Impact of Background Synaptic Activity on Neuronal Response Properties Revealed by Stepwise Replication of In Vivo-Like Conditions In Vitro

Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 1)


Neurons in the intact brain are bombarded by spontaneous synaptic input that causes increased membrane conductance (i.e. shunting), tonic depolarization, and noisy fluctuations in membrane potential. By comparison, neurons in acute brain slices experience little spontaneous synaptic input and are therefore less leaky, more hyperpolarized, and less noisy. Such differences can compromise the extrapolation of in vitro data to explain neuronal operation in vivo. Here, we replicated three effects of synaptic background activity in acute brain slices, using dynamic clamp to artificially increase membrane conductance, constant current injection to cause tonic depolarization, and time-varying current injection to introduce noise. These manipulations were applied separately and in different combinations in order to resolve their specific influence on neuronal activity. In addition to straightforward effects on passive membrane properties, shunting caused nonlinear effects on spiking. As a result, shunted neurons behaved more like coincidence detectors and less like integrators. Furthermore, shunting caused either divisive or subtractive modulation of firing rate depending on the presence or absence of background noise. These results demonstrate that even simplistic applications of dynamic clamp can reveal interesting phenomena and expand our ability to use in vitro experiments to help understand neuronal operation in vivo.


Firing Rate Voltage Fluctuation Divisive Modulation Dynamic Clamp Acute Brain Slice 
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.


