Context-dependent neural coding

上下文相关的神经编码

• 批准号: 0928251
• 负责人: Adrienne Fairhall
• 金额: $ 45.43万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928251&HistoricalAwards=false
• 关键词: Context; dependent; neural; coding

The outputs from neuronal systems adapt following a change in a stimulus, through a variety of mechanisms acting on different timescales. Many systems show a rapid form of adaptation through which stimuli are encoded relative to the context within which they were presented. This form of context-modulated coding is ubiquitous through sensory and higher-level systems, and may support the ability of the nervous system to efficiently encode complex natural stimuli. Experiments have shown that this form of gain control occurs both in neural systems and in single neurons in the cortex. On longer timescales, neural systems show a decrease of activity after long exposure to a constant stimulus. It is proposed that this behavior is a reflection of intrinsic neuronal dynamics that may contribute to the efficient coding of the slowly-varying stimulus envelope. This project will further develop the hypothesis that these slow dynamics may reflect the system's ongoing estimate of the changing statistical characteristics of the input. The mechanisms for these adaptive behaviors will be pursued with a combination of theoretical analysis and simulation of realistic neuronal models. The project's goal is to elucidate the mathematical basis of fundamental neural mechanisms for the efficient encoding of time-varying signals and reveal optimal strategies for sampling and representing complex natural environments. This work examines neural coding mechanisms that apply to multiple sensory and higher brain systems and will help to develop a language and methodology that can translate across these areas. The interdisciplinary nature of the work will provide training opportunities for undergraduate and graduate students crossing over from mathematics and physics to biology. The project includes the development of a summer course for advanced high school students.

神经元系统的输出通过在不同的时间尺度上作用的多种机制来适应刺激的变化。许多系统表现出一种快速的适应形式，通过，刺激相对于呈现它们的上下文进行了编码。这种形式的上下文调制编码通过感觉和更高级别的系统无处不在，并且可以支持神经系统有效编码复杂自然刺激的能力。实验表明，这种增益控制形式既发生在神经系统和皮层中的单个神经元中。在更长的时间尺度上，神经系统在长时间暴露于恒定刺激后显示活性下降。有人提出，这种行为反映了内在神经元动力学的反映，可能有助于缓慢变化的刺激包膜的有效编码。该项目将进一步发展以下假设：这些缓慢的动态可能反映了系统对输入统计特征不断变化的持续估计。这些自适应行为的机制将通过理论分析和现实神经元模型的仿真结合来实现。该项目的目标是阐明有效编码时变信号的基本神经机制的数学基础，并揭示用于采样和代表复杂自然环境的最佳策略。这项工作研究了适用于多种感觉和更高脑系统的神经编码机制，并将有助于开发一种可以在这些领域转化的语言和方法。这项工作的跨学科性质将为从数学和物理学到生物学的本科生和研究生提供培训机会。该项目包括为高级高中生开发夏季课程。