The asymmetric particle population density method for simulation of coupled noisy oscillators
Many biological phenomena can be modeled by the collective activity of a population of individual units. A common strategy for simulating such a system, the population density approach, is to take the macroscopic limit and track a population density function. Here, we develop the asymmetric particle...
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Veröffentlicht in: | Journal of computational physics 2023-09, Vol.488, p.112157, Article 112157 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Many biological phenomena can be modeled by the collective activity of a population of individual units. A common strategy for simulating such a system, the population density approach, is to take the macroscopic limit and track a population density function. Here, we develop the asymmetric particle population density (APPD) method that efficiently and accurately simulates populations with complex behaviors that are infeasible for previous population density-based methods. The APPD method is well-suited for a parallel implementation. Our method can accurately reproduce complex macroscopic behaviors such as inhibitory coupling-induced clustering and noise-induced firing while being faster than the direct simulation. We compare the method's performance against direct Monte-Carlo simulation and verify its accuracy by applying it to the well-studied Hodgkin-Huxley model with a range of challenging scenarios.
•Asymmetric particle population density (APPD) method efficiently simulates complex behaviors of noisy coupled oscillators.•Well-suited for parallel implementation.•Faster than Monte-Carlo simulation.•Validation using the Hodgkin-Huxley model with challenging scenarios. |
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ISSN: | 0021-9991 1090-2716 |
DOI: | 10.1016/j.jcp.2023.112157 |