Skip to main content
Log in

Realistic simulations of neurons by means of an ad hoc modified version of SPICE

  • Published:
Biological Cybernetics Aims and scope Submit manuscript

Abstract

This paper describes an ad hoc modified version of the electrical circuit analysis program SPICE, which has been optimized for detailed simulations of the behaviour of neurons. An equivalent-circuit description of the simulation building blocks is provided, and the SPICE modifications are specified. These modifications, in contrast to previous uses of SPICE, allows one to simulate the behaviour of neurons of Hodgkin-Huxley type (excitable membrane) and of postsynaptic membranes without any approximations. Simulation results are reported and compared, both with data previously analysed in the literature by other authors and with experimental data recently obtained by coupling neurons to planar extracellular microelectrodes. Details of the circuit elements used in the simulations are reported. The improvements of our proposed model are discussed in comparison with a previous SPICE-based model described in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Baxter DA, Byrne JH (1993) Learning rules in neurobiology. In: Gardner D (eds) The neurobiology of neural networks. (Bradford Book) MIT Press, Cambridge, MA, pp 71–105

    Google Scholar 

  • Bunow B, Segev I, Fleshman JW (1985) Modeling the electrical behavior of anatomically complex neurons using a network analysis program: excitable membrane. Biol Cybern 53:41–56

    Article  PubMed  Google Scholar 

  • Cohen E (1976) Program reference for SPICE2. (Electronics Research Laboratory, Rep No ERL-M592) University of California, Berkeley

    Google Scholar 

  • Cooley JW, Dodge FA (1966) Digital computer solution for excitation and propagation of the nerve impulse. Biophys J 6:583–599

    PubMed  Google Scholar 

  • De Schutter E (1989) Computer software for development and simulation of compartmental models of neurons. Comp Biol Med 19:71–81

    Article  Google Scholar 

  • Goldstein SS, Rall W (1974) Changes in action potential shape and velocity for changing core conductor geometry. Biophys J 14:731–757

    PubMed  Google Scholar 

  • Grattarola M, Martinoia S (1993) Modeling the neuron-microtransducer junction from: extracellular to patch recording. IEEE Trans Biomed Eng 40:35–41

    Article  PubMed  Google Scholar 

  • Hines M (1989) A program for simulation of nerve equations with branching geometries. Int J Biomed Comput 24:55–68

    Article  PubMed  Google Scholar 

  • Hodgkin L, Huxley AF (1952) A quantitative description of membrane current and its applications to conduction and excitation in nerve. J Physiol 117:500–544

    PubMed  Google Scholar 

  • Koch C, Poggio T, Torre V (1983) Non linear interactions in a dendritic tree: localization, timing, and role in information processing. Proc Natl Acad Sci, USA 85:4075–4078

    Google Scholar 

  • Lüscher HR, Shiner JS (1990) Simulation of action potential propagation in complex terminal arborizations. Biophys J 58:1389–1399

    PubMed  Google Scholar 

  • Manor Y, Koch C, Segev I (1991) Effect of geometrical irregularities on propagation delay in axonal trees. Biophys J 60:1424–1437

    PubMed  Google Scholar 

  • Parnas I, Segev I (1979) A mathematical model for conduction of action potential along bifurcating axons. J Physiol (Lond) 295:323–343

    Google Scholar 

  • Rall W (1964) Theoretical analysis of dendritic tree for input-output relation. In: Reiss R (eds) Neural theory and modeling. Stanford University Press, Stanford, pp 73–97

    Google Scholar 

  • Rall W (1967) Distinguishable theoretical synaptic potentials computed for different soma-dendritic distributions of synaptic input. J Neurophysiol 30:1138–1168

    PubMed  Google Scholar 

  • Regher WG, Pine J, Rutledge DB (1988) A long-term in vitro siliconbased microelectrode neuron connection. IEEE Trans Biomed Eng 35:1023–1032

    Article  PubMed  Google Scholar 

  • Regher WG, Pine J, Cohan CS, Mischke MD, Tank DW (1989) Sealing cultured invertebrate neurons to embedded dish electrodes facilitates long-term stimulation and recording. J Neurosci Methods 30:91–106

    Article  PubMed  Google Scholar 

  • Robinson DA (1968) The electrical properties of metal microelectrodes. Proc IEEE 56:1065–1071

    Google Scholar 

  • Segev I, Fleshman JW, Miller JP, Bunow B (1985) Modeling the electrical behavior of anatomically complex neurons with a network analysis program: passive membrane. Biol Cybern 53:27–40

    Article  PubMed  Google Scholar 

  • Segev I, Fleshman JW, Burke RE (1989) Compartmental models of complex neurons. In: Koch C, Segev I (eds) Methods in neuronal modeling. From synapses to network. (Bradford Book) MIT Press, Cambridge, MA, pp 63–96

    Google Scholar 

  • Shepherd GM, Brayton RK (1979) Computer simulation of a dendrodendritic synaptic circuit for self- and lateral-inhibition in the olfactory bulb. Brain Res 175:377–382

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Additional information

Dedicated to the memory of Prof. Antonio Borsellino.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bove, M., Massobrio, G., Martinoia, S. et al. Realistic simulations of neurons by means of an ad hoc modified version of SPICE. Biol. Cybern. 71, 137–145 (1994). https://doi.org/10.1007/BF00197316

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00197316

Keywords