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OSCILLATIONS AND TEMPORAL ENCODING OF OLFACTORY INFO

OSCILLATIONS AND TEMPORAL ENCODING OF OLFACTORY INFO
嗅觉信息的振荡和时间编码
批准号:
2909923
负责人:
GILLES J LAURENT
金额:
$21.21万
依托单位国家:
美国
项目类别:
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-05-01 至 2003-04-30

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中文摘要
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英文摘要
DESCRIPTION: (Adapted from applicant's abstract): A major goal of modern neuroscience is to understand the various facets of neural coding. While it is widely accepted that firing rates of neurons usually encode features of a stimulus or of the behavioral state of the animal, recent results from mammals, insects, and mollusks suggest that temporal features of activity in single groups of neurons might also contain useful information. The goal of this proposal is therefore to explore the nature of a specific temporal coding scheme by olfactory neuronal ensembles in the brain, to assess its potential relevance for perception, and to understand some of the mechanisms that might allow decoding of temporal "messages" by downstream circuits. This work will be carried out using the olfactory system of insects, which is structured and operates along the same design principles as its vertebrate (including mammalian) counterpart, and in which stimulus-evoked oscillatory synchronization of neurons and complex temporal response patterns have recently been described. The insect nervous system contains a glomerular antennal lobe, analogous to the vertebrate olfactory bulb, and a mushroom body, analogous to the piriform cortex and downstream cortical structures. Recently a mechanism has been identified to desynchronize odor-activated antennal lobe neurons in vivo. This knowledge will be used to investigate the following: 1) The potential mechanisms for decoding temporal patterns of neural activity in the mushroom bodies, in particular the potential role of oscillations as a selective filter and the sensitivity of central neurons to the temporal structure of their input; 2) The dependence of temporal activity patterns of the antennal lobe's principal neurons on odor concentration and complexity; 3) The emergence of neuronal temporal patterns during odor "learning", by studying the evolution of the responses of principal neurons from a "naive" to a "familiar" state; and, 4) The local circuit dynamics and coupling within the antennal lobes, by examining the degree of correlation between response "noisiness" of simultaneously recorded neurons. An understanding of temporal coding schemes in a complex brain circuit specialized for pattern recognition (the olfactory system) will provide crucial insights into the basic principles of stimulus representation and recognition in sensory systems.
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