The Influence of Neuronal Variability on Perception and Behavior

项目摘要 我们对世界的反应不仅仅是我们感觉器官所检测到的东西的总和，而且还包括我们的感觉器官如何感知世界。 大脑选择代表这些检测，并对它们采取行动。然而，关于感官如何 输入被我们的大脑解释为产生行为输出是缺乏的。与简单的反射不同， 我们的大多数行为都受到外部世界的内部表征的支配。这种内部 状态不是静态的，而是在清醒和睡眠期间显示动态活动。简而言之， 总是在思考。即使在感官剥夺的情况下，我们大脑的几乎所有区域都保持活跃。 因此，从感官输入预测行为输出的核心挑战是， 对世界的感知是动态的，变化很大，使许多行为不可预测。 对复杂大脑内部动力学如何产生的功能基础的理解是有限的。 然而，动态的内部状态也会影响简单动物的感知和行为， 秀丽隐杆线虫它是目前唯一一个我们拥有每个神经元详细地图的生物体 和Synapse。我们可以同时操纵和监测大脑中每个神经元的活动。 这种在完全映射的大脑中操纵特定神经元的精致能力使C。理想中的优雅 生物体了解简化系统中静息态动力学的复杂性。我的长期 目标是了解神经回路如何在不同的时间尺度上产生静息态动力学， 这些状态如何影响感知和行为。了解这个过程将提供一个 理解学习过程的基础，以及管理行为的原则 新奇产生并适应环境。

Project Summary Our response to the world is not simply the sum of what our sensory organs detect, but also how our brain chooses to represent these detections, and act upon them. However, knowledge of how sensory inputs are interpreted by our brains to yield behavioral outputs is lacking. Unlike simple reflexes, the majority of our behaviors are governed by an internal representation of the external world. This internal state is not static; but shows dynamic activity during both awake and sleep periods. In short, we are always thinking. Even in sensory deprived contexts, nearly all regions of our brain remain active. Therefore, the central challenge with predicting behavioral output from sensory input is that our perception of the world is dynamic and highly variable, rendering many behaviors unpredictable. Understanding the functional underpinnings of how internal dynamics arise in complex brains is limited. However, dynamic internal states also influence perception and behavior in simple animals such as Caenorhabditis elegans. It is currently the only organism where we have a detailed map of every neuron and synapse. We can simultaneously manipulate and monitor the activity of every neuron in the brain. This exquisite ability to manipulate specific neurons in a fully mapped brain makes C. elegans the ideal organism to understand the complexity of resting state dynamics in a reduced system. My long-term goal is to understand how neural circuits generate resting state dynamics on different timescales, and how these states influence perception and behavior. Understanding this process will provide a foundation for understanding the learning process, and the principles that govern how behavioral novelty arises and adapts to the environment.