Analysis of combinatorial olfactory coding

组合嗅觉编码分析

• 批准号: 6492129
• 负责人: KEVIN C DALY
• 金额: $ 7.37万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-05-01 至 2005-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6492129
• 关键词: Manduca; biological models; chemical chain length; chemical structure; conditioning; electrophysiology; experience; histology; learning; mathematical model; neural information processing; neural plasticity; odors; olfactory stimulus; sensory discrimination

Processing of pheromonal odorants has evolved in what is referred to as a labeled-line system, whereby single odorants of a given pheromonal blend bind to specific receptors as well as specific down stream processing pathways. The solution of the pheromonal odor-coding problem has evolved in response to specific evolutionary constrains of mate location and discrimination of conspecifics from those of closely related species. In the case of non-pheromonal odors, olfactory systems appear to have evolved with a small number of relatively broadly tuned receptors, as well as glomeruli, to code for a large number of ephemeral odors by processing odor information in a combinatorial manner whereby odors are assessed along a number of odor dimensions. Indeed, by their very nature, combinatorial coding schemes have a far greater capacity for odor discrimination than do labeled line schemes. However, while it is becoming increasingly clear that odor codes are distributed the specification of odor dimensionality is still poorly defined. The specific aims of this R03 are designed to develop methods for quantifying and analyzing variation in signal processing of non-pheromonal odors that vary systematically along a restricted set of proposed odor dimensions, such as carbon chain length, and, whether experience enhances the statistical distinctiveness of these representations. Aim 1 is designed to assess the degrees to which related odors are coded for in spatiotemporal overlapping, or combinatorial codes that vary systematically along dimensions that codify corresponding variation in the geometry of these odors. Here we will statistically model the spatiotemporal relatedness of arrays of odors that systematically vary along specified geometric dimensions. It has also been demonstrated that learning changes the odor code in some clear and reproducible ways. Yet the role these changes play are poorly understood. One likely possibility is that these changes enhance the discriminability of odors. Aim 2 further develops Aim 1 by looking at how the relatedness of these overlapping spatiotemporal odor codes changes as moths are conditioned to related odors to food.

信息素气味剂的处理已在所谓的标记线系统中发展，其中给定信息素混合物的单一气味剂与特定受体以及特定下游处理途径结合。信息素气味编码问题的解决方案是为了响应交配位置的特定进化限制以及同种动物与密切相关物种的区别而不断发展的。就非信息素气味而言，嗅觉系统似乎已经进化出少量相对广泛调节的受体以及肾小球，通过以组合方式处理气味信息来编码大量短暂的气味，从而沿着多个气味维度评估气味。事实上，就其本质而言，组合编码方案比标记线方案具有更大的气味辨别能力。然而，虽然气味代码的分布越来越明显，但气味维度的规范仍然没有明确定义。 R03 的具体目标是开发用于量化和分析非信息素气味信号处理变化的方法，这些气味沿着一组有限的拟议气味维度（例如碳链长度）系统地变化，以及经验是否增强了这些表示的统计独特性。目标 1 旨在评估相关气味在时空重叠或组合代码中的编码程度，这些代码沿着编码这些气味几何形状的相应变化的维度系统地变化。在这里，我们将对沿指定几何维度系统变化的气味阵列的时空相关性进行统计建模。研究还表明，学习可以通过一些清晰且可重复的方式改变气味代码。然而，人们对这些变化所发挥的作用却知之甚少。一种可能的可能性是这些变化增强了气味的辨别能力。目标 2 通过观察这些重叠的时空气味代码的相关性如何随着飞蛾适应与食物相关的气味而变化，进一步发展了目标 1。