by a fixed network. Problems arrive randomly anywhere in this network and must find their way to their respective “specialized solvers” by relying on local information alone. The organization handles multiple problems simultaneously. For this reason, the process may be subject to congestion. We provide a characterization of the threshold of collapse of the network and of the stock of floating problems (or average delay) that prevails below that threshold. We build upon this characterization to address a design problem: the determination of what kind of network architecture optimizes performance for any given problem arrival rate. We conclude that, for low arrival rates, the optimal network is very polarized (i.e. star-like or “centralized”), whereas it is largely homogenous (or “decentralized”) for high arrival rates. We also show that, if an auxiliary assumption holds, the transition between these two opposite structures is sharp and they are the only ones to ever qualify as optimal. Keywords: Networks, information transmission, search, organization design.Networks, Information transmission, Search, Organization design

Synchronization invariance under network structural transformations

Synchronization processes are ubiquitous despite the many connectivity patterns that complex systems can show. Usually, the emergence of synchrony is a macroscopic observable; however, the microscopic details of the system, as, e.g., the underlying network of interactions, is many times partially or totally unknown. We already know that different interaction structures can give rise to a common functionality, understood as a common macroscopic observable. Building upon this fact, here we propose network transformations that keep the collective behavior of a large system of Kuramoto oscillators invariant. We derive a method based on information theory principles, that allows us to adjust the weights of the structural interactions to map random homogeneous in-degree networks into random heterogeneous networks and vice versa, keeping synchronization values invariant. The results of the proposed transformations reveal an interesting principle; heterogeneous networks can be mapped to homogeneous ones with local information, but the reverse process needs to exploit higher-order information. The formalism provides analytical insight to tackle real complex scenarios when dealing with uncertainty in the measurements of the underlying connectivity structure

Xarxes completes: de la cèl·lula al Facebook

Les unitats que formen els sistemes complexos interaccionen entre elles en xarxes que no són ni perfectament regulars ni perfectament aleatòries. L'estructura d'aquestes xarxes determina el comportament dels processos dinàmics que hi tenen lloc i, alhora, és un refl ex de l'evolució i les funcions del sistema. Des d'aquesta doble perspec�� va, l'estudi de les xarxes complexes és important. En aquest ar�� cle discu�� m el resultats clàssics de la teoria de xarxes i algunes de les línies de recerca actualment més ac�� ves

Xarxes completes: de la cèl·lula al Facebook

Les unitats que formen els sistemes complexos interaccionen entre elles en xarxes que no són ni perfectament regulars ni perfectament aleatòries. L'estructura d'aquestes xarxes determina el comportament dels processos dinàmics que hi tenen lloc i, alhora, és un refl ex de l'evolució i les funcions del sistema. Des d'aquesta doble perspec�� va, l'estudi de les xarxes complexes és important. En aquest ar�� cle discu�� m el resultats clàssics de la teoria de xarxes i algunes de les línies de recerca actualment més ac�� ves

Functional strengthening through synaptic scaling upon connectivity disruption in neuronal cultures

An elusive phenomenon in network neuroscience is the extent of neuronal activity remodeling upon damage. Here, we investigate the action of gradual synaptic blockade on the effective connectivity in cortical networks in vitro. We use two neuronal cultures configurations one formed by about 130 neuronal aggregates and another one formed by about 600 individual neurons and monitor their spontaneous activity upon progressive weakening of excitatory connectivity. We report that the effective connectivity in all cultures exhibits a first phase of transient strengthening followed by a second phase of steady deterioration. We quantify these phases by measuring GEFF, the global efficiency in processing network information. We term hyperefficiency the sudden strengthening of GEFF upon network deterioration, which increases by 20-50% depending on culture type. Relying on numerical simulations we reveal the role of synaptic scaling, an activity-dependent mechanism for synaptic plasticity, in counteracting the perturbative action, neatly reproducing the observed hyperefficiency. Our results demonstrate the importance of synaptic scaling as resilience mechanism

Trade synchronization in the World Trade Web

In March 2008, the bankruptcy of Lehman Brothers marked for many the beginning of the global crisis. In an increasingly globalized world, the financial crisis spread relentlessly. Recent theories of financial fragility link globalization with economic cycles, i.e. when local crises coincide with bad credit regulation and failures in international monetary arrangements. The globalization process in recent years has been accelerated due to to the increase of international trade. Here we analyze how economic cycles can spread worldwide over the global trade network (WTW). We use the WTW network structure to simulate a network of Integrate-and-Fire oscillators for two different years, 1980 and 2000. The results reinforce the idea that globalization accelerates the global synchronization process