A comparison of deterministic and stochastic simulations of neuronal vesicle release models
Modchang, Charin; Nadkarni, Suhita; Bartol, Thomas M; Triampo, Wannapong; Sejnowski, Terrence J; Levine, Herbert; Rappel, Wouter-Jan; Modchang, Charin; Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA 92093, USA; R&D Group of Biological and Environmental Physics, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand; Nadkarni, Suhita; Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA 92093, USA; Bartol, Thomas M; Computational Neurobiology Laboratory, The Salk Institute, La Jolla, CA 92037, USA; Triampo, Wannapong; R&D Group of Biological and Environmental Physics, Department of Physics, Faculty of Science, Mahidol University, Bangkok 10400, Thailand; Sejnowski, Terrence J; Howard Hughes Medical Institute and The Salk Institute for Biological Studies, La Jolla, CA 92037, USA; Levine, Herbert; Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA 92093, USA; Rappel, Wouter-Jan; Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, CA 92093, USA
Журнал:
Physical Biology
Дата:
2010-06-01
Аннотация:
We study the calcium-induced vesicle release into the synaptic cleft using a deterministic algorithm and MCell, a Monte Carlo algorithm that tracks individual molecules. We compare the average vesicle release probability obtained using both algorithms and investigate the effect of the three main sources of noise: diffusion, sensor kinetics and fluctuations from the voltage-dependent calcium channels (VDCCs). We find that the stochastic opening kinetics of the VDCCs are the main contributors to differences in the release probability. Our results show that the deterministic calculations lead to reliable results, with an error of less than 20%, when the sensor is located at least 50 nm from the VDCCs, corresponding to microdomain signaling. For smaller distances, i.e. nanodomain signaling, the error becomes larger and a stochastic algorithm is necessary.
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