  1. Azouz R, Gray CM (2000) Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. Proc Natl Acad Sci USA 97: 8110–8115.PubMedCrossRefGoogle Scholar
  2. Berman NJ, Douglas RJ, Martin KA (1992) GABA-mediated inhibition in the neural networks of visual cortex. Prog Brain Res 90: 443–476.PubMedCrossRefGoogle Scholar
  3. Bernander Ö, Douglas RJ, Martin KA, Koch C (1991) Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proc Natl Acad Sci USA 88: 11569–11573.PubMedCrossRefGoogle Scholar
  4. Blomfield S (1974) Arithmetical operations performed by nerve cells. Brain Res 69: 115–124.PubMedCrossRefGoogle Scholar
  5. Bruckner S, Hyson RL (1998) Effect of GABA on the processing of interaural time differences in nucleus laminaris neurons in the chick. Eur J Neurosci 10: 3438–3450.PubMedCrossRefGoogle Scholar
  6. Buhl EH, Halasy K, Somogyi P (1994) Diverse sources of hippocampal unitary inhibitory postsynaptic potentials and the number of synaptic release sites. Nature 368: 823–828.PubMedCrossRefGoogle Scholar
  7. Carandini M, Heeger DJ (1994) Summation and division by neurons in primate visual cortex. Science 264: 1333–1336.PubMedCrossRefGoogle Scholar
  8. Chance FS, Abbott LF, Reyes AD (2002) Gain modulation from background synaptic input. Neuron 35: 773–782.PubMedCrossRefGoogle Scholar
  9. Connors BW, Malenka RC, Silva LR (1988) Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and cat. J Physiol 406: 443–468.PubMedGoogle Scholar
  10. Destexhe A, Paré D (1999) Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J Neurophysiol 81: 1531–1547.PubMedGoogle Scholar
  11. Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ (2001) Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107: 13–24.PubMedCrossRefGoogle Scholar
  12. Destexhe A, Rudolph M, Pare D (2003) The high-conductance state of neocortical neurons in vivo. Nat Rev Neurosci 4: 739–751.PubMedCrossRefGoogle Scholar
  13. Eccles JC (1964) The Physiology of Synapses. Berlin: Springer-Verlag.CrossRefGoogle Scholar
  14. Ermentrout B (2002) Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students. Philadelphia, PA: SIAM.CrossRefGoogle Scholar
  15. Fellous JM, Rudolph M, Destexhe A, Sejnowski TJ (2003) Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity. Neuroscience 122: 811–829.PubMedCrossRefGoogle Scholar
  16. Fernandez FR, White JA (2008) Artificial synaptic conductances reduce subthreshold oscillations and periodic firing in stellate cells of the entorhinal cortex. J Neurosci 28: 3790–3803.PubMedCrossRefGoogle Scholar
  17. Higgs MH, Slee SJ, Spain WJ (2006) Diversity of gain modulation by noise in neocortical neurons: regulation by the slow afterhyperpolarization conductance. J Neurosci 26: 8787–8799.PubMedCrossRefGoogle Scholar
  18. Hodgkin AL (1948) The local electric changes associated with repetitive action in a non-medullated axon. J Physiol 165–181.Google Scholar
  19. Holmes WR, Woody CD (1989) Effects of uniform and non-uniform synaptic 'activation-distributions' on the cable properties of modeled cortical pyramidal neurons. Brain Res 505: 12–22.PubMedCrossRefGoogle Scholar
  20. Holt GR, Koch C (1997) Shunting inhibition does not have a divisive effect on firing rates. Neural Comput 9: 1001–1013.PubMedCrossRefGoogle Scholar
  21. Hu H, Vervaeke K, Storm JF (2007) M-channels (Kv7/KCNQ channels) that regulate synaptic integration, excitability, and spike pattern of CA1 pyramidal cells are located in the perisomatic region. J Neurosci 27: 1853–1867.PubMedCrossRefGoogle Scholar
  22. Jean-Xavier C, Mentis GZ, O’Donovan MJ, Cattaert D, Vinay L (2007) Dual personality of GABA/glycine-mediated depolarizations in immature spinal cord. Proc Natl Acad Sci USA 104: 11477–11482.PubMedCrossRefGoogle Scholar
  23. König P, Engel AK, Singer W (1996) Integrator or coincidence detector? The role of the cortical neuron revisited. Trends Neurosci 19: 130–137.PubMedCrossRefGoogle Scholar
  24. Kuhn A, Aertsen A, Rotter S (2004) Neuronal integration of synaptic input in the fluctuation-driven regime. J Neurosci 24: 2345–2356.PubMedCrossRefGoogle Scholar
  25. Longtin A, Doiron B, Bulsara AR (2002) Noise-induced divisive gain control in neuron models. Biosystems 67: 147–156.PubMedCrossRefGoogle Scholar
  26. Mainen ZF, Joerges J, Huguenard JR, Sejnowski TJ (1995) A model of spike initiation in neocortical pyramidal neurons. Neuron 15: 1427–1439.PubMedCrossRefGoogle Scholar
  27. Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268: 1503–1506.PubMedCrossRefGoogle Scholar
  28. Mitchell SJ, Silver RA (2003) Shunting inhibition modulates neuronal gain during synaptic excitation. Neuron 38: 433–445.PubMedCrossRefGoogle Scholar
  29. Morris C, Lecar H (1981) Voltage oscillations in the barnacle giant muscle fiber. Biophys J 35: 193–213.PubMedCrossRefGoogle Scholar
  30. Paré D, Shink E, Gaudreau H, Destexhe A, Lang EJ (1998) Impact of spontaneous synaptic activity on the resting properties of cat neocortical pyramidal neurons in vivo. J Neurophysiol 79: 1450–1460.PubMedGoogle Scholar
  31. Pinto RD, Elson RC, Szucs A, Rabinovich MI, Selverston AI, Abarbanel HD (2001) Extended dynamic clamp: controlling up to four neurons using a single desktop computer and interface. J Neurosci Methods 108: 39–48.PubMedCrossRefGoogle Scholar
  32. Prescott SA, De Koninck Y (2003) Gain control of firing rate by shunting inhibition: roles of synaptic noise and dendritic saturation. Proc Natl Acad Sci USA 100: 2076–2081.PubMedCrossRefGoogle Scholar
  33. Prescott SA, De Koninck Y, Sejnowski TJ (2008a) Biophysical basis for three distinct dynamical mechanisms of action potential initiation. PLoS Comput Biol 4: e1000198.Google Scholar
  34. Prescott SA, Ratté S, De Koninck Y, Sejnowski TJ (2006a) Nonlinear interaction between shunting and adaptation controls a switch between integration and coincidence detection in pyramidal neurons. J Neurosci 26: 9084–9097.Google Scholar
  35. Prescott SA, Ratté S, De Koninck Y, Sejnowski TJ (2008b) Pyramidal neurons switch from integrators in vitro to resonators under in vivo-like conditions. J Neurophysiol 100: 3030–3042.Google Scholar
  36. Prescott SA, Sejnowski TJ, De Koninck Y (2006b) Reduction of anion reversal potential subverts the inhibitory control of firing rate in spinal lamina I neurons: towards a biophysical basis for neuropathic pain. Mol Pain 2(32).Google Scholar
  37. Rinzel J, Ermentrout GB (1998) Analysis of neural excitability and oscillations. In: Methods in Neuronal Modeling: From Ions to Networks (Koch C, Segev I, eds), pp 251–291. Cambridge, MA: The MIT Press.Google Scholar
  38. Robinson HP, Kawai N (1993) Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons. J Neurosci Methods 49: 157–165.PubMedCrossRefGoogle Scholar
  39. Rose D (1977) On the arithmetical operation performed by inhibitory synapses onto the neuronal soma. Exp Brain Res 28: 221–223.PubMedCrossRefGoogle Scholar
  40. Rudolph M, Destexhe A (2003) Tuning neocortical pyramidal neurons between integrators and coincidence detectors. J Comput Neurosci 14: 239–251.PubMedCrossRefGoogle Scholar
  41. Salinas E, Thier P (2000) Gain modulation: a major computational principle of the central nervous system. Neuron 27: 15–21.PubMedCrossRefGoogle Scholar
  42. Sharp AA, O'Neil MB, Abbott LF, Marder E (1993a) Dynamic clamp: computer-generated conductances in real neurons. J Neurophysiol 69: 992–995.Google Scholar
  43. Sharp AA, O'Neil MB, Abbott LF, Marder E (1993b) The dynamic clamp: artificial conductances in biological neurons. Trends Neurosci 16: 389–394.Google Scholar
  44. Shu Y, Duque A, Yu Y, Haider B, McCormick DA (2007) Properties of action-potential initiation in neocortical pyramidal cells: evidence from whole cell axon recordings. J Neurophysiol 97: 746–760.PubMedCrossRefGoogle Scholar
  45. Shu Y, Hasenstaub A, Badoual M, Bal T, McCormick DA (2003) Barrages of synaptic activity control the gain and sensitivity of cortical neurons. J Neurosci 23: 10388–10401.PubMedGoogle Scholar
  46. Strogatz SH (1998) Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Don Mills, ON: Addison-Wesley.Google Scholar
  47. Stuart G, Spruston N, Sakmann B, Hausser M (1997) Action potential initiation and backpropagation in neurons of the mammalian CNS. Trends Neurosci 20: 125–131.PubMedCrossRefGoogle Scholar
  48. Uhlenbeck GE, Ornstein LS (1930) On the theory of Brownian motion. Phys Rev 36: 823–841.CrossRefGoogle Scholar
  49. Wang HS, McKinnon D (1995) Potassium currents in rat prevertebral and paravertebral sympathetic neurones: control of firing properties. J Physiol 485: 319–335.PubMedGoogle Scholar

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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of NeurobiologyUniversity of Pittsburgh, Biomedical Science TowerPittsburghUSA

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