ML Anthology

Optimizing Synaptic Conductance Calculation for Network Simulations

William W. Lytton
NeCo 1996 pp. 501-509
doi:10.1162/NECO.1996.8.3.501 /neco/1996/lytton1996neco-optimizing/

Abstract

High computational requirements in realistic neuronal network simulations have led to attempts to realize implementation efficiencies while maintaining as much realism as possible. Since the number of synapses in a network will generally far exceed the number of neurons, simulation of synaptic activation may be a large proportion of total processing time. We present a consolidating algorithm based on a recent biophysically-inspired simplified Markov model of the synapse. Use of a single lumped state variable to represent a large number of converging synaptic inputs results in substantial speed-ups.

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Cite

Text

Lytton. "Optimizing Synaptic Conductance Calculation for Network Simulations." Neural Computation, 1996. doi:10.1162/NECO.1996.8.3.501

Markdown

[Lytton. "Optimizing Synaptic Conductance Calculation for Network Simulations." Neural Computation, 1996.](https://mlanthology.org/neco/1996/lytton1996neco-optimizing/) doi:10.1162/NECO.1996.8.3.501

BibTeX

@article{lytton1996neco-optimizing,
  title     = {{Optimizing Synaptic Conductance Calculation for Network Simulations}},
  author    = {Lytton, William W.},
  journal   = {Neural Computation},
  year      = {1996},
  pages     = {501-509},
  doi       = {10.1162/NECO.1996.8.3.501},
  volume    = {8},
  url       = {https://mlanthology.org/neco/1996/lytton1996neco-optimizing/}
}