Features
General
- Python based user interface
- Built-in simulation language interpreter
- Multi-threading to use multi-processor machines efficiently
- MPI-parallelism to use computer clusters and super computers
Neuron models
Integrate and fire (IAF) neuron models with current based synapses (delta-, exponential- and alpha-function shaped)
Integrate and fire neuron models with conductance-based synapses
Adaptive-exponential integrate and fire neuron model (AdEx)
(Brette & Gerstner, 2005) - the standard in the FACETS EU project ([1])MAT2 neuron model (Kobayashi et al. 2009)
Hodgkin-Huxley type models with one compartment
Neuron models with few compartments
Synapse models
- Static synapses
- Spike-timing dependent plasticity (STDP)
- Short-term plasticity (Tsodyks et al. 2000)
- Neuromodulatory synapses using dopamine
Network models
NEST 2.x
- Topology Module for creating complex networks (Topology Module User Manual)
NEST 3.0
Interoperability
- Interface to the Multi Simulator Coordinator MUSIC
- Backend for the simulator-independent modeling tool PyNN
Accuracy
Each neuron model is assigned an appropriate solver
Exact Integration is used for suitable neuron models
By default spikes are restricted to the grid spanned by the computation time step
For some neuron models spike interaction in continuous time is available
Verification
After installation NEST can be verified by an automatic testsuite
The testsuite is automatically run after each modification of the NEST sources. You can watch the current status on our Continuous Integration system.
Supported platforms
- Linux
- Mac OS X
- Virtual machines for use under Windows
- IBM BlueGene
By support we mean that we regularly test and use NEST on recent versions of these systems and that NEST therefore should work on those systems. It should not be construed as any warranty that NEST will run on any particular system.