Preprint available as neurocomputing2004.pdf
A short introduction to how "integrate and fire" cells are implemented in NEURON. Network simulations that use only artificial spiking cells are extremely efficient, with runtimes proportional to the total number of synaptic inputs received and independent of the number of cells or problem time. These cells are completely interoperable with biophysical model neurons (oxymoronically called "real model neurons" by some)--i.e. they can receive synaptic inputs from, and deliver inputs to, any combination of artificial spiking neurons and/or biophysical model neurons. Also see our SFN 2002 poster discrete_event_poster.pdf.
Discrete event simulation in the NEURON environment
| Title | Discrete event simulation in the NEURON environment |
| Publication Type | Journal Article |
| Year of Publication | 2004 |
| Authors | Hines, M. L., and Carnevale N. T. |
| Journal | Neurocomputing |
| Volume | 58 |
| Pagination | 1117–1122 |
| Keywords | Artificial cells; Spiking nets; Discrete events; Simulation; Integrate and fire |
| Abstract | The response of many types of integrate and fire cells to synaptic input can be computed analytically and their threshold crossing either computed analytically or approximated to high accuracy via Newton approximation. The NEURON simulation environment simulates networks of such artificial spiking neurons using discrete event simulation techniques in which computations are performed only when events are received. Thus, computation time is proportional only to the number of events delivered and is independent of the number of cells or problem time. |
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