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BMC Neuroscience

, 14:P80 | Cite as

The intrinsic and synaptic responsiveness of a new realistic Purkinje cell model

  • Stefano Masoli
  • Sergio Solinas
  • Egidio D'Angelo
Open Access
Poster presentation
  • 1.1k Downloads

Keywords

Purkinje Cell Axon Initial Segment Complex Spike Bistable Behavior Intrinsic Excitability 
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 latest discoveries on Purkinje cell (PC) physiology suggest that the mechanisms of PCs intrinsic excitability have to be revisited. Starting from available models [1], we have constructed a new PC model in Python-NEURON, which explicitly accounts for the Axon Initial Segment (AIS) [2, 3, 4] and a part of the axon including the first node of Ranvier (RVN). The fast Na+ channels are located in AIS, soma with initial dendrite and RVN [4]. The K+ delayed rectifier channels are located only in the soma. The Ca2+ and Ca2+-dependent K+ channels, including SK2, as well as intracellular Ca2+ dynamics have been updated [5]. The new model configuration now generates simple spike (SS) firing reproducing the experimental input-output curve[6]. SSs initiate in AIS and then back-propagate into the soma decaying sharply inside the dendritic tree. Activation of parallel fiber (pf) generates a short burst followed by a pause caused by Stellate cells. Following a complex spike (CS), SS activity is interrupted independently of the inhibitory synaptic input. Interestingly, the model can shift its state from silent to autorhythmic (configuring a bistable behavior) upon transient current injection or activation of CFs. The pf and granule cell ascending axon (aa) synapses have been modeled using a stochastic release mechanism activating AMPA synaptic receptors. The facilitation and depression profiles of pf and aa synapses faithfully reproduce the experimental data. This model provides a valuable tool to further investigate the Purkinje cell function in cerebellar network models.

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Copyright information

© Masoli et al; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Stefano Masoli
    • 1
  • Sergio Solinas
    • 2
  • Egidio D'Angelo
    • 1
    • 2
  1. 1.Department of Brain and Behavioural Science, Neurophysiology and Neurocomputation UnitUniversity of PaviaPaviaItaly
  2. 2.Brain Connectivity CenterIstituto Neurologico IRCCS C. MondinoPaviaItaly

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