, Volume 3, Issue 1, pp 49–63 | Cite as

A modeling environment with three-dimensional morphology, A-Cell-3D, and Ca2+ dynamics in a spine

Original Article


A-Cell-3D was developed to model and simulate a neuron with three-dimensional (3D) morphology utilizing graphic user interface (GUI)-based operations. A-Cell-3D generates and compartmentalizes 3D morphologies of a whole cell or a part of a cell based on a small number of parameters. A-Cell-3D has functions for embedding biochemical reactions and electrical equivalent circuits in the generated 3D morphology, automatically generating a simulation program for spatiotemporal numerical integration, and for visualizing the simulation results. A-Cell-3D is a free software and will be a powerful tool for both experimental and theoretical researchers in modeling and simulating neurons.

The Ca2+ dynamics in a dendritic spine and its parent dendrite were modeled and simulated to demonstrate the capabilities of A-Cell-3D. The constructed reaction-diffusion model comprised Ca2+ entry at the spine head, Ca2+ buffering by endogenous buffers, Ca2+ extrusion, and Ca2+ diffusion with or without exogenous Ca2+ indicator dyes. A simulation program was generated by A-Cell-3D, and differential equations were numerically integrated by the fourth-order Runge-Kutta method.

Index Entries

Modeling simulation morphology reaction diffusion Hodgkin-Huxley equation neuron Ca2+ dynamics spine 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Allbritton, N. L., Meyer, T., and Stryer, L. (1992) Range of messenger action of calcium ion and inositol 1,4,5-triphosphate. Science 258, 1812–1815.PubMedCrossRefGoogle Scholar
  2. Bhalla, U. S. and Iyengar, R. (1999) Emergent properties of networks of biological signaling pathways. Science 283, 381–387.PubMedCrossRefGoogle Scholar
  3. Burnashev, N., Zhou, Z., and Neher, E. (1995) Fractional calcium currents through recombinant GluR channels of the NMDA, AMPA and kainate receptor subtypes. J. Physiol. 485, 403–418.PubMedGoogle Scholar
  4. Connor, J. A., Wadman, W. J., Hockberger, P. E., and Wong, R. K. S. (1988) Sustained dendritic gradients of Ca2+ induced by excitatory amino acids in CA1 hippocampal neurons. Science 240, 649–653.PubMedCrossRefGoogle Scholar
  5. De Schutter, E. and Bower, J. M. (1993) Sensitivity of synaptic plasticity to the Ca2+ permeability of NMDA channels: a model of long-term potentiation in hippocampal neurons. Neural Comp. 5, 681–694.CrossRefGoogle Scholar
  6. De Schutter, E. and Bower, J. M. (1994a) An active membrane model of the cerebellar Purkinje cell. I. Simulation of current clamps in slice. J. Neurophysiol. 71, 375–400.PubMedGoogle Scholar
  7. De Schutter, E. and Bower, J. M. (1994b) An active membrane model of the cerebellar Purkinje cell II. Simulation of synaptic responses. J. Neurophysiol. 71, 401–419.PubMedGoogle Scholar
  8. De Schutter, E. and Smolen, P. (1998) Calcium dynamics in large neuronal models. In: Methods in Neuronal Modeling, 2nd edn. Koch, C. and Segev, I. (eds.) The MIT Press, Cambridge, MA, pp.211–250.Google Scholar
  9. Dosemeci, A. and Albers, R. W. (1996) A mechanism for synaptic frequency detection through autophosphorylation of Cam kinase II. Biophys. J. 70, 2493–2501.Google Scholar
  10. Fischer, M., Kaech, S., Knutti, D., and Matus, A. (1998) Rapid actin-based plasticity in dendritic spines. Neuron 20, 847–854.PubMedCrossRefGoogle Scholar
  11. Gabso, M., Neher, E., and Spira, M. E. (1997) Low mobility of the Ca2+ buffers in axons of cultured Aplysia neurons. Neuron 18, 473–481.PubMedCrossRefGoogle Scholar
  12. Goldberg, J. H., Tamas, G., Aronov, D., and Yuste, R. (2003) Calcium microdomains in aspiny dendrites. Neuron 40, 807–821.PubMedCrossRefGoogle Scholar
  13. Ichikawa, K. (1994) Transduction steps which characterize retinal cone photocurrent induced by flash stimuli. Neurosci. Res. 20, 337–343.PubMedCrossRefGoogle Scholar
  14. Ichikawa, K. (1996) Modeling and analysis of spatio-termporal change in [Ca2+]i in a retinal rod outer segment. Neurosci. Res. 25, 137–144.Google Scholar
