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Re-Creating In Vivo-Like Activity and Investigating the Signal Transfer Capabilities of Neurons: Dynamic-Clamp Applications Using Real-Time Neuron

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Dynamic-Clamp

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

Abstract

Understanding the input–output transfer properties of NEURONs is a complex problem which requires detailed knowledge of the intrinsic properties of neurons, and how these intrinsic properties influence signal integration. More recently, it became clear that the transfer function of neurons also highly depends on the activity of the surrounding network, and in particular on the presence of synaptic background activity. We review here different in vitro techniques to investigate such problems in cortex, thalamus, and spinal cord, along three examples: First, by constructing “hybrid” networks with real and artificial thalamic neurons using dynamic clamp, it was possible to study how the state of the circuit influences spike transfer through the thalamus. Second, the dynamic clamp was used to study how the state of discharge of spinal neurons influences their information processing capabilities. Third, the dynamic-clamp experiments could re-create “in vivo-like” background synaptic activity by injection of stochastic excitatory and inhibitory conductances, and we showed that this activity profoundly modifies the input–output transfer function of thalamic and cortical neurons. We also illustrate how such applications are greatly facilitated by the use of a neuronal simulator to run the dynamic-clamp experiments, as shown here for RT-NEURON.

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Acknowledgments

This work was supported by Centre National de la Recherche Scientifique, European Commission (IST-2001-34712), Action Concertée Incitative “Neurosciences intégratives et computationnelles” and ANR grants T-State and HR-cortex. We thank Michelle Rudolph, Paul Galloux, Leonel Gomez, and José Gomez for help with computation, Jakob Wolfart, Damien Debay, and Mathilde Badoual for testing RT-NEURON experimentally, and Charlotte Deleuze for comments on the manuscript.

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  1. CNRS, Gif sur Yvette, France

    Gerard Sadoc

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  1. Gerard Sadoc
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  2. Gwendal Le Masson
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  3. Bruno Foutry
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  4. Yann Le Franc
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  5. Zuzanna Piwkowska
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  6. Alain Destexhe
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  7. Thierry Bal
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Correspondence to Gerard Sadoc .

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    Sadoc, G. et al. (2009). Re-Creating In Vivo-Like Activity and Investigating the Signal Transfer Capabilities of Neurons: Dynamic-Clamp Applications Using Real-Time Neuron. 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_14

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