Metaplasticity and memory in multilevel recurrent feed-forward networks.

Network systems can exhibit memory effects in which the interactions between different pairs of nodes adapt in time, leading to the emergence of preferred connections, patterns, and subnetworks. To a first approximation, this memory can be modeled through a "plastic" Hebbian or homophily mechanism, in which edges get reinforced proportionally to the amount of information flowing through them. However, recent studies on glia-neuron networks have highlighted how memory can evolve due to more complex dynamics, including multilevel network structures and "metaplastic" effects that modulate reinforcement.

The folding space of protein2-microglobulin is modulated by a single disulfide bridge.

Protein beta-2-microglobulin (2m) is classically considered the causative agent of dialysis related amyloidosis, a conformational disorder that affects patients undergoing long-term hemodialysis. The wild type (WT) form, the Δ6 structural variant, and the D76N mutant have been extensively used as model systems of2m aggregation. In all of them, the native structure is stabilized by a disulfide bridge between the sulphur atoms of the cysteine residues 25 (at B strand) and 80 (at F strand), which has been considered fundamental in2m fibrillogenesis.

Large deviations of random walks on random graphs.

We study the rare fluctuations or large deviations of time-integrated functionals or observables of an unbiased random walk evolving on Erdös-Rényi random graphs, and construct a modified, biased random walk that explains how these fluctuations arise in the long-time limit. Two observables are considered: the sum of the degrees visited by the random walk and the sum of their logarithm, related to the trajectory entropy. The modified random walk is used for both quantities to explain how sudden changes in degree fluctuations, similar to dynamical phase transitions, are related to localization transitions.

Attractor nonequilibrium stationary states in perturbed long-range interacting systems.

Isolated long-range interacting particle systems appear generically to relax to nonequilibrium states ("quasistationary states" or QSSs) which are stationary in the thermodynamic limit. A fundamental open question concerns the "robustness" of these states when the system is not isolated. In this paper we explore, using both analytical and numerical approaches to a paradigmatic one-dimensional model, the effect of a simple class of perturbations.

Finite-N corrections to Vlasov dynamics and the range of pair interactions.

We explore the conditions on a pair interaction for the validity of the Vlasov equation to describe the dynamics of an interacting N-particle system in the large N limit. Using a coarse graining in phase space of the exact Klimontovich equation for the N-particle system, we evaluate, neglecting correlations of density fluctuations, the scalings with N of the terms describing the corrections to the Vlasov equation for the coarse-grained one-particle phase space density. Considering a generic interaction with radial pair force F(r), with F(r)∼1/r(γ) at large scales, and regulated to a bounded behavior below a "softening" scale ɛ, we find that there is an essential qualitative difference between the cases γd, i.

Scaling quasistationary states in long-range systems with dissipation.

Hamiltonian systems with long-range interactions give rise to long-lived out-of-equilibrium macroscopic states, so-called quasistationary states. We show here that, in a suitably generalized form, this result remains valid for many such systems in the presence of dissipation. Using an appropriate mean-field kinetic description, we show that models with dissipation due to a viscous damping or due to inelastic collisions admit "scaling quasistationary states," i.