Temporal Coding in an Olfactory Circuit

嗅觉回路中的时间编码

• 批准号: 9511764
• 负责人: Gilles Laurent
• 金额: $ 24.96万
• 依托单位: California Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-08-01 至 1999-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9511764&HistoricalAwards=false
• 关键词: Temporal; Coding; Olfactory; Circuit

9511764 Laurent Although brains and computers are thought to be quite similar, the mechanisms which they use to encode and store information are fundamentally different. This is partly because computers were developed by engineers using tools of formal logic to solve rather limited sets of problems, while brains were developed over millions of years with selective pressure of evolution as the only engineer. Indeed, brains evolved to increase the chances of survival of their "owners", and thus primarily to facilitate the detection of prey, predators and mates. Consequently, they succeeded in solving the very complex problems of pattern recognition, problems which present computers are notoriously poor at handling. How do we recognize something as complex as a face or an odor, how do we store their infinite number of possible appearances, how does our brain represent them with neuronal activity patterns? To understand this, we must understand coding in the nervous system; we need to determine the rules that underlie stimulus representation in the brain. Conventional views of coding by the brain hold that information resides in the average number of impulses produced per unit time (rate coding); the role of relative timing of impulses produced by groups of neurons has not been carefully evaluated. The work of this young scientist focuses on circuits that process smells. Experiments are designed to determine whether the relative timing of neuronal impulses (temporal coding) is a potential carrier for information.

9511764 Laurent认为大脑和计算机非常相似，但它们用于编码和存储信息的机制在根本上是不同的。这部分是因为工程师是使用正式逻辑工具来解决相当有限的问题的工程师开发的，而大脑是在数百万年内开发的，而进化的选择性压力是唯一的工程师。的确，大脑进化出来增加了其“所有者”生存的机会，因此主要是为了促进猎物，捕食者和伴侣的检测。因此，他们成功地解决了模式识别的非常复杂的问题，众所周知，这些问题在处理方面臭名昭著。我们如何认识到像面部或气味一样复杂的事物，如何存储它们的无限数量可能的外观，我们的大脑如何用神经元活动模式代表它们？要了解这一点，我们必须了解神经系统中的编码。我们需要确定大脑中刺激表示的规则。 大脑编码的常规观点认为，信息存在于单位时间产生的平均冲动数（费率编码）；尚未仔细评估由神经元组产生的冲动的相对时间的作用。这位年轻科学家的工作专注于过程闻起来的电路。 实验旨在确定神经元脉冲（时间编码）的相对时机是否是信息的潜在载体。