This review reports on the research done during past years on violations of the fluctuation–
dissipation theorem (FDT) in glassy systems. It is focused on the existence of a quasi …

What happens in our brain when we make a decision? What triggers a neuron to send out a
signal? What is the neural code? This textbook for advanced undergraduate and beginning …

Graph theory is now becoming a standard tool in system-level neuroscience. However,
endowing observed brain anatomy and dynamics with a complex network structure does not …

Neurons in the brain communicate by short electrical pulses, the so-called action potentials
or spikes. How can we understand the process of spike generation? How can we …

A continuous-time dynamic model of a network of N nonlinear elements interacting via
random asymmetric couplings is studied. A self-consistent mean-field theory, exact in the …

In this work we study of the dynamics of large-size random neural networks. Different
methods have been developed to analyze their behavior, and most of them rely on heuristic …

We deal with the problem of bridging the gap between two scales in neuronal modeling. At
the first (microscopic) scale, neurons are considered individually and their behavior …

This article is part of the Physical Review Research collection titled Physics of
Neuroscience. Recurrent networks are widely used as models of biological neural circuits …

Kinetic traps are a notorious problem in equilibrium statistical mechanics, where
temperature quenches ultimately fail to bring the system to low energy configurations. Using …

A theoretical performance analysis of the graph neural network (GNN) is presented. For
classification tasks, the neural network approach has the advantage in terms of flexibility that …