Integrated plasticity at inhibitory and excitatory synapses in the cerebellar circuit

Lisa Mapelli, Martina Pagani, Jesus A. Garrido, Egidio D’Angelo

Research output: Contribution to journalArticle

Abstract

The way long-term potentiation (LTP) and depression (LTD) are integrated within the different synapses of brain neuronal circuits is poorly understood. In order to progress beyond the identification of specific molecular mechanisms, a system in which multiple forms of plasticity can be correlated with large-scale neural processing is required. In this paper we take as an example the cerebellar network, in which extensive investigations have revealed LTP and LTD at several excitatory and inhibitory synapses. Cerebellar LTP and LTD occur in all three main cerebellar subcircuits (granular layer, molecular layer, deep cerebellar nuclei) and correspondingly regulate the function of their three main neurons: granule cells (GrCs), Purkinje cells (PCs) and deep cerebellar nuclear (DCN) cells. All these neurons, in addition to be excited, are reached by feed-forward and feed-back inhibitory connections, in which LTP and LTD may either operate synergistically or homeostatically in order to control information flow through the circuit. Although the investigation of individual synaptic plasticities in vitro is essential to prove their existence and mechanisms, it is insufficient to generate a coherent view of their impact on network functioning in vivo. Recent computational models and cell-specific genetic mutations in mice are shedding light on how plasticity at multiple excitatory and inhibitory synapses might regulate neuronal activities in the cerebellar circuit and contribute to learning and memory and behavioral control.

Original languageEnglish
Article number169
JournalFrontiers in Cellular Neuroscience
Volume9
Issue numberMAY
DOIs
Publication statusPublished - May 5 2015

Keywords

  • Cerebellum
  • Excitatory synapse
  • Inhibitory synapse
  • LTD
  • LTP

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience

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