We develop a simulator for spiking neural networks named Brian, with Dan Goodman (Goodman & Brette 2008; 2009; Brette & Goodman, 2009; Goodman & Brette 2013a; 2013b). The motto of Brian is “a simulator should not only save the time of processors, but also the time of scientists” (Brette 2012). It is written in Python and equation-oriented (Stimberg et al. 2014): users define models themselves by providing their mathematical definition (as opposed to built-in models). This choice makes Brian ideally suited for rapid model writing and for teaching. The first version of Brian relied on vectorised algorithms to make simulations efficient for large networks (Brette & Goodman 2011). The new version of Brian (2.0) relies on code generation to simulate models very efficiently on various platforms.
We have also developed a toolbox for Brian to fit spiking models to electrophysiological recordings (Rossant et al 2010; 2011), as well as an auditory toolbox (Fontaine et al 2011).
Our current projects include: running Brian on diverse platforms such as GPU (Brette & Goodman, 2012), FPGA and clusters, using Brian to run electrophysiology experiments, and further develop multicompartmental modeling in Brian (which is already in Brian 2.0).
- Brian website: briansimulator.org
- Documentation for Brian 2: brian2.readthedocs.org
- Github repository for Brian 2: github.com/brian-team/brian2
- Brette R (2012). On the design of script languages for neural simulation. Network 23(4), 150-156.
- Brette R and DF Goodman (2011). Vectorised algorithms for spiking neural network simulation, Neural Comput 23(6), 1503-1535.
- Brette R and Goodman D (2012). Simulating spiking neural networks on GPU. Network 23(4), 167-182.
- Brette, R. (2006). Exact simulation of integrate-and-fire models with synaptic conductances. Neural Comput 18(8): 2004-2027. (code)
- Brette, R. (2007). Exact simulation of integrate-and-fire models with exponential currents. Neural Comput 19(10): 2604-2609. (code)
- Brette, R. (2009). Generation of correlated spike trains. Neural Comput 21(1): 188–215. (code)
- Brette, R. and D. Goodman (2009). Brian: a simple and flexible simulator for spiking neural networks. The Neuromorphic Engineer, doi:10.2417/1200907.1659.
- Brette, R. et al (2007). Simulation of networks of spiking neurons: a review of tools and strategies. J Comput Neurosci 23(3):349-98.
- Fontaine B, Goodman DFM, Benichoux F, Brette R (2011). Brian Hears: online auditory processing using vectorisation over channels. Front Neuroinf 5:9. doi: 10.3389/fninf.2011.00009.
- Goodman D and R Brette (2008). Brian: a simulator for spiking neural networks in Python. Front Neuroinform 2:5. doi:10.3389/neuro.11.005.2008.
- Goodman DFM and Brette R (2013a) Brian simulator. Scholarpedia, 8(1):10883.
- Goodman DFM and Brette R (2013b). Brian Spiking Neural Network Simulator. In: Jaeger D., Jung R. (Ed.) Encyclopedia of Computational Neuroscience: SpringerReference. Springer-Verlag Berlin Heidelberg, 2013. DOI: 10.1007/SpringerReference_348318 2013-07-28 17:58:33 UTC.
- Goodman, D. and R. Brette (2009). The Brian simulator. Front Neurosci doi:10.3389/neuro.01.026.2009.
- Rossant C, Goodman DF, Fontaine B, Platkiewicz J, Magnusson AK and Brette R (2011). Fitting neuron models to spike trains.Front Neurosci. 5:9. doi: 10.3389/fnins.2011.00009.
- Rossant C, Goodman DF, Platkiewicz J and Brette R (2010). Automatic fitting of spiking neuron models to electrophysiological recordings. Front. Neuroinform. doi:10.3389/neuro.11.002.2010
- Stimberg M, Goodman DFM, Benichoux V, Brette R (2014).Equation-oriented specification of neural models for simulations. Frontiers Neuroinf, doi: 10.3389/fninf.2014.00006