Definition
A stochastic simulator that tracks the location and interactions of individual molecules, also known as Brownian motion simulator.
Detailed Description
Stochastic simulators are utilized to model an array of phenomena in neuroscience, ranging from vesicle release, to activation of signaling pathways by G protein-coupled receptors, to initiation of gene transduction. In the presynaptic terminal, action potentials do not always produce vesicle release; instead vesicles are released with some probability. G protein-coupled receptors may activate a few to many G proteins, which diffuse within the membrane to find an enzyme or ion channel to react with. The smaller number of synaptic channels at some synapses produces variability in the postsynaptic response. The variability in numerous experimental measurements attests to the stochastic nature of neuron activity.
Ion channel opening, vesicle release, and signaling pathways all can be simulated using a number of techniques,...
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References
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Blackwell, K. (2014). Particle-Based Stochastic Simulators. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_191-1
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_191-1
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Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4614-7320-6
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Latest
Particle-Based Stochastic Simulators- Published:
- 11 May 2018
DOI: https://doi.org/10.1007/978-1-4614-7320-6_191-2
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Original
Particle-Based Stochastic Simulators- Published:
- 20 March 2014
DOI: https://doi.org/10.1007/978-1-4614-7320-6_191-1