Dendritic integration in a midbrain circuit controlling innate escape responses

为了生存，动物必须不断监测其环境，整合外部和内部信息并做出适当的行为反应。例如，当受到捕食者威胁时，危险的紧迫性和背景会指导执行防御行为，例如逃跑、冻结或攻击。控制本能行为选择的计算在动物物种中高度保守，但人们对它们如何在细胞水平上实现知之甚少。在这个项目中，我们将研究中导水管周围灰质（PAG）神经元如何计算逃离先天掠夺性威胁的决定，尽管它是执行防御行为的关键区域，但人们对它仍然知之甚少。结合行为学、神经生理学和先进的分子生物学技术，在本研究的第一部分，我们将检查 PAG 回路中神经元的基本特性，旨在确定将掠夺性威胁与执行飞行反应联系起来的突触整合过程的树突、突触和分子基础。在该项目的第二部分，我们将测试控制先天行为的神经元回路是否是遗传性的，或者 PAG 中的信息处理是否可以通过经验和学习进行调节。该项目将有助于理解关键中脑回路中的单个神经元如何计算并将掠夺性威胁的传入感官信息转化为关键的生存行为。

In order to survive, animals must constantly monitor their environment, integrate external and internal information and engage in appropriate behavioural responses. For example, when threatened by a predator, the imminence and context of the danger directs the execution of defensive behaviours such as escape, freezing or attack. The computations that control instinctive behavioural choices are highly conserved across animal species, but little is known about how they are implemented at the cellular level. In this project, we will investigate how the decision to escape from innate predatory threats is computed by neurons in the periaqueductal gray (PAG), which remain poorly understood despite being a key area involved in the execution of defensive behaviours. Employing a combination of behavioural, neurophysiological and advanced molecular biological techniques, in the first part of this study we will examine the basic properties of neurons in the PAG circuit, and aim to determine the dendritic, synaptic and molecular basis of synaptic integration processes that link predatory threats to the execution of flight responses. In the second part of the project, we will test whether neuronal circuits controlling innate behaviours are genetically hard-wired or whether information processing in the PAG can be modulated through experience and learning. This project will contribute to the understanding of how the single neurons in a key midbrain circuit compute and convert incoming sensory information of a predatory threat into a critical survival behaviour.