A computational approach to the study of AMPA receptor clustering at Purkinje cell synapses.

Abstract

Synapses between parallel fibres and Purkinje cells in the cerebellum exhibit unique forms of synaptic plasticity thought to be associated with the refinement of motor skills. Since the discovery of Long Term Depression (LTD), more than twenty years ago, many molecular signalling pathways potentially underlying LTD have been explored. These have revealed a surprisingly diverse array of cellular and molecular mechanisms. Foremost has been the now well-established discovery that LTD is the electrophysiological manifestation of a reduced density of AMPA receptors at the synapse, following induction. Although LTD is primarily an electrophysiologically defined phenomenon, recent studies have increasingly combined electrophysiological, imaging, proteomic and biochemical approaches to probe its mechanisms. The challenge is now to integrate data from different modalities into a unified formalism that can deal with the complexity of the system, as well as generate experimental predictions. Here, we use particle-based stochastic modelling as a prototype to explore the feasibility of building realistic model of synaptic plasticity, at the molecular level.