University of Chicago, United States.
University of Chicago, United States.
Neurobiol Learn Mem. 2021 Apr;180:107407. doi: 10.1016/j.nlm.2021.107407. Epub 2021 Feb 22.
Although information processing and storage in the brain is thought to be primarily orchestrated by synaptic plasticity, other neural mechanisms such as intrinsic plasticity are available. While a number of recent studies have described the plasticity of intrinsic excitability in several types of neurons, the significance of non-synaptic mechanisms in memory and learning remains elusive. After reviewing plasticity of intrinsic excitation in relation to learning and homeostatic mechanisms, we focus on the intrinsic properties of a class of basal-ganglia projecting song system neurons in zebra finch, how these related to each bird's unique learned song, how these properties change over development, and how they are maintained dynamically to rapidly change in response to auditory feedback perturbations. We place these results in the broader theme of learning and changes in intrinsic properties, emphasizing the computational implications of this form of plasticity, which are distinct from synaptic plasticity. The results suggest that exploring reciprocal interactions between intrinsic and network properties will be a fruitful avenue for understanding mechanisms of birdsong learning.
虽然人们认为大脑中的信息处理和存储主要是由突触可塑性来协调的,但其他神经机制,如内在可塑性,也是可用的。虽然最近有许多研究描述了几种类型神经元的内在兴奋性的可塑性,但非突触机制在记忆和学习中的意义仍然难以捉摸。在回顾了内在兴奋的可塑性与学习和动态平衡机制的关系之后,我们专注于斑胸草雀一类基底神经节投射歌唱系统神经元的内在特性,这些特性如何与每只鸟独特的习得歌曲相关,这些特性如何在发育过程中发生变化,以及它们如何动态地保持以快速响应听觉反馈的干扰。我们将这些结果置于学习和内在特性变化的更广泛主题中,强调这种形式的可塑性的计算意义,它与突触可塑性不同。结果表明,探索内在和网络特性之间的相互作用将是理解鸟鸣学习机制的一个富有成效的途径。