MIXTURE INTERACTIONS IN OLFACTION

该项目的长期目标是发现基本的 关于气味物质检测和鉴别的原则 混合物及其组份。这项研究的重点将是 对混合气味的反应，这将作为一个模式 适用于更复杂的混合物。研究中的一种常见观察 气味或味觉的混合物是对混合物的反应 往往是不可预测的，即使是在对个人的反应 混合物的成分是已知的。这些现象被称为 混合物相互作用是普遍存在的，在人类中也存在。 作为低等动物。建议的项目用作实验项目 动物模型刺龙虾Panulirus Argus，已经证明 成为研究嗅觉的优秀系统，包括 混合物相互作用与质量的行为和神经方面 编码。该项目的具体目标是：(1)确定和 二元气味物质的嗅觉混合物相互作用特征 混合物；和(20评估混合物相互作用对 旗帜质量的行为学和神经学判别 气味混合物。将确定混合物相互作用，并 配体-受体行为模型的诉求特征 有约束力的。混合物交互作用对性别差异的影响 混合香料及其成分的质量将是 描述了Btu评价双基混合物的质量鉴别。 包含门不显示混合物相互作用的组件， 使用以前开发的技术；：多变量分析 嗅觉感受器细胞的单位神经生理学数据 嗅觉脑神经间质用于神经辨别； 差分厌恶结果的多元分析 行为歧视的条件反射。

The long-term objective of this project is to discover basic principles concerning the detection and discrimination of odorant mixtures and their componets. The focus of this research will been responses to bianry odorant mixture, which will serve as a model for more complex mixtures. A common observation in studies of mixtures of odorant or tastants is that responses to mixtures are often not predictable, even when thresponses to the individual components of the mixtures are known. These phenomena, termed mixture interactions, are widespread, occurring in humans as well as lower animals. The proposed project uses as the experimental animal model the spiny lobster Panulirus argus, which has proven to be an excellent system for studies of olfaction, including mixture interactions and behavioral and neural aspects of quality coding. The specific aims of this project are to: (1) identify and characterize olfactory mixture interactions for binary odorant mixtures; and (20 evaluate the effects of mixture interactions on behavioral and neural discrimination of the quality of banner odorant mixtures. Mixture interactions will be identified and characteri by appealing behavioral models of ligand-receptor binding. The effects of mixture interactions on discrimination of quality of bianry odorant mixtures and their components will be described btu evaluating quality discrimination for bianry mixtures containing componets that door do not show mixture interactions, using previously developed techniques;: multivariate analysis of single-unit neurophysiological data from olfactory receptor cells and olfactory brain interneurone for neural discrimination; multivariate analysis of results of differential aversive conditioning for behavioral discrimination.