Information processing by respiratory motoneurons

呼吸运动神经元的信息处理

• 批准号: 402532-2013
• 负责人: Funk, Gregory
• 金额: $ 3.42万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=630707
• 关键词: Information; processing; respiratory; motoneurons

Understanding how neurons transform input into output, i.e. how they integrate and process information, is fundamental to understanding brain function and how behaviour emerges from the activity of neural networks. The geometry of the dendritic tree has long been recognized as a critical factor in determining how synaptic input is transformed into neuronal output, but how the brain utilizes the complex geometries of neurons and their dendritic trees to achieve this function remains unclear. In this study we will use optical and electrophysiological methods (that allow us to record from single neurons) to map the information processing tree (dendrites) of motoneurons that drive respiratory muscles. These methods will be applied to brain slices from neonatal rodents that retain a functioning neural network that generates rhythmic "breathing" in a dish. This endogenous behaviour is critical. It means that the synapses mediating inspiratory drive to motoneurons will be activated in a manner similar to what happens normally; i.e. we will monitor motoneuron activity while the inspiratory synaptic input is physiologically processed by the dendritic tree. Our optical mapping will examine anatomical structure as well as functional behaviour. By using our new methods for cellular microsurgery we will modify the dendrite structure of the neuron to clarify the role of different dendrite branches in processing inspiratory inputs (i.e., do all dendrites have a similar role?). We will also explore how the electrical properties of the dendrites and inputs from modulatory neurons important in controlling brain state are organized spatially on the dendrites, how they change dendritic properties and how these changes influence integration of inspiratory inputs. These experiments will provide new insight into neuronal integration and help clarify the basis for how the brain achieves such remarkable information processing.

了解神经元如何将输入转化为输出，即它们如何整合和处理信息，对于理解大脑功能以及行为如何从神经网络的活动中产生至关重要。树突树的几何形状一直被认为是决定突触输入如何转化为神经元输出的关键因素，但大脑如何利用神经元及其树突树的复杂几何形状来实现这一功能仍不清楚。在这项研究中，我们将使用光学和电生理方法（使我们能够从单个神经元记录）来绘制驱动呼吸肌的运动神经元的信息处理树（树突）。这些方法将应用于新生啮齿动物的大脑切片，这些大脑切片保留了一个功能正常的神经网络，可以在培养皿中产生有节奏的“呼吸”。这种内在行为至关重要。这意味着调节吸气驱动到运动神经元的突触将以类似于正常情况下发生的方式被激活;也就是说，我们将监测运动神经元的活动，而吸气突触输入由树突树进行生理处理。我们的光学映射将检查解剖结构以及功能行为。通过使用我们的细胞显微外科新方法，我们将修改神经元的树突结构，以阐明不同树突分支在处理吸气输入中的作用（即，所有的树突都有类似的作用吗？）。我们还将探讨如何在空间上的树突，它们如何改变树突的特性，以及这些变化如何影响吸气输入的整合的树突和重要的控制大脑状态的调节神经元的输入的电特性。这些实验将为神经元整合提供新的见解，并有助于阐明大脑如何实现如此卓越的信息处理的基础。