Plasticity and stability in neuronal output via changes in intrinsic excitability: it's what's inside that counts.

The nervous system faces an extremely difficult task. It must be flexible, both during development and in adult life, so that it can respond to a variety of environmental demands and produce adaptive behavior. At the same time the nervous system must be stable, so that the neural circuits that produce behavior function throughout the lifetime of the animal and that changes produced by learning endure. We are only beginning to understand how neural networks strike a balance between altering individual neurons in the name of plasticity, while maintaining long-term stability in neural system function. The balance of this plasticity and stability in neural networks undoubtedly plays a critical role in the normal functioning of the nervous system. While mechanisms of synaptic plasticity have garnered extensive study over the past three decades, it is only recently that more attention has been turned to plasticity of intrinsic excitability as a key player in neural network function. This review will focus on this emerging area of research that undoubtedly will contribute a great deal to our understanding of the functionality of the nervous system.