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Computationally efficient simulation of signaling pathways underlying synaptic plasticity

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SDBW04 - Spatially distributed stochastic dynamical systems in biology

Co-authors: Jedrzejewski-Szmek, Zbigniew (George Mason University), Jedrzejewska-Szmek, Joanna (George Mason University)

Long-lasting forms of long term potentiation (LTP) represent one of the major cellular mechanisms underlying learning and memory. The degree to which neuromodulatory systems, e.g. beta-adrenergic receptors or dopamine receptors, modify LTP and memory is still unclear. Computational modeling of the signaling pathways activated by neuromodulatory and cortical inputs is one approach for investigating these issues. Cortical inputs are spatially specific, often synapse onto spines and produce changes in small numbers of molecules. In contrast, neuromodulatory inputs tend to to be spatially dispersed. The interaction between these two inputs can lead to changes lasting minutes to hours. Because of the heavy computational cost of performing simulations at these diverse spatial and temporal scales, we have developed an asynchronous, adaptive tau-leaping algorithm for reaction-diffusion systems. For every reaction and diffusion channel at each step of the simulation the more efficien t of an exact stochastic event or a tau-leap is implemented from the priority queue. This new approach removes the inherent tradeoff between speed and accuracy in stiff systems which was present in all tau-leaping methods by allowing each reaction channel to proceed at its own pace. We use our computational efficient tau leaping algorithm to investigate how activation of neuromodulatory systems interacts with cortical inputs to modify the development of synaptic plasticity.

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