ModelDB: Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011)

Vectorized algorithms for spiking neural network simulation (Brette and Goodman 2011)

Accession: 137989

"... We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages."
Reference: Brette R, Goodman DF (2011) Vectorized Algorithms for Spiking Neural Network Simulation. Neural Comput [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	Brian (web link to method);
Model Concept(s):	Methods;
Implementer(s):	Brette R; Goodman PH;

Model files (located externally to ModelDB) Help downloading and running models

Here is a web link to the Brian simulator

http://www.briansimulator.org/

whose vector methods are disscussed in the article

Brette R, Goodman DF (2011) Vectorized Algorithms for Spiking Neural
Network Simulation. Neural Comput

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