Synaptic Conductances and Spike Generation in Cortical Cells

  • Hugh P. C. Robinson
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 1)


Investigating how cortical neurons integrate their electrical inputs has commonly involved injecting fixed patterns of current and observing the resulting membrane potential and spike responses. However, we now have accurate biophysical models of the ionic conductances at the postsynaptic sites of cortical synapses and of the conductances which generate action potentials (APs). Using conductance injection or dynamic clamp, it is possible to inject point conductances which closely capture the electrical properties of synaptic inputs, including the shunting, reversible nature of inhibitory gamma-amino butyric acid (GABA)A receptor input, the saturating or “choking” behaviour of α-amino-3-hydroxy-5-methyl-4-isoazoleprionic acid (AMPA) receptor input and the voltage-dependent block of N-methyl-D-aspartate (NMDA) receptor input. Complex conductance signals which reproduce the effects of stochastic and oscillatory network activity can be applied repeatedly and precisely to neurons. In this chapter, I review our work using this approach, addressing the nature of the threshold and of the reliability of spike generation in cortical neurons, how synaptic conductance input patterns are encoded into variations in AP shape and how neurons integrate network burst and gamma oscillatory activity.


Spike Generation Synaptic Conductance Synaptic Integration Spike Shape Inhibitory Conductance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I am deeply grateful to all my collaborators in this work: Kazuyuki Aihara, Gonzalo de Polavieja, Nathan Gouwens, Annette Harsch, Mikko Juusola, Rita Kalra, Nobufumi Kawai, Ingo Kleppe, Kenji Morita, Takashi Tateno, Kunichika Tsumoto, Mariana Vargas-Caballero and Hugo Zeberg. Supported by grants from the EC, BBSRC and the Daiwa Foundation.


