Neuroinformatic Analysis of Olfactory Coding

描述（由申请人提供）：我们的目标是使用神经信息学来帮助解决两种嗅觉编码模型出现的相互矛盾的发现。一个模型提出，非常多的低特异性神经反应代表每一种气味，另一个模型表明，更少，更具体的嗅觉受体结合到特定的分子特征，这些特定的反应的组合表征每一种气味。由于支持低特异性模型的大部分数据都是在不考虑嗅觉系统的空间异质性的情况下收集的，如果将不同实验室收集的不同类型的数据放在空间上相互注册，那么结论中的差异就可能得到解决。为此，我们一直在建立一个档案馆的肾小球反应的空间模式引起了广泛的气味，我们已经能够测试的假设，通过计算同源性在肾小球层的反应模式的嗅觉编码的策略。为了促进我们的分析任务，并使其他人能够将他们的数据与这个气味反应档案库注册，我们建议继续开发嗅球数据的分析和可视化软件。我们还建议将这种方法扩展到嗅觉上皮和嗅觉皮层，以便能够理解嗅觉系统的初始编码和合成水平。 这些努力将通过我们的嗅觉活动档案发布的网站免费提供。我们建议通过整合元数据以及来自使用其他物种和其他类型数据的实验室的数据来改进该网站，例如可以定位在空间中的病变和神经生理数据。最后，我们必须测试各种各样的气味剂来捕捉系统的感觉，这也将需要使用信息学方法，使我们能够测试关于化学结构在系统中表示的复杂方法的假设。这些方法的结合应该有助于解决嗅觉编码的冲突模型之间的差异。

DESCRIPTION (provided by applicant): Our goal is to use neuroinformatics to help resolve the conflicting findings from which two models of olfactory coding have emerged. One model proposes that very many low-specificity neural responses represent each odorant and the other model suggests that fewer, more specific olfactory receptors bind to particular molecular features and that the combination of these specific responses characterizes each odorant. Since much of the data supporting the low-specificity model has been collected without regard for the exquisite spatial heterogeneity of the olfactory system, it is possible that the differences in conclusions could be resolved if the distinct types of data that are collected by various laboratories were placed into spatial register with one another. To that end, we have been building an archive of the spatial patterns of glomerular responses evoked by a wide range of odorants, and we have been able to test hypotheses regarding strategies of olfactory coding by calculating homologies across glomerular-layer response patterns. To facilitate our analytical task, and to make it feasible for others to place their data in register with this odorant response archive, we propose to continue to develop analytical and visualization software for olfactory bulb data. We also propose to extend this approach to both the olfactory epithelium and olfactory cortex to be able to understand both the initial coding and synthetic levels of the olfactory system. These efforts will be freely available via the web site on which our olfactory activity archive is posted. We propose to improve the site by incorporating meta-data, as well as data from labs using other species and other types of data, such as lesions and neurophysiological data that can be located in space. Finally, the wide range of odorants that we must test to capture a sense of the system also will necessitate the use of an informatics approach to allow us to test hypotheses regarding the complex means by which chemical structure is represented in the system. The combination of these approaches should help resolve the differences between the conflicting models of olfactory coding.