The integrate-and-fire neuron model describes the state of a neuron in terms of its
membrane potential, which is determined by the synaptic inputs and the injected current that …

Although MEG/EEG signals are highly variable, systematic changes in distinct frequency
bands are commonly encountered. These frequency-specific changes represent robust …

This study examines the ability of neurons to track temporally varying inputs, namely by
investigating how the instantaneous firing rate of a neuron is modulated by a noisy input with …

We use a neural mass model to address some important issues in characterising functional
integration among remote cortical areas using magnetoencephalography or …

The extreme complexity of the brain naturally requires mathematical modeling approaches
on a large variety of scales; the spectrum ranges from single neuron dynamics over the …

Cortical neurons in vivo undergo a continuous bombardment due to synaptic activity, which
acts as a major source of noise. Here, we investigate the effects of the noise filtering by …

The aim of this work was to investigate the mechanisms that shape evoked
electroencephalographic (EEG) and magneto-encephalographic (MEG) responses. We …

Recent work has examined the estimation of models of stimulus-driven neural activity in
which some linear filtering process is followed by a nonlinear, probabilistic spiking stage …

A dynamical equation is derived for the spike emission rate ν (t) of a homogeneous network
of integrate-and-fire (IF) neurons in a mean-field theoretical framework, where the activity of …

A coarse-grained representation of neuronal network dynamics is developed in terms of
kinetic equations, which are derived by a moment closure, directly from the original large …