  1. Alle, H. and J. R. Geiger (2006). “Combined analog and action potential coding in hippocampal mossy fibers.” Science 311(5765): 1290–3.PubMedCrossRefGoogle Scholar
  2. Beierlein, M., J. R. Gibson, et al. (2003). “Two dynamically distinct inhibitory networks in layer 4 of the neocortex.” J Neurophysiol 90: 2987–3000.PubMedCrossRefGoogle Scholar
  3. Chance, F., L. Abbott, and A. Reyes (2002). “Gain modulation from background synaptic input.” Neuron 35: 773–82.PubMedCrossRefGoogle Scholar
  4. Clarke, R. J. and J. W. Johnson (2006). “NMDA receptor NR2 subunit dependence of the slow component of magnesium unblock.” J Neurosci 26(21): 5825–34.PubMedCrossRefGoogle Scholar
  5. Connors, B. W., M. J. Gutnick, et al. (1982). “Electrophysiological properties of neocortical neurons in vitro.” J Neurophysiol 48(6): 1302–20.PubMedGoogle Scholar
  6. Coombs, J. S., J. C. Eccles, et al. (1955). “Excitatory synaptic action in motoneurones.” J Physiol 130: 374–95.PubMedGoogle Scholar
  7. de Polavieja, G. G., A. Harsch, et al. (2005). “Stimulus history reliably shapes action potential waveforms of cortical neurons.” J Neurosci 25(23): 5657–65.PubMedCrossRefGoogle Scholar
  8. Destexhe, A., M. Rudolph, et al. (2001). “Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons.” Neuroscience 107(1): 13–24.PubMedCrossRefGoogle Scholar
  9. Eccles, J. (1963). “The ionic mechanism of postsynaptic inhibition.” Nobel Prize Lecture.Google Scholar
  10. Erisir, A., D. Lau, et al. (1999). “Function of specific K(+) channels in sustained high-frequency firing of fast-spiking neocortical interneurons.” J Neurophysiol 82(5): 2476–89.PubMedGoogle Scholar
  11. Forsythe, I. D. and G. L. Westbrook (1988). “Slow excitatory postsynaptic currents mediated by N-methyl-D-aspartate receptors on cultured mouse central neurones.” J Physiol 396: 515–33.PubMedGoogle Scholar
  12. Harsch, A. and H. P. C. Robinson (2000). “Postsynaptic variability of firing in rat cortical neurons: the roles of input synchronization and synaptic NMDA receptor conductance.” J Neurosci 20(16): 6181–92.PubMedGoogle Scholar
  13. Hasenstaub, A., Y. Shu, et al. (2005). “Inhibitory postsynaptic potentials carry synchronized frequency information in active cortical networks.” Neuron 47(3): 423–35.PubMedCrossRefGoogle Scholar
  14. Hausser, M., G. Major, et al. (2001). “Differential shunting of EPSPs by action potentials.” Science 291(5501): 138–41.PubMedCrossRefGoogle Scholar
  15. Hodgkin, A. L. (1948). The local electric changes associated with repetitive action in a non-medullated axon. J Physiol 107: 165–81.PubMedGoogle Scholar
  16. Hodgkin, A. L. and A. F. Huxley (1952). “A quantitative descrption of membrane current and its application to conduction and excitation in nerve.” J Physiol 117: 500–44.PubMedGoogle Scholar
  17. Itazawa, S.-I., T. Isa, et al. (1997). “Inwardly rectifying and Ca2+-permeable AMPA-type glutamate receptor channels in rat neocortical neurons.” J Neurophysiol 78: 2592–601.PubMedGoogle Scholar
  18. Izhikevich, E. M. (2007). Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting, MIT Press, Cambridge.Google Scholar
  19. Juusola, M., H. P. Robinson, et al. (2007). “Coding with spike shapes and graded potentials in cortical networks.” Bioessays 29(2): 178–87.PubMedCrossRefGoogle Scholar
  20. Kampa, B. M., J. Clements, et al. (2004). “Kinetics of Mg2+ unblock of NMDA receptors: implications for spike-timing dependent synaptic plasticity.” J Physiol 556: 337–45.PubMedCrossRefGoogle Scholar
  21. Koch, C., T. Poggio, et al. (1983). “Nonlinear interactions in a dendritic tree: localization, timing and role in information processing.” Proc Natl Acad Sci USA 80: 2799–2802.Google Scholar
  22. Mayer, M. L., G. L. Westbrook, et al. (1984). “Voltage-dependent block by Mg2+ of NMDA responses in spinal cord neurones. “ Nature 309: 261–3.PubMedCrossRefGoogle Scholar
  23. Mitchell, S. J. and R. A. Silver (2003). “Shunting inhibition modulates neuronal gain during synaptic excitation.” Neuron 38: 433–45.PubMedCrossRefGoogle Scholar
  24. Morita, K., R. Kalra, et al. (2008). “Recurrent synaptic input and the timing of gamma-frequency-modulated firing of pyramidal cells during neocortical “UP” states.” J Neurosci 28: 1871–81.PubMedCrossRefGoogle Scholar
  25. Nevian, T., M. E. Larkum, et al. (2007). “Properties of basal dendrites of layer 5 pyramidal neurons: a direct patch-clamp recording study.” Nature Neurosci 10: 206–14.PubMedCrossRefGoogle Scholar
  26. Nowak, L., P. Bregestovski, et al. (1984). “Magnesium gates glutamate-activated channels in mouse central neurones.” Nature 307: 462–5.PubMedCrossRefGoogle Scholar
  27. Qian, N. and T. J. Sejnowski (1990). “When is an inhibitory synapse effective?” Proc Natl Acad Sci USA 87: 8145–9.PubMedCrossRefGoogle Scholar
  28. Rall, W. (1962). “Electrophysiology of a dendrite neuron model.” Biophys J 2: 145–67.PubMedCrossRefGoogle Scholar
  29. Robinson, H. P. C. (1991). “Kinetics of synaptic conductances in mammalian central neurons.” Neurosci Res 16: VI.Google Scholar
  30. Robinson, H. P. C. (2008). “A scriptable DSP-based system for dynamic conductance injection.” J Neurosci Methods 169: 271–81.PubMedCrossRefGoogle Scholar
  31. Robinson, H. P. and A. Harsch (2002). “Stages of spike time variability during neuronal responses to transient inputs.” Phys Rev E Stat Nonlin Soft Matter Phys 66(6 Pt 1): 061902.PubMedCrossRefGoogle Scholar
  32. Robinson, H. P. C. and N. Kawai (1993). “Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons.” J Neurosci Methods 49(3): 157–65.PubMedCrossRefGoogle Scholar
  33. Robinson, H. P. C., K. Tsumoto, et al. (2004). Modelling phase-locking in electrically-coupled networks of inhibitory cortical interneurons. Proceedings of Nonlinear Theory and its Applications, Fukuoka, Japan.Google Scholar
  34. Sakmann, B. and E. Neher (1995). Single Channel Recording. New York and London, Plenum.Google Scholar
  35. Sharp, A. A., M. B. O’Neil, et al. (1993). “Dynamic clamp: computer-generated conductances in real neurons.” J Neurophysiol 69(3): 992–5.PubMedGoogle Scholar
  36. Shu, Y., A. Hasenstaub, et al. (2006). “Modulation of intracortical synaptic potentials by presynaptic somatic membrane potential.” Nature 441(7094): 761–5.PubMedCrossRefGoogle Scholar
  37. Singer, W. and C. M. Gray (1995). “Visual feature integration and the temporal hypothesis.” Annual Rev Neurosci 18: 555–86.CrossRefGoogle Scholar
  38. Spruston, N. (2008). “Pyramidal neurons: dendritic structure and synaptic integration.” Nat Rev Neurosci 9(3): 206–21.PubMedCrossRefGoogle Scholar
  39. Steriade, M., A. Nunez, et al. (1993). “A novel slow (< 1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components.” J Neurosci 13(8): 3252–65.PubMedGoogle Scholar
  40. Stuart, G. J. and B. Sakmann (1994). “Active propagation of somatic action potentials into neocortical pyramidal cell dendrites.” Nature 367(6458): 69–72.PubMedCrossRefGoogle Scholar
  41. Tateno, T., A. Harsch, et al. (2004). “Threshold firing frequency-current relationships of neurons in rat somatosensory cortex: type 1 and type 2 dynamics.” J Neurophysiol 92(4): 2283–94.PubMedCrossRefGoogle Scholar
  42. Tateno, T. and H. P. Robinson (2006). “Rate coding and spike-time variability in cortical neurons with two types of threshold dynamics.” J Neurophysiol 95(4): 2650–63.PubMedCrossRefGoogle Scholar
  43. Vargas-Caballero, M. and H. P. Robinson (2003). “A slow fraction of Mg2+ unblock of NMDA receptors limits their contribution to spike generation in cortical pyramidal neurons.” J Neurophysiol 89(5): 2778–83.PubMedCrossRefGoogle Scholar
  44. Vargas-Caballero, M. and H. P. Robinson (2004). “Fast and slow voltage-dependent dynamics of magnesium block in the NMDA receptor: the asymmetric trapping block model.” J Neurosci 24(27): 6171–80.PubMedCrossRefGoogle Scholar
  45. Williams, S. R. (2004). “Spatial compartmentalization and functional impact of conductance in pyramidal neurons.” Nature Neurosci 7: 961–7.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Physiology, Development and NeuroscienceUniversity of CambridgeCambridgeUK

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