It is a fundamental challenge to understand how the function of a network is related to its
structural organization. Adaptive dynamical networks represent a broad class of systems that …

A celebrated and controversial hypothesis suggests that some biological systems—parts,
aspects, or groups of them—may extract important functional benefits from operating at the …

Self-organized criticality (SOC) refers to the ability of complex systems to evolve toward a
second-order phase transition at which interactions between system components lead to …

The neural criticality hypothesis states that the brain may be poised in a critical state at a
boundary between different types of dynamics. Theoretical and experimental studies show …

Coupled biological and chemical systems, neural networks, social interacting species, the
Internet and the World Wide Web, are only a few examples of systems composed by a large …

Statistical physics has proven to be a fruitful framework to describe phenomena outside the
realm of traditional physics. Recent years have witnessed an attempt by physicists to study …

We review the recent rapid progress in the statistical physics of evolving networks. Interest
has focused mainly on the structural properties of complex networks in communications …

Depending on the connectivity, recurrent networks of simple computational units can show
very different types of dynamics, ranging from totally ordered to chaotic. We analyze how the …

Information diffusion in online social networks is affected by the underlying network
topology, but it also has the power to change it. Online users are constantly creating new …

Adaptive networks appear in many biological applications. They combine topological
evolution of the network with dynamics in the network nodes. Recently, the dynamics of …