Population density methods for large-scale modelling of neuronal networks with realistic synaptic kinetics: cutting the dimension down to size.

@article{Haskell2001PopulationDM,
  title={Population density methods for large-scale modelling of neuronal networks with realistic synaptic kinetics: cutting the dimension down to size.},
  author={E. Haskell and Duane Q. Nykamp and Daniel Tranchina},
  journal={Network},
  year={2001},
  volume={12 2},
  pages={
          141-74
        }
}
Population density methods provide promising time-saving alternatives to direct Monte Carlo simulations of neuronal network activity, in which one tracks the state of thousands of individual neurons and synapses. A population density method has been found to be roughly a hundred times faster than direct simulation for various test networks of integrate-and-fire model neurons with instantaneous excitatory and inhibitory post-synaptic conductances. In this method, neurons are grouped into large… CONTINUE READING

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