Features of the current version

Easy to use python interface

Since PCSIM is incorporated into python it is not necessary to learn any other script laguage to set up the simulation. This is all done with python scripts. Furthermore the results of a simulation are directly returned as python arrays and hence any plotting and analysis tools available in python (via the matplotlib package) can easily be applied.

Distributed Simulation

Via MPI

Different levels of modeling

Different neuron models: leaky-integrate-and-fire neurons, compartmental based neurons, sigmoidal neurons. Different synapse models: static synapses and a certain model of dynamic synapses are available for spiking as well as for sigmoidal neurons. Spike time dependent synaptic plasticity is also implemented.

Object oriented design

We adopted an object oriented design for PCSIM which is similar to the approaches taken in GENESIS and NEURON. That is there are objects (e.g. a LifNeuron object implements the standard leaky-integrate-and-fire model) which are interconnected by means of some signal channels. The creation of objects, the connection of objects and the setting of parameters of the objects is controlled at the level of python scipts whereas the actual simulation is done in the fast C++ core.

Fast C++ core

Since PCSIM is implemented in C++ and is not yet as general as GENESIS or NEURON simulations are performed quite fast. We also implemented some ideas from event driven simulators like SpikeNet which result on an average speedup of 3 (assuming an average firing rate of the neurons of 20Hz and short synaptic time constants) compared to a standard fixed time step simulation scheme.

GPL Licensed

PCSIM is distributed under the GNU General Public License