Why are most empirical networks, with the prominent exception of social ones, generically
degree-degree anticorrelated? To answer this long-standing question, we define the …

The performance of attractor neural networks has been shown to depend crucially on the
heterogeneity of the underlying topology. We take this analysis a step further by examining …

Complex coherent dynamics is present in a wide variety of neural systems. A typical
example is the voltage transitions between up and down states observed in cortical areas in …

Trophic coherence, a measure of the extent to which the nodes of a directed network are
organised in levels, has recently been shown to be closely related to many structural and …

We here illustrate how a well-founded study of the brain may originate in assuming
analogies with phase-transition phenomena. Analyzing to what extent a weak signal …

It is now generally assumed that the heterogeneity of most networks in nature probably
arises via preferential attachment of some sort. However, the origin of various other …

Short-term memory in the brain cannot in general be explained the way long-term memory
can–as a gradual modification of synaptic weights–since it takes place too quickly. Theories …

Here we numerically study the emergence of stochastic resonance as a mild phenomenon
and how this transforms into an amazing enhancement of the signal-to-noise ratio at several …

We present an evolving network model in which the total numbers of nodes and edges are
conserved, but in which edges are continuously rewired according to nonlinear preferential …

Excitable systems are of great theoretical and practical interest in mathematics, physics,
chemistry, and biology. Here, we numerically study models of excitable media, namely …