Dynamic-Clamp pp 217-235 | Cite as

Unraveling the Dynamics of Deep Cerebellar Nucleus Neurons with the Application of Artificial Conductances

  • Dieter Jaeger
  • Risa Lin
Part of the Springer Series in Computational Neuroscience book series (NEUROSCI, volume 1)


In this chapter we demonstrate how dynamic clamping can be used to apply different types of conductances to neurons in the deep cerebellar nuclei (DCN) to explore how spiking in these neurons is controlled by the interaction of synaptic and intrinsic conductances. Besides the application of synaptic- and voltage-gated conductances, we introduce the modeling of an intracellular calcium pool in the real-time loop of the dynamic clamp in order to apply calcium-dependent conductances to DCN neurons in brain slices. Further, we report on our ongoing computer simulation studies, in which we compare the effects of focal somatic or distributed dendritic conductances on the spiking behavior of a full morphological DCN neuron model in order to better understand the limitations of dynamic clamping given by applying artificial conductances only at a single location.


Purkinje Cell Synaptic Input Spike Rate Climbing Fiber Deep Cerebellar Nucleus 
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.



The work described in this chapter was not solely carried out by the authors. Volker Gauck obtained the dynamic-clamp recordings with inhibitory and NMDA conductances, Steven Feng programmed the HVA, Ca2+ pool, and sk conductance simulation into our LabVIEW dynamic clamp package and obtained the dynamic clamp data using these conductances. The work was supported by RO1 MH065634.


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of BiologyEmory UniversityAtlantaUSA

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