  15. Ichikawa, K. (2001) A-Cell: graphical user interface for the construction of biochemical reaction models. Bioinformatics 17, 483–484.PubMedCrossRefGoogle Scholar
  16. Kamiyama, Y., Ogura, T., and Usui S. (1996) Ionic current model of the vertebrate rod photoreceptor. Vis. Res. 36, 4059–4068.CrossRefGoogle Scholar
  17. Koch, C. and Zador, A. (1993) The function of dendritic spines: devices subserving biochemical rather than electrical compartmentalization. J. Neurosci. 13, 413–422.PubMedGoogle Scholar
  18. Koch, C. (1999) Biophysics of Computation. Oxford University Press, New York.Google Scholar
  19. Lamprecht, R. and LeDoux, J. (2004) Structural plasticity and memory. Nat. Rev. Neurosci. 5, 45–54.PubMedCrossRefGoogle Scholar
  20. Lisman, J.E. (1989) A mechanism for the Hebb and the anti-Hebb processes underlying learning and memory. Proc. Natl. Acad. Sci. USA 86, 9574–9578.PubMedCrossRefGoogle Scholar
  21. Majewska, A., Tashiro, A., and Yuste, R. (2000) Regulation of spine calcium dynamics by rapid spine motility. J. Neurosci. 20, 8262–8268.PubMedGoogle Scholar
  22. Maravall, M., Mainen, Z. F., Sabatini, B. L., and Svoboda, K. (2000) Estimating intracellular calcium concentrations and buffering without wavelength ratioing. Biophys. J. 78, 2655–2667.PubMedCrossRefGoogle Scholar
  23. Mell, B. W. (1993) Synaptic integration in an excitable dendritic tree. J. Neurophysiol. 70, 1086–1101.Google Scholar
  24. Okamoto, H. and Ichikawa, K. (2000) Switching characteristics of a model for biochemical-reaction network describing autophosphorylation versus dephosphorylation of Ca2+/calmodulin-dependent protein kinase II. Bio. Cyber. 82, 35–47.CrossRefGoogle Scholar
  25. Quandroni, R. and Knopfel, T. (1994) Compartmental models of type A and type B guinea pig medial vestibular neurons. J. Neurophysiol. 72, 1911–1924.Google Scholar
  26. Rogers, M., Dani, J. A., and Nozawa, M. (1995) Comparison of quantitative calcium flux through NMDA, ATP, and ACh receptor channels. Biophys. J. 68, 501–506.PubMedGoogle Scholar
  27. Schaff, J., Fink, C. C., Slepchenko, B., Carson, J. H., and Loew, L. M. (1997) A general computational framework for modeling cellular structure and function. Biophys. J. 73, 1135–1146.PubMedGoogle Scholar
  28. Segal, M., Korkotian, E., and Murphy, D. D. (2000) Dendritic spine formation and pruning: common cellular mechanisms? TINS 23, 53–57.PubMedGoogle Scholar
  29. Sinha, S. R., Wu, L. G., and Saggau, P. (1997) Presynaptic calcium dynamics and transmitter release evoked by single action potentials at mammalian central synapses. Biophys. J. 72, 637–651.PubMedGoogle Scholar
  30. Stiles, J. R. and Bartol, T. M. (2000) Monte Carlo methods for simulating realistic synaptic microphysiology using Mcell. In: Computational Neuroscience: Realistic Modeling for Experimentalists. DeSchutter, E. (ed.) CRC Press, Boca Raton, FL, pp. 87–127.Google Scholar
  31. Tamori, Y. (1993) Theory of dendritic morphology. Phys. Rev. E. 48, 3124–3129.CrossRefGoogle Scholar
  32. Usui, S. (2003) VisioMe: neuroinformatics research in vision project. Neural Netw. 16, 1293–1300.PubMedCrossRefGoogle Scholar
  33. Volfovsky, N., Parnas, H., Segal, M., and Korkotian, E. (1999) Geometry of dendritic spines affects calcium dynamics in hippocampal neurons: theory and experiments. J. Neurophysiol. 81, 450–462.Google Scholar
  34. Yuste, R. and Bonhoeffer, T. (2004) Genesis of dendritic spines: insight from ultrastructural and imaging studies. Nat. Rev. Neurosci. 5, 24–34.PubMedCrossRefGoogle Scholar
  35. Zhou, Z. and Neher, E. (1993) Mobile and immobile calcium buffers in bovine adrenal chromaffin cells. J. Physiol. 469, 245–273.PubMedGoogle Scholar

Copyright information

© The Humana Press Inc 2005

Authors and Affiliations

  1. 1.Human Information Systems Laboratories, Kanazawa Institute of Technology, Advanced Research Institute for Science and EngineeringWaseda UniversityKanazawaJapan

Personalised recommendations