We review different aspects of the simulation of spiking neural networks. We start by
reviewing the different types of simulation strategies and algorithms that are currently …

Synaptic plasticity is considered to be the biological substrate of learning and memory. In
this document we review phenomenological models of short-term and long-term synaptic …

The Neural Simulation Tool NEST is a computer program for simulating large
heterogeneous networks of point neurons or neurons with a small number of compartments …

“Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di. ens.
fr). It is an intuitive and highly flexible tool for rapidly develo** new models, especially …

The digital neuromorphic hardware SpiNNaker has been developed with the aim of
enabling large-scale neural network simulations in real time and with low power …

Self-organized criticality refers to the spontaneous emergence of self-similar dynamics in
complex systems poised between order and randomness. The presence of self-organized …

The balanced random network model attracts considerable interest because it explains the
irregular spiking activity at low rates and large membrane potential fluctuations exhibited by …

Oscillatory activity plays a crucial role in corticospinal control of muscle synergies and is
widely investigated using corticospinal and intermuscular synchronization. However, the …

For simulations of neural networks, there is a trade-off between the size of the network that
can be simulated and the complexity of the model used for individual neurons. In this study …

Progress in science depends on the effective exchange of ideas among scientists. New
ideas can be assessed and criticized in a meaningful manner only if they are formulated …