Strategies for encoding odor information

气味信息编码策略

• 批准号: 8260194
• 负责人: Barry W. ACHE
• 金额: $ 21.98万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-26 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8260194
• 关键词: Animal Model; Characteristics; Code; Complex; Computer Simulation; Detection; Functional disorder; Human; Literature; Odors; Olfactory Receptor Neurons; Optics; Output; Perception; Peripheral; Physiological; Process; Relative (related person); Research; Signal Transduction; Structure; System; Testing; design; relating to nervous system; research study; spatiotemporal

DESCRIPTION (provided by applicant): Odor information is generally assumed to be encoded by olfactory receptor neurons (ORNs) in which odorants evoke a tonic discharge. Exciting new evidence extends hints in the earlier literature that some ORNs are not tonically active, but rather are inherently rhythmically active or 'bursting' ORNs (bORNs) in which the rhythmic bursting is entrained by odorants. bORNs open up an entirely new possibility for encoding odor information, in particular information relative to the spatiotemporal characteristics of the odor signal. Experiments are proposed using an animal model in which both tonically active and bORNs are well characterized physiologically to compare the potential of both types of ORNs to encode odor information. This will be done by first using computational modeling to test the hypothesis that synchronization of large ensembles of bORNs selectively favors (1) the detection and amplification of weak odor signals and (2) the detection and coding of the temporal characteristics of the odor signal itself compared to tonically active ORNs. Combined optical and electrophysiological recording from small ensembles of actual ORNs will then be used to experimentally test the predictions of the computational model. This project has the capacity to identify a heretofore unappreciated way in which olfactory information is encoded. PUBLIC HEALTH RELEVANCE: This project has the potential to derive a heretofore unappreciated principle of olfactory information encoding and processing that can be used not only to better understand olfactory dysfunction in humans but also to better design artificial systems capable of analyzing and localizing complex chemosensory signals.

描述(申请人提供)：气味信息通常被认为是由嗅觉感受器神经元(ON)编码的，在这些神经元中，气味引起紧张性放电。令人兴奋的新证据扩展了早期文献中的暗示，即一些鸟儿并不是音调活跃的，而是天生就有节奏活跃的，或者是被气味缠绕的节奏爆发的鸟儿(出生的)。Borns为气味信息的编码开辟了一种全新的可能性，特别是与气味信号的时空特征相关的信息。实验采用了一种动物模型，在该模型中，张力活跃和出生的婴儿都具有良好的生理特征，以比较这两种类型的Orn编码气味信息的潜力。这将通过首先使用计算建模来检验这样的假设来完成，即出生的大集合的同步选择性地有利于(1)微弱气味信号的检测和放大，以及(2)与音调活跃的Orn相比，气味信号本身的时间特征的检测和编码。然后，来自实际Orn的小集合的光学和电生理组合记录将被用于对计算模型的预测进行实验测试。这个项目有能力识别一种迄今未被赏识的嗅觉信息编码方式。 与公共卫生相关：该项目有可能衍生出一种迄今未被认可的嗅觉信息编码和处理原理，不仅可以用来更好地了解人类的嗅觉功能障碍，还可以更好地设计能够分析和定位复杂化学感觉信号的人工系统。