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Mechanisms for Odor Coding in the Olfactory System

Mechanisms for Odor Coding in the Olfactory System
嗅觉系统中的气味编码机制
批准号:
6775025
负责人:
MAKSIM V BAZHENOV
金额:
$32.59万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-04-01 至 2009-02-28

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中文摘要
翻译
描述(由申请人提供):该项目的总体目标是了解大脑中感觉信息处理的一般原理,特别是与加州理工学院的Gilles Laurent合作,探索无脊椎动物嗅觉系统中的气味编码、处理和学习。昆虫和哺乳动物的嗅觉系统对气味的反应是振荡的和有时间结构的。来自触角叶和嗅球的单个神经元的记录显示,在刺激诱发的振荡中,兴奋和抑制的时间模式缓慢而复杂。将解决的主要问题是:(1)嗅觉刺激是如何在嗅觉系统中编码的?(2)不同的气味浓度在嗅觉系统中是如何表现的?(3)人工智能的内在动态如何优化气味表征?(4)嗅觉信息在大脑中是如何解码的?这些问题将通过计算机模拟蝗虫嗅觉系统的霍奇金-赫胥黎模型来解决。来自蜜蜂和果蝇等其他昆虫的数据将用于推广模型预测。神经元数量接近于生物系统的网络模型将被模拟。嗅觉系统区分气味的能力将在包括几个处理水平(受体细胞,AL和蘑菇体)的模型中进行探索。研究人工智能的内在动力学在放大相似气味差异和提高信噪比方面的作用。这项工作的目标是研究细胞和网络功能的问题,这些问题很难通过实验来探索。模型中嗅觉神经元的内在和突触特性将以实验数据为基础,模型结果将与蝗虫和其他昆虫的记录进行比较。脊椎动物的嗅球和昆虫的嗅球是根据相似的解剖原理组织起来的;AL神经元的反应与嗅球相似。因此,这项研究将导致嗅觉处理的原理也可能适用于脊椎动物。由于在其他感觉系统中也观察到神经元振荡和同步,因此本研究的结论也可能为其他大脑区域的信息处理提供见解。
英文摘要
DESCRIPTION (provided by applicant): The overall goal of this project is to understand the general principles underlying the processing of sensory information in the brain and in particular to explore odor coding, processing, and learning in the invertebrate olfactory system in collaboration with Gilles Laurent at Caltech. The responses of insect and mammalian olfactory systems to an odor are oscillatory and temporally structured. Recordings from single neurons in the antennal lobe (AL) and olfactory bulb show slow, complex temporal patterns of excitation and inhibition during the stimulus-evoked oscillations. The main questions that will be addressed are: (1) How is an olfactory stimulus encoded in the olfactory system? (2) How are different odor concentrations represented in the olfactory system? (3) How do the AL intrinsic dynamics optimize odor representations? (4) How is the olfactory information decoded in the brain? These questions will be addressed using computer simulations of detailed Hodgkin-Huxley type models of the locust olfactory system. Data from other insects such as honeybee and Drosophila will be used to generalize model predictions. Network models with numbers of neurons close to that in the biological systems will be simulated. The ability of the olfactory system to discriminate between odors will be explored in the models including several levels of processing (receptor cells, AL and mushroom body). The role of AL intrinsic dynamics in amplifying differences between similar odors and improving signal/noise ratio will be studied. The goal of this work will be to examine questions of cellular and network function that are very difficult to explore experimentally. The intrinsic and synaptic properties of the olfactory neurons in the model will be based on experimental data and the results of the model will be compared with recordings from the locust and other insects. The vertebrate olfactory bulb and insect AL are organized according to similar anatomical principles; the responses of neurons in the AL are similar to those in olfactory bulb. Thus, this study will lead to principles of olfactory processing that may also apply to vertebrates. Since neuronal oscillations and synchrony are observed in other sensory systems, the conclusions of this study might also provide insights into information processing in other brain areas.
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