Monte Carlo methods for simulating realistic synaptic microphysiology using MCell

Computational Neuroscience: Realistic Modeling for Experimentalists

Volumn , Issue , 2000, Pages 87-127

  Stiles, Joel R ^a   Bartol, Thomas M ^b  

^a PITTSBURGH SUPERCOMPUTING CENTER   (United States)

^b SALK INSTITUTE FOR BIOLOGICAL STUDIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85057660342     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (35)

1. Anglister, L., Stiles, J. R., and Salpeter, M. M., Acetylcholinesterase density and turnover number at frog neuromuscular junctions, with modeling of their role in synaptic function, Neuron, 12, 783, 1992.
2. Arkin, A. P., Ross, J., and McAdams, H. H., Stochastic kinetic analysis of developmental pathway bifurcation in phage λ-infected E. coli cells, Genetics, 149, 1633, 1998.
3. Barbour, B. and Hausser, M., Intersynaptic diffusion of neurotransmitter, Trends Neurosci., 20, 377, 1997.
4. Barrow, G. M., Physical Chemistry for the Life Sciences, McGraw-Hill, New York, 1981.
5. Bartol, T. M., Jr., Land, B. R., Salpeter, E. E., and Salpeter, M. M., Monte Carlo simulation of MEPC generation in the vertebrate neuromuscular junction, Biophys. J., 59, 1290, 1991.
6. Bennett, M. R., Farnell, L., and Gibson, W. G., Quantal transmission at purinergic synapses: stochastic interaction between ATP and its receptors, J. Theor. Biol., 175, 397, 1995.
7. Bennett, M. R., Farnell, L., Gibson, W. G., and Lavidis, N. A., Synaptic transmission at visualized sympathetic boutons: stochastic interaction between acetylcholine and its receptors, Biophys. J., 72, 1595, 1997.
8. Clements, J. D., Transmitter timecourse in the synaptic cleft: its role in central synaptic function, Trends Neurosci., 19, 163, 1996.
9. Crank, J., The Mathematics of Diffusion, Oxford University Press, London, 1956.
10. Denes, J. and Krewski, D., An exact representation for the generating function for the Moolgavkar-Venzon-Knudson two-stage model of carcinogenesis with stochastic stem cell growth, Math. Biosci., 131, 185, 1996.
11. Faber, D. S., Young, W. S., Legendre, P., and Korn, H., Intrinsic quantal variability due to stochastic properties of receptor-transmitter interactions, Science, 258, 1494, 1992.
12. Geiger, J. R. P., Roth, A., Taskin, B., and Jonas, P., Glutamate-mediated synaptic excitation of cortical interneurons, in Handbook of Experimental Pharmacology, Vol. 141, Retinoids, Ionotropic Glutamate Receptors in the CNS, Jonas, P. and Monyer, H., Eds., Springer-Verlag, Berlin, 363, 1999.
13. Kalos, M. H. and Whitlock, P. A., Monte Carlo Methods, Vol. I: Basics, John Wiley & Sons, New York, 1986.
14. Knuth, D., The Art of Computer Programming, MIT Press, Cambridge, 1969.
15. Kruk, P. J., Korn, H., and Faber, D. S., The effects of geometrical parameters on synaptic transmission: a Monte Carlo simulation study, Biophys. J., 73, 2874, 1997.
16. Land, B. R., Salpeter, E. E., and Salpeter, M. M., Acetylcholine receptor site density affects the rising phase of miniature endplate currents, Proc. Natl. Acad. Sci. U.S.A., 77, 3736, 1980.
17. Matthews-Bellinger, J. and Salpeter, M. M., Distribution of acetylcholine receptors at frog neuromuscular junctions with a discussion of some physiological implications, J. Physiol., 279, 197, 1978.
18. McQuarrie, D. A., Jachimowski, C. J., and Russell, M. E., Kinetics of small systems II, J. Chem. Phys., 40, 2914, 1964.
19. Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T., Numerical Recipes. The Art of Scientific Computing, Cambridge University Press, New York, 1986.
20. Rosenberry, T., Acetylcholinesterase, Adv. Enzymol., 43, 103, 1975.
21. Rubenstein, R. Y., Simulation and the Monte Carlo Method, John Wiley & Sons, New York, 1981.
22. Rusakov, D. A. and Kullmann, D. M., Extrasynaptic glutamate diffusion in the hippocampus: ultrastructural constraints, uptake, and receptor activation, J. Neurosci., 18, 158, 1998.
23. Rusakov, D. A., Kullmann, D. M., and Stewart, M. G., Hippocampal synapses: do they talk to their neighbors? Trends Neurosci., 22, 382, 1999.
24. Salpeter, M. M., Electron microscope autoradiography as a quantitative tool in enzyme cytochemistry: the distribution of acetylcholinesterase at motor endplates of a vertebrate twitch muscle, J. Cell Biol., 32, 379, 1967.
25. Salpeter, M. M., Electron microscope radioautography as a quantitative tool in enzyme cytochemistry. II. The distribution of DFP-reactive sites at motor endplates of a vertebrate twitch muscle, J. Cell Biol., 42, 122, 1969.
26. Salpeter, M. M., Vertebrate neuromuscular junctions: general morphology, molecular organization, and functional consequences, in The Vertebrate Neuromuscular Junction, Salpeter, M. M., Ed., Alan R. Liss, New York, 1987, 1.
27. Salpeter, M. M., Smith, C. D., and Matthews-Bellinger, J. A., Acetylcholine receptor at neuromuscular junctions by EM autoradiography using mask analysis and linear sources, J. Electron Microsc. Tech., 1, 63, 1984.
28. Schroeder, W., Martin, K., and Lorensen, B., The Visualization Toolkit, 2nd Ed., Prentice-Hall, Englewood Cliffs, NJ, 1998.
29. Smart, J. L. and McCammon, J. A., Analysis of synaptic transmission in the neuromuscular junction using a continuum finite element model, Biophys. J., 75, 1679, 1998.
30. Stiles, J. R., Van Helden, D., Bartol, T. M., Salpeter, E. E., and Salpeter, M. M., Miniature endplate current rise times <100 µs from improved dual recordings can be modeled with passive acetylcholine diffusion from a synaptic vesicle, Proc. Natl. Acad. Sci. U.S.A., 93, 5747, 1996.
31. Stiles, J. R., Bartol, T. M., Salpeter, E. E., and Salpeter, M. M., Monte Carlo simulation of neurotransmitter release using MCell, a general simulator of cellular physiological processes, in Computational Neuroscience, Bower, J. M., Ed., Plenum Press, New York, 1998, 279.
32. Stiles, J. R., Kovyazina, I.V., Salpeter, E. E., and Salpeter, M. M., The temperature sensitivity of miniature endplate currents is mostly governed by channel gating:evidence from optimized recordings and Monte Carlo simulations, Biophys. J., 77, 1177, 1999.
33. Stiles, J. R., Bartol, T. M., Salpeter, M. M., Salpeter, E. E., and Sejnowski, T. J., Synaptic variability: new insights from reconstructions and Monte Carlo simulations with MCell, in Synapses, Cowan, W. M., Stevens, C. F., and Sudhof, T. C., Eds., Johns Hopkins University Press, Baltimore, MD, in press.
34. Tomita, M., Hashimoto, K., Takahashi, K., Shimizu, T., Matsuzaki, Y., Miyoshi, F., Saito, K., Tanida, S., Yugi, K., Venter, J. C., and Hutchison, C., E-CELL: software environment for whole cell simulation, Bioinformatics, 15, 72, 1999.
35. Wahl, L. M., Pouzat, C., and Stratford, K. J., Monte Carlo simulation of fast excitatory synaptic transmission at a hippocampal synapse, J. Neurophysiol., 75, 597, 1996.