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Brian: a simulator for spiking neural networks in Python
Open accessAbstract
"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 developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.
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Cited by
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Schuman, C. D., Kulkarni, S. R., Parsa, M., Mitchell, J. P., Date, P., & Kay, B. (2022) · Nature Computational Science · doi:10.1038/s43588-021-00184-y · Cited by 1,117
Brian 2, an intuitive and efficient neural simulator
Stimberg, M., Brette, R., & Goodman, D. F. (2019) · eLife · doi:10.7554/elife.47314 · Cited by 749
Self-citationMurray, J. D., Anticevic, A., Gancsos, M., Ichinose, M., Corlett, P. R., Krystal, J. H., & Wang, X.-J. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhs370 · Cited by 255
NetPyNE, a tool for data-driven multiscale modeling of brain circuits
Dura-Bernal, S., Suter, B. A., Gleeson, P., Cantarelli, M., Quintana, A., Rodriguez, F., Kedziora, D. J., Chadderdon, G. L., Kerr, C. C., Neymotin, S. A., et al. (2019) · eLife · doi:10.7554/elife.44494 · Cited by 169
A dendritic disinhibitory circuit mechanism for pathway-specific gating
Yang, G. R., Murray, J. D., & Wang, X.-J. (2016) · Nature Communications · doi:10.1038/ncomms12815 · Cited by 148
Metadata
- Authors
- Goodman, D.
- Venue
- Frontiers in Neuroinformatics
- Publisher
- Frontiers Media SA
- Published
- 2008
- Volume
- 2
- Pages
- 5-5
- ISSN
- 1662-5196 (ISSN-L)
- OpenAlex
- W2018027127
- Cited by
- 518
- References
- 0
- FWCI
- 9.74
- Type
- journal article
- Language
- en
- Open access
- gold
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