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Cerebellar long-term depression (LTD) (Antunes and De Schutter 2012)
 
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Model Information
Model File
Accession:
141270
Many cellular processes involve small number of molecules and undergo stochastic fluctuations in their levels of activity. Among these processes is cerebellar long-term depression (LTD), a form of synaptic plasticity expressed as a reduction in the number of synaptic AMPA receptors (AMPARs) in Purkinje cells. Using a stochastic model of the signaling network and mechanisms of AMPAR trafficking involved in LTD, we show that the network activity in single synapses switches between two discrete stable states (LTD and non-LTD). Stochastic fluctuations affecting more intensely the level of activity of a few components of the network lead to the probabilistic induction of LTD and threshold dithering. The non-uniformly distributed stochasticity of the network allows the stable occurrence of several different macroscopic levels of depression, determining the experimentally observed sigmoidal relationship between the magnitude of depression and the concentration of the triggering signal.
Reference:
1 .
Antunes G, De Schutter E (2012) A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression.
J Neurosci
32
:9288-300
[
PubMed
]
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Model Information
(Click on a link to find other models with that property)
Model Type:
Synapse;
Brain Region(s)/Organism:
Cell Type(s):
Cerebellum Purkinje GABA cell;
Channel(s):
Gap Junctions:
Receptor(s):
AMPA;
Gene(s):
Transmitter(s):
Simulation Environment:
STEPS;
Model Concept(s):
Synaptic Plasticity;
Implementer(s):
De Schutter, Erik [erik at oist.jp];
Antunes, Gabriela [gabri_antunes at hotmail.com];
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for information about:
Cerebellum Purkinje GABA cell
;
AMPA
;
/
LTDmodel
README.txt
Info_on_the_model.pdf
ltd.py
ltd_updated.py
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