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.
Model Type: Synapse
Cell Type(s): Cerebellum Purkinje GABA cell
Model Concept(s): Synaptic Plasticity
Simulation Environment: STEPS
Antunes G, De Schutter E. (2012). A stochastic signaling network mediates the probabilistic induction of cerebellar long-term depression. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]