Physics is a field of science that has traditionally used the scientific method to answer
questions about why natural phenomena occur and to make testable models that explain the …

Low-dimensional neural mass models are often invoked to model the coarse-grained activity
of large populations of neurons and synapses and have been used to help understand the …

This is a book about 'Neurodynamics'. What we mean is that this is a book about how ideas
from dynamical systems theory have been developed and employed in recent years to give …

Networks of spiking neurons with adaption have been shown to be able to reproduce a wide
range of neural activities, including the emergent population bursting and spike synchrony …

We consider a ring network of theta neurons with non-local homogeneous coupling. We
analyse the corresponding continuum evolution equation, analytically describing all …

We consider a ring network of quadratic integrate-and-fire neurons with nonlocal synaptic
and gap junction coupling. The corresponding neural field model supports solutions such as …

We derive the Kuramoto model (KM) corresponding to a population of weakly coupled,
nearly identical quadratic integrate-and-fire (QIF) neurons with both electrical and chemical …

Rhythmic activities that alternate between coherent and incoherent phases are ubiquitous in
chemical, ecological, climate, or neural systems. Despite their importance, general …

Pulse-coupled spiking neural networks are a powerful tool to gain mechanistic insights into
how neurons self-organize to produce coherent collective behavior. These networks use …

Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal
populations. A common framework for NMMs assumes heuristically that the output firing rate …