Skip to main content
Log in

Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation

  • Published:
Journal of Computational Neuroscience Aims and scope Submit manuscript

Abstract

The hippocampus is a brain structure critical for memory functioning. Its network dynamics include several patterns such as sharp waves that are generated in the CA3 region. To understand how population outputs are generated, models need to consider aspects of network size, cellular and synaptic characteristics and context, which are necessarily ‘balanced’ in appropriate ways to produce particular outputs. Thick slice hippocampal preparations spontaneously produce sharp waves that are initiated in CA3 regions and depend on the right balance of glutamatergic activities. As a step toward developing network models that can explain important balances in the generation of hippocampal output, we develop models of CA3 pyramidal cells. Our models are single compartment in nature, use an Izhikevich-type structure and involve parameter values that are specifically designed to encompass CA3 intrinsic properties. Importantly, they incorporate spike frequency adaptation characteristics that are directly comparable to those measured experimentally. Excitatory networks using these model cells are able to produce bursting suggesting that the amount of spike frequency adaptation expressed in the biological cells is an essential contributor to network bursting, and as such, may be important for sharp wave generation. The network bursting mechanism is numerically dissected showing the critical balance between adaptation and excitatory drive. The compact nature of our models allows large network simulations to be efficiently computed. This, together with the linkage of our models to cellular characteristics, will allow us to develop an understanding of population output of CA3 hippocampus with direct biological comparisons.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Andersen, P., Morris, R., Amaral, D., Bliss, T., & O’Keefe, J. (Eds.) (2006). The hippocampus book. Oxford: Oxford University Press.

    Google Scholar 

  • Bianchi, R., Chuang, S. C., & Wong, R. K. (2006). Pharmacology of a slowly inactivating outward current in hippocampal CA3 pyramidal neurons. Journal of Neurophysiology, 96(3), 1116–1123.

    Article  PubMed  CAS  Google Scholar 

  • Buzsaki, G. (1986). Hippocampal sharp waves: Their origin and significance. Brain Research, 398, 242–252.

    Article  PubMed  CAS  Google Scholar 

  • Buzsaki, G. (2011). Hippocampus. Scholarpedia, 6(1), 1468.

    Article  Google Scholar 

  • De Almeida, L., Idiart, M., & Lisman, J. E. (2007). Memory retrieval time and memory capacity of the CA3 network: Role of gamma frequency oscillations. Learning and Memory, 14, 795–806.

    Article  PubMed  Google Scholar 

  • Destexhe, A., Mainen, Z. F., & Sejnowski, T. J. (1998). Kinetic models of synaptic transmission. In C. Koch, & I. Segev (Eds.), Methods in neuronal modeling: From synapses to networks. Cambridge: MIT Press.

    Google Scholar 

  • Freund, T. F., & Buzsaki, G. (1996). Interneurons of the hippocampus. Hippocampus, 6(4), 347–470.

    Article  PubMed  CAS  Google Scholar 

  • Goutagny, R., Jackson, J., & Williams, S. (2009). Self-generated theta oscillations in the hippocampus. Nature Neuroscience, 12(12), 1491–1493.

    Article  PubMed  CAS  Google Scholar 

  • Gu, N., Vervaeke, K., & Storm, J. F. (2007). BK potassium channels facilitate high-frequency firing and cause early spike frequency adaptation in rat CA1 hippocampal pyramidal cells. Journal of Physiology, 580, 859–882.

    Article  PubMed  CAS  Google Scholar 

  • Hemond, P., Epstein, D., Boley, A., Migliore, M., Ascoli, G. A., & Jaffe, D. B. (2008). Distinct classes of pyramidal cells exhibit mutually exclusive firing patterns in hippocampal area CA3b. Hippocampus, 18, 411–424.

    Article  PubMed  Google Scholar 

  • Hemond, P., Migliore, M., Ascoli, G. A., & Jaffe, D. B. (2009). The membrane response of hippocampal CA3b pyramidal neurons near rest: Heterogeneity of passive properties and the contribution of hyperpolarization-activated currents. Neuroscience, 160(2), 359–370.

