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Synaptic Conductances and Spike Generation in Cortical Cells

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Dynamic-Clamp

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

Abstract

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.

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Acknowledgments

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.

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Correspondence to Hugh P. C. Robinson .

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Robinson, H.P.C. (2009). Synaptic Conductances and Spike Generation in Cortical Cells. In: Bal, T., Destexhe, A. (eds) Dynamic-Clamp. Springer Series in Computational Neuroscience, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-0-387-89279-5_3

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