Manis Paul B, Campagnola Luke
Dept. of Otolaryngology/Head and Neck Surgery, B027 Marsico Hall, 125 Mason Farm Road, UNC Chapel Hill, Chapel Hill, NC 27599-7070, USA.
Dept. of Otolaryngology/Head and Neck Surgery, B027 Marsico Hall, 125 Mason Farm Road, UNC Chapel Hill, Chapel Hill, NC 27599-7070, USA.
Hear Res. 2018 Mar;360:76-91. doi: 10.1016/j.heares.2017.12.017. Epub 2017 Dec 28.
Models of the auditory brainstem have been an invaluable tool for testing hypotheses about auditory information processing and for highlighting the most important gaps in the experimental literature. Due to the complexity of the auditory brainstem, and indeed most brain circuits, the dynamic behavior of the system may be difficult to predict without a detailed, biologically realistic computational model. Despite the sensitivity of models to their exact construction and parameters, most prior models of the cochlear nucleus have incorporated only a small subset of the known biological properties. This confounds the interpretation of modelling results and also limits the potential future uses of these models, which require a large effort to develop. To address these issues, we have developed a general purpose, biophysically detailed model of the cochlear nucleus for use both in testing hypotheses about cochlear nucleus function and also as an input to models of downstream auditory nuclei. The model implements conductance-based Hodgkin-Huxley representations of cells using a Python-based interface to the NEURON simulator. Our model incorporates most of the quantitatively characterized intrinsic cell properties, synaptic properties, and connectivity available in the literature, and also aims to reproduce the known response properties of the canonical cochlear nucleus cell types. Although we currently lack the empirical data to completely constrain this model, our intent is for the model to continue to incorporate new experimental results as they become available.
听觉脑干模型一直是检验听觉信息处理假说以及凸显实验文献中最重要空白的宝贵工具。由于听觉脑干乃至大多数脑回路的复杂性,如果没有一个详细的、符合生物学实际的计算模型,系统的动态行为可能很难预测。尽管模型对其精确构建和参数很敏感,但大多数先前的耳蜗核模型只纳入了已知生物学特性的一小部分。这混淆了建模结果的解释,也限制了这些模型未来的潜在用途,而开发这些模型需要付出巨大努力。为了解决这些问题,我们开发了一个通用的、具有生物物理细节的耳蜗核模型,用于检验关于耳蜗核功能的假说,也作为下游听觉核模型的输入。该模型使用基于Python的NEURON模拟器接口实现基于电导的霍奇金 - 赫胥黎细胞表示。我们的模型纳入了文献中大多数定量表征的内在细胞特性、突触特性和连接性,并且旨在重现典型耳蜗核细胞类型的已知反应特性。尽管我们目前缺乏完全约束该模型的经验数据,但我们的意图是随着新实验结果的出现,该模型继续纳入这些结果。