    Article  PubMed  CAS  Google Scholar 

  • Ho, E. C. Y. (2011). If you want to be slow you have to be fast: Control of slow population activities by fast-spiking interneurons via network multistability. PhD Thesis, University of Toronto.

  • Ho, E. C. Y., Zhang, L., & Skinner, F. K. (2009a). Inhibition dominates in shaping spontaneous CA3 hippocampal network activities in vitro. Hippocampus, 19(2), 152–165.

    Article  PubMed  Google Scholar 

  • Ho, E., Zhang, L., & Skinner, F. K. (2009b). Mathematical analyses and simulations predict conditions for the emergence of slow population rhythms. Program no. 321.16. In 2009 Neuroscience meeting planner. Chicago: Society for Neuroscience. Online.

    Google Scholar 

  • Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on Neural Networks, 14, 1569–1572.

    Article  PubMed  CAS  Google Scholar 

  • Izhikevich, E. M. (2007). Dynamical systems in neuroscience. Cambridge: MIT Press.

    Google Scholar 

  • Latham, P. E., Richmond, B. J., Nelson, P. G., & Nirenberg, S. (2000). Intrinsic dynamics in neuronal networks. I. Theory. Journal of Neurophysiology, 83(2), 808–827.

    PubMed  CAS  Google Scholar 

  • Li, X. G., Somogyi, P., Ylinen, A., & Buzsaki, G. (1994). The hippocampal CA3 network: An in vivo intracellular labeling study. Journal of Comparative Neurology, 339(2), 181–208.

    Article  PubMed  CAS  Google Scholar 

  • Lisman, J. E. (1997). Bursts as a unit of neural information: making unreliable synapses reliable. Trends in Neurosciences, 20(1), 38–43.

    Article  PubMed  CAS  Google Scholar 

  • Marder, E., & Selverston, A. I. (1992). Modeling the stomatogastric nervous system. In R. M. Harris-Warrick, E. Marder, A. I. Selverston, & M. Moulins (Eds.), Dynamic biological networks: The stomatogastric system. Cambridge: MIT Press.

    Google Scholar 

  • McBain, C. J., & Fisahn, A. (2001). Interneurons unbound. Nature Reviews. Neuroscience, 2(1), 11–23.

    Article  PubMed  CAS  Google Scholar 

  • Migliore, M., Ascoli, G. A., & David, B. J. (2010). CA3 cells: Detailed and simplified pyramidal cell models. In V. Cutsuridis, B. Graham, S. Cobb, & I. Vida (Eds.), Hippocampal microcircuits: A computational modeler’s resource book. Springer series in computational neuroscience (Vol. 5).

  • Migliore, M., Cook, E. P., Jaffe, D. B., Turner, D. A., & Johnston, D. (1995). Computer simulations of morphologically reconstructed CA3 hippocampal neurons. Journal of Neurophysiology, 73, 1157–1168.

    PubMed  CAS  Google Scholar 

  • Mitterdorfer, J., & Bean, B. P. (2002). Potassium currents during the action potential of hippocampal CA3 neurons. Journal of Neuroscience, 22(23), 10106–10115.

    PubMed  CAS  Google Scholar 

  • Nesse, W. H., Borisyuk, A., & Bressloff, P. C. (2008). Fluctuation-driven rhythmogenesis in an excitatory neuronal network with slow adaptation. Journal of Computational Neuroscience, 25(2), 317–333.

    Article  PubMed  Google Scholar 

  • Pinsky, P. F., & Rinzel, J. (1994). Intrinsic and network rhythmogenesis in a reduced Traub model for CA3 neurons. Journal of Computational Neuroscience, 1, 39–60.

    Article  PubMed  CAS  Google Scholar 

  • Rudolph, M., Piwkowska, Z., Badoual, M., Bal, T., & Destexhe, A. (2004). A method to estimate synaptic conductances from membrane potential fluctuations. Journal of Neurophysiology, 91(6), 2884–2896.

