Long-Term Plasticity of Intrinsic Excitability: Learning Rules and Mechanisms

  1. Gaël Daoudal and
  2. Dominique Debanne1
  1. Institut National de la Santé Et de la Recherche Médicale UMR464 Neurobiologie des Canaux Ioniques, Institut Fédératif Jean Roche, Faculté de Médecine Secteur Nord, Université d'Aix-Marseille II, 13916 Marseille, France

Abstract

Spatio-temporal configurations of distributed activity in the brain is thought to contribute to the coding of neuronal information and synaptic contacts between nerve cells could play a central role in the formation of privileged pathways of activity. Synaptic plasticity is not the exclusive mode of regulation of information processing in the brain, and persistent regulations of ionic conductances in some specialized neuronal areas such as the dendrites, the cell body, and the axon could also modulate, in the long-term, the propagation of neuronal information. Persistent changes in intrinsic excitability have been reported in several brain areas in which activity is elevated during a classical conditioning. The role of synaptic activity seems to be a determinant in the induction, but the learning rules and the underlying mechanisms remain to be defined. We discuss here the role of synaptic activity in the induction of intrinsic plasticity in cortical, hippocampal, and cerebellar neurons. Activation of glutamate receptors initiates a long-term modification in neuronal excitability that may represent a parallel, synergistic substrate for learning and memory. Similar to synaptic plasticity, long-lasting intrinsic plasticity appears to be bidirectional and to express a certain level of input or cell specificity. These nonsynaptic forms of plasticity affect the signal propagation in the axon, the dendrites, and the soma. They not only share common learning rules and induction pathways with the better-known synaptic plasticity such as NMDA receptor dependent LTP and LTD, but also contribute in synergy with these synaptic changes to the formation of a coherent engram.

Footnotes

  • Article and publication are at http://www.learnmem.org/cgi/doi/10.1101/lm.64103.

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