ArticleJournal of neuroscience methods2006
An efficient stochastic diffusion algorithm for modeling second messengers in dendrites and spines.
Article in Journal of neuroscience methods, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Systems modeling predicts that mitochondria ER contact sites regulate the postsynaptic energy landscape.NPJ systems biology and applications · 2021Article
- A first-passage approach to diffusion-influenced reversible binding and its insights into nanoscale signaling at the presynapse.Scientific reports · 2021Article
- Asynchronous τ-leaping.The Journal of chemical physics · 2016Article
- Signaling pathways involved in striatal synaptic plasticity are sensitive to temporal pattern and exhibit spatial specificity.PLoS computational biology · 2013Article
- Subcellular location of PKA controls striatal plasticity: stochastic simulations in spiny dendrites.PLoS computational biology · 2012Article
- Colocalization of protein kinase A with adenylyl cyclase enhances protein kinase A activity during induction of long-lasting long-term-potentiation.PLoS computational biology · 2011Article
- An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.The Journal of chemical physics · 2011Article
- The role of type 4 phosphodiesterases in generating microdomains of cAMP: large scale stochastic simulations.PloS one · 2010Article
- Modelling the molecular mechanisms of synaptic plasticity using systems biology approaches.Nature reviews. Neuroscience · 2010Review
- Spine neck geometry determines spino-dendritic cross-talk in the presence of mobile endogenous calcium binding proteins.Journal of computational neuroscience · 2009Article
- Spino-dendritic cross-talk in rodent Purkinje neurons mediated by endogenous Ca2+-binding proteins.The Journal of physiology · 2007Article
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1 author.
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Abstract
Intracellular signaling pathways, which encompass both biochemical reactions and second messenger diffusion, interact non-linearly with neuronal membrane properties in their role as essential intermediaries for synaptic plasticity and neuromodulation. Computational modeling is a productive approach for investigating these phenomena; however, most current strategies for modeling neurons exclude signaling pathways. To overcome this deficiency, a new algorithm is presented to simulate stochastic diffusion in a highly efficient manner. The gain in speed is obtained by considering collections of molecules, instead of tracking the movement of individual molecules. The probability of a molecule leaving a spatially discrete compartment is used to create a lookup table that stores the probability of k(m) molecules leaving the compartment as a function of the total number of molecules in the compartment. During the simulation, the number of molecules leaving the compartment is determined using a uniform random number as an index into the lookup table. Simulations illustrate the accuracy of this algorithm by comparing it with the theoretical solution for deterministic diffusion. Additional simulations show how spines on a dendritic branch compartmentalize diffusible molecules. The efficiency of the algorithm is sufficient to allow simulation of second messenger pathways in a multitude of spines on an entire neuron.
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