Dynamical modeling of neural systems and brain functions has a history of success over the
last half century. This includes, for example, the explanation and prediction of some features …

The brain is a highly modular structure. To exploit modularity, it is necessary that spiking
activity can propagate from one module to another while preserving the information it …

Neural network modeling is often concerned with stimulus-driven responses, but most of the
activity in the brain is internally generated. Here, we review network models of internally …

Both theoretical and experimental evidence indicate that synaptic excitation and inhibition in
the cerebral cortex are well-balanced during the resting state and sensory processing. Here …

Transmission of signals within the brain is essential for cognitive function, but it is not clear
how neural circuits support reliable and accurate signal propagation over a sufficiently large …

Recent theoretical work has provided a basic understanding of signal propagation in
networks of spiking neurons, but mechanisms for gating and controlling these signals have …

A neuronal network inspired by the anatomy of the cerebral cortex was simulated to study
the self-organization of spiking neurons into neuronal groups. The network consisted of 100 …

Sequential neural activity patterns are as ubiquitous as the outputs they drive, which include
motor gestures and sequential cognitive processes. Neural sequences are long, compared …

A train of action potentials (a spike train) can carry information in both the average firing rate
and the pattern of spikes in the train. But can such a spike-pattern code be supported by …

Inhibitory neurons, although relatively few in number, exert powerful control over brain
circuits. They stabilize network activity in the face of strong feedback excitation and actively …