Highlights•Metastable activity is increasingly being observed in many cortical areas and in a
variety of tasks.•Metastable activity is correlated with sensory and cognitive processes and …

An essential step toward understanding neural circuits is linking their structure and their
dynamics. In general, this relationship can be almost arbitrarily complex. Recent theoretical …

Neural population equations such as neural mass or field models are widely used to study
brain activity on a large scale. However, the relation of these models to the properties of …

Autonomous, randomly coupled, neural networks display a transition to chaos at a critical
coupling strength. Here, we investigate the effect of a time-varying input on the onset of …

Recurrent networks of non-linear units display a variety of dynamical regimes depending on
the structure of their synaptic connectivity. A particularly remarkable phenomenon is the …

Rate chaos is a collective state of a neural network characterized by slow irregular
fluctuations of firing rates of individual neurons. We study a sparsely connected network of …

Explaining the mechanisms of dynamic memory, that allows for a temporary storage of
information at the timescale of seconds despite the neuronal firing at the millisecond scale …

While most models of randomly connected neural networks assume single-neuron models
with simple dynamics, neurons in the brain exhibit complex intrinsic dynamics over multiple …

Complexity and limited knowledge render it impractical to write down the equations
describing a cellular system completely. Cellular biophysics uses hypotheses-based …

The generation of neural action potentials (spikes) is random but nevertheless may result in
a rich statistical structure of the spike sequence. In particular, contrary to the popular renewal …