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A comparison of deterministic and stochastic simulations of neuronal vesicle release models.


ABSTRACT: 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.

SUBMITTER: Modchang C 

PROVIDER: S-EPMC2892017 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature

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A comparison of deterministic and stochastic simulations of neuronal vesicle release models.

Modchang Charin C   Nadkarni Suhita S   Bartol Thomas M TM   Triampo Wannapong W   Sejnowski Terrence J TJ   Levine Herbert H   Rappel Wouter-Jan WJ  

Physical biology 20100526 2


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 d  ...[more]

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