Physiological models of the lateral superior olive
Physiological models of the lateral superior olive
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DOI：
10.1371/journal.pcbi.1005903
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发表时间：
2017-12-01
影响因子：
4.3
通讯作者：
Kretzberg, Jutta
中科院分区：
文献类型：
--
作者：
Ashida, Go;Tolling, Daniel J.;Kretzberg, Jutta
在计算生物学中，建模是描述、分析和预测复杂现象的基本工具。然而，大多数神经元模型的设计是为了重现某些小的经验数据集。因此，它们的结果通常与其他模型或数据集不兼容或不可比，因此不清楚这些模型的适用范围有多广。在这项研究中，我们研究了建模的这些方面，即可信度和泛化，特别是涉及声源定位的听觉神经元。双耳声音定位的主要线索是两耳间的时间差和水平差(ITD/ILD)，这是到达两只耳朵的声波的时间和强度差异。听觉脑干中的外侧上橄榄核(LSO)是这种声学信息最早被计算的位置之一。LSO神经元接收分别由同侧和对侧声音刺激驱动的具有时间结构的兴奋性和抑制性突触输入，并根据双耳声学差异改变其尖峰频率。在这里，我们研究了具有不同生物物理复杂性水平的七个当代LSO神经元模型，从主要功能的模型(“散粒噪声”模型)到那些具有更详细的生理组件(集成与火灾和Hodgkin-Huxley类型的变体)的模型。这些模型经过校准以再现LSO的已知单耳和双耳特性，在模拟ITD和ILD编码时产生彼此基本相似的结果。我们对模型的生理细节、计算效率、预测性能和进一步的可扩展性的比较表明：(1)简单、功能性的LSO模型适用于需要低计算成本和数学透明度的应用；(2)对于亚神经元非线性过程起重要作用的模拟研究，需要更复杂的具有详细膜电位动力学的模型；(3)对于一般目的，中间模型可能是简单性和生物学合理性之间的合理折衷。
In computational biology, modeling is a fundamental tool for formulating, analyzing and predicting complex phenomena. Most neuron models, however, are designed to reproduce certain small sets of empirical data. Hence their outcome is usually not compatible or comparable with other models or datasets, making it unclear how widely applicable such models are. In this study, we investigate these aspects of modeling, namely credibility and generalizability, with a specific focus on auditory neurons involved in the localization of sound sources. The primary cues for binaural sound localization are comprised of interaural time and level differences (ITD/ILD), which are the timing and intensity differences of the sound waves arriving at the two ears. The lateral superior olive (LSO) in the auditory brainstem is one of the locations where such acoustic information is first computed. An LSO neuron receives temporally structured excitatory and inhibitory synaptic inputs that are driven by ipsi-and contralateral sound stimuli, respectively, and changes its spike rate according to binaural acoustic differences. Here we examine seven contemporary models of LSO neurons with different levels of biophysical complexity, from predominantly functional ones ('shot-noise' models) to those with more detailed physiological components (variations of integrate-and-fire and Hodgkin-Huxley-type). These models, calibrated to reproduce known monaural and binaural characteristics of LSO, generate largely similar results to each other in simulating ITD and ILD coding. Our comparisons of physiological detail, computational efficiency, predictive performances, and further expandability of the models demonstrate (1) that the simplistic, functional LSO models are suitable for applications where low computational costs and mathematical transparency are needed, (2) that more complex models with detailed membrane potential dynamics are necessary for simulation studies where sub-neuronal nonlinear processes play important roles, and (3) that, for general purposes, intermediate models might be a reasonable compromise between simplicity and biological plausibility.