Reaction-diffusion in the NEURON simulator

McDougal, Robert A.; Hines, Michael L.; Lytton, William W.

doi:10.3389/fninf.2013.00028

Cited by 67 publications

(82 citation statements)

References 42 publications

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“…Event (19,11) comes from LP 15, arriving at channel [16,15] (a channel is marked in the format [host LP, source LP]), finds submit of this channel to be 0, and is submitted to the LPEQ of LP 16, submit is set to (19,11); submitT rack of LPEQ 16 is empty. Then this event is submitted to TEQ, the pointer to (19,11) is pushed at the top of submitT rack and the insertion of (19, 11) now ends.…”

Section: Definitionmentioning

confidence: 99%

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NTW-Mt

Lin

Tropper

Patoary

et al. 2015

Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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This paper describes a parallel discrete event simulator, Neuron Time Warp-Multi Thread (NTW-MT), developed for the simulation of reaction diffusion models of neurons. The simulator was developed as part of the NEURON project and is intended to be included in NEURON. It relies upon a stochastic discrete event model developed for chemical reactions. NTW-MT is optimistic and thread-based, in which communication latency among threads within the same process is minimized by pointers. We investigate the performance of NTW-MT on a reaction-diffusion model for the transmission of calcium waves in a neuron. Calcium plays a fundamental role in the second messenger system of a neuron. However, the mechanism by which calcium waves are transmitted is not entirely understood. Stochastic models are more realistic than deterministic models for small populations of ions such as those found in apical dendrites. To be more precise, we simulate a stochastic discrete event model for calcium wave propagation on an unbranched apical dendrite of a hippocampal pyramidal neuron. We examine the performance of NTW-MT on this calcium wave model and compare it to the performance of (1) a process based op- * This author is affiliated with State timistic simulator and (2) a threaded simulator which uses a single priority (SQ) queue for each thread. Our multithreaded simulator is shown to achieve superior performance to these simulators.

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Section: Definitionmentioning

confidence: 99%

“…It makes use of deterministic simulators for the reaction diffusion model [15] and for electrical models. We are collaborating with the NEURON group; our intention is to develop parallel discrete event simulators suitable for simulating the reaction diffusion models.…”

Section: Introductionmentioning

confidence: 99%

NTW-Mt

Lin

Tropper

Patoary

et al. 2015

Proceedings of the 3rd ACM SIGSIM Conference on Principles of Advanced Discrete Simulation

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“…NEURON is very flexible and supports a wide class of models. Recently, NEURON was extended to incorporate reaction-diffusion models so that it would be able to simulate chemical reactions of diffusive ions (example Ca 2+ ) as well as electric signals and allow these two types of information to be combined to understand diseases [30]. NEURON as released currently only support deterministic, although there is infrastructure to support stochastic using NTW.…”

Section: Neuron [28] Is a Simulation Environment Primarily Developed mentioning

confidence: 99%

Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron

Patoary

Tropper

McDougal

et al. 2019

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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the correctness and performance of NTW by comparing it to a sequential deterministic simulation in NEURON. The derivation of a discrete event calcium wave model using the stochastic IP 3 R structure is one of my main scientific contributions of this thesis. This newly derived stochastic discrete event calcium wave model is described in chapter-5. In high performance issue, a dynamic load balancing algorithm and a dynamic window control algorithm for NTW was also developed for the stochastic calcium wave model. We use Q-learning to determine the basic control parameters of the algorithm. Prof. Tropper motivated me to employ Q-learning to optimize the performance of NTW in calcium wave simulation. Developing such an intelligent dynamic load balancing algorithm with dynamic window control is another research contribution of this thesis. All algorithms are described in chapter 6. vi ABSTRACTThe intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and the calcium concentrations are so low that one molecule diffusing into the compartment can make a nontrivial difference in calcium concentration. Such events can affect dynamics discretely in such a way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. My research focuses on the development of a high performance parallel discrete event simulation environment, NTW , which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-cellular calcium signaling. We make use of two models, a calcium buffer model and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a sequential deterministic simulation in NEURON. NEURON is a framework for simulating neurons which is used by neuroscientists world-wide. Our work is part of the NEURON project and has the long term goal of developing a multiscale simulation for large scale neuronal networks. We derived a discrete event calcium wave model from a deterministic model using the stochastic inositol 1,4,5-trisphosphate receptors, IP 3 R, structure. A dynamic load balancing algorithm and a dynamic window control algorithm for NTW was also developed for the stochastic calcium wave model.We make use of Q-learning to determine the basic control parameters of the algorithm.

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“…ion, enzyme. The activity can be represented by (1) reaction that leads to disappearance of reactants and generation of products; (2) diffusion that can alter concentration at individual region [1]. In this perspective, to model and simulate the reaction and diffusion within and among cells can discover molecular dynamics in those biochemical systems, and then help to understand and affect the behaviour of those systems.…”

Section: Introductionmentioning

confidence: 98%

“…In neuroscience community, most simulators, e.g. NEURON [2], GENESIS [3], VCell [4] etc., provide deterministic solutions. However, a continuous model is not appropriate for a small number of molecules, e.g.…”

Section: Introductionmentioning

confidence: 99%

Parallel Discrete Event Simulation of Stochastic Reaction and Diffusion Using Reverse Computation

Lin

Yao

2015

2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity)

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Parallel discrete event simulation consumes massive memory, involves frequent allocation and deallocation, and generates huge amount of data, which makes the memory usage an important issue for performance. In this paper, we present our reverse computation approach in our multi-threaded parallel discrete event simulator used for large scale stochastic reactiondiffusion simulation. We compute the reverse control code to record what operation an event did on the state of the host Logical Process during forward processing, and undo the operation according to the corresponding code during recovering that event.As the results on two versions of calcium wave model show, the reverse computation version achieved better performance than the state-saving version-it saved about 33% and 36% execution time for the two models respectively when two processing threads were used.

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Reaction-diffusion in the NEURON simulator

Cited by 67 publications

References 42 publications

NTW-Mt

NTW-Mt

Parallel Stochastic Discrete Event Simulation of Calcium Dynamics in Neuron

Parallel Discrete Event Simulation of Stochastic Reaction and Diffusion Using Reverse Computation

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