Abstract
The complexity of neural networks of the brain makes studying these networks through computer simulation challenging. Conventional methods, where one models thousands of individual neurons, can take enormous amounts of computer time even for models of small cortical areas. An alternative is the population density method in which neurons are grouped into large populations and one tracks the distribution of neurons over state space for each population. We discuss the method in general and illustrate the technique for integrate-and-fire neurons. (C) 2000 Elsevier Science B.V. All rights reserved.
Original language | English (US) |
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Pages (from-to) | 487-492 |
Number of pages | 6 |
Journal | Neurocomputing |
Volume | 32-33 |
DOIs | |
State | Published - Jun 2000 |
Externally published | Yes |
Event | The 8th Annual Computational Neuroscience Meeting (CNS'99) - Pittsburgh, PA, USA Duration: Jul 18 1999 → Jul 22 1999 |
Keywords
- Computer simulation
- Network modeling
- Populations
- Probability density function