Mechanisms underlying brain dynamics: contributions and control by inhibitory cells and networks

大脑动力学的潜在机制：抑制细胞和网络的贡献和控制

• 批准号: 203700-2011
• 负责人: Skinner, Frances
• 金额: $ 3.5万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=569990
• 关键词: Mechanisms; underlying; brain; dynamics; contributions

It has been many decades since electrical activities were first measured from the brain. It is clear that there are distinct electrical signatures that can be correlated with normal and pathological states. However, it is far from clear how these brain signatures are generated. An understanding of how such activities are produced is needed not only to help us understand brain functioning, but also to help us diagnose and ultimately control and treat neurological diseases. My research program aims to obtain a cellular-based mechanistic understanding of population activities that produce electrical signatures in the brain. We do this by developing and analyzing mathematical models of neurons and networks. However, this is a challenge because network size and architecture, along with connectivity and cellular characteristics all need to be considered. We tackle this challenge by focusing on a brain structure important for learning and memory, the hippocampus, and on which much experimental data is available. We aim to develop models based on well-defined population activities that have been recorded at both the cellular and population levels in hippocampus. In this way there can be a bidirectional relationship between model and experiment as mechanisms and hypotheses are developed with our models and analyses to understand brain activities. In particular, we focus on specific inhibitory cell types as they have been shown not only to be diverse in a functionally relevant fashion, but also to be the controllers of several population activities. Thus, the overall objective of this proposal is to understand the contribution of hippocampal inhibitory cells by building and examining neuronal and network models with particular connections and with particular cellular properties in well-defined experimental contexts.

自从第一次从大脑中测量电活动以来，已经有几十年了。 很明显，存在可以与正常和病理状态相关的不同的电特征。 然而，目前还不清楚这些大脑信号是如何产生的。 了解这些活动是如何产生的，不仅有助于我们了解大脑的功能，也有助于我们诊断并最终控制和治疗神经系统疾病。 我的研究计划旨在获得一个基于细胞的机械理解的人口活动，在大脑中产生的电子签名。 我们通过开发和分析神经元和网络的数学模型来做到这一点。 然而，这是一个挑战，因为网络规模和架构，沿着连接性和蜂窝特性都需要考虑。 我们通过专注于对学习和记忆很重要的大脑结构海马体来应对这一挑战，并且可以获得许多实验数据。 我们的目标是开发模型的基础上定义明确的人口活动，已记录在细胞和人口水平的海马。 通过这种方式，可以在模型和实验之间建立双向关系，因为机制和假设是通过我们的模型和分析来理解大脑活动的。 特别是，我们专注于特定的抑制性细胞类型，因为它们已被证明不仅在功能相关的方式是多样化的，而且是几个群体活动的控制器。 因此，本提案的总体目标是通过建立和检查具有特定连接和特定细胞特性的神经元和网络模型，在明确定义的实验环境中了解海马抑制细胞的贡献。