    Article  PubMed  Google Scholar 

  • Skinner, F. K., Bazzazi, H., & Campbell, S. A. (2005). Two-cell to N-cell heterogeneous, inhibitory networks: Precise linking of multistable and coherent properties. Journal of Computational Neuroscience, 18(3), 343–352.

    Article  PubMed  CAS  Google Scholar 

  • Tabak, J., Mascagni, M., & Bertram, R. (2010). Mechanism for the universal pattern of activity in developing neuronal networks. Journal of Neurophysiology, 103(4), 2208–2221.

    Article  PubMed  Google Scholar 

  • Touboul, J. (2008). Bifurcation analysis of a general class of non-linear integrate and fire neurons. SIAM Journal of Applied Mathematics, 68, 1045–1079.

    Article  Google Scholar 

  • Traub, R. D., & Miles, R. (1991). Neuronal networks of the hippocampus. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Traub, R. D., Miles, R., & Wong, R. K. (1989). Model of the origin of rhythmic population oscillations in the hippocampal slice. Science, 243(4896), 1319–1325.

    Article  PubMed  CAS  Google Scholar 

  • Traub, R. D., Miles, R., & Buzsaki, G. (1992). Computer simulation of carbachol-driven rhythmic population oscillations in the CA3 region of the in vitro rat hippocampus. Journal of Physiology, 451, 653–672.

    PubMed  CAS  Google Scholar 

  • Traub, R. D., Wong, R. K., Miles, R., & Michelson, H. (1991). A model of a CA3 hippocampal pyramidal neuron incorporating voltage-clamp data on intrinsic conductances. Journal of Neurophysiology, 66, 635–650.

    PubMed  CAS  Google Scholar 

  • Treves, A., & Rolls, E. T. (1992). Computational constraints suggest the need for two distinct input systems to the hippocampal CA3 network. Hippocampus, 2, 189–199.

    Article  PubMed  CAS  Google Scholar 

  • van Vreeswijk, C. V., & Hansel, D. (2001). Patterns of synchrony in neural networks with spike adaptation. Neural Computation, 13, 959–992.

    Article  PubMed  Google Scholar 

  • Vladimirski, B. B., Tabak, J., O’Donovan, M., & Rinzel, J. (2008). Episodic activity in a heterogeneous excitatory network, from spiking neurons to mean field. Journal of Computational Neuroscience, 25(1), 39–63.

    Article  PubMed  Google Scholar 

  • Wu, C., Asl, M. N., Gillis, J., Skinner, F., & Zhang, L. (2005a). An in vitro model of hippocampal sharp waves: Regional initiation and intracellular correlates. Journal of Neurophysiology, 94(1), 741–753.

    Article  PubMed  Google Scholar 

  • Wu, C., Luk, W. P., Gillis, J., Skinner, F. K., & Zhang, L. (2005b). Size does matter: Generation of intrinsic network rhythms in thick mouse hippocampal slices. Journal of Neurophysiology, 93(4), 2302–2317.

    Article  PubMed  Google Scholar 

  • Wu, C. P., Luk, W. P., Wong, T., Wu, X., Sheppy, E., & Zhang, L. (2009). Adenosine as an endogenous regulating factor of hippocampal sharp waves. Hippocampus, 19, 205–220.

    Article  PubMed  CAS  Google Scholar 

  • Xu, J., & Clancy, C. E. (2008). Ionic mechanisms of endogenous bursting in CA3 hippocampal pyramidal neurons: A model study. PLoS ONE, 3(4), e2056. doi:10.1371/journal.pone.0002056.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank NSERC and the Center for Mathematical Medicine (CMM) at the Fields Institute in Toronto for their support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Frances K. Skinner.

Additional information

Action Editor: David Terman

S.A. Campbell and F.K. Skinner contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dur-e-Ahmad, M., Nicola, W., Campbell, S.A. et al. Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation. J Comput Neurosci 33, 21–40 (2012). https://doi.org/10.1007/s10827-011-0372-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10827-011-0372-6

Keywords

Navigation