Development and use of an enhanced neuronal/silicon interface for the study of neuronal system dynamics.

开发和使用增强的神经元/硅接口来研究神经元系统动力学。

• 批准号: RGPIN-2020-05218
• 负责人: Colicos, Michael
• 金额: $ 2.04万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=763336
• 关键词: Development; use; enhanced; neuronal; silicon

Brain function results from the propagation of information through networks of interconnected neurons. Glial cells provide physiological support for neurons but also directly modulate neuronal activity and thus contribute to the network structure. Moreover, glial cells are connected together in their own communication network that runs in parallel to, but is distinct from, the neuronal network. While neuronal networks have been intensely studied, the role of glial networks in modulating the flow of information through the neurons has not. In vitro neuronal systems have allowed us to investigate the underlying mechanisms of neural circuits, and from this has come the study of emergent complex behaviors in the firing patterns of ensembles of interconnected neurons. My research program aims at further development of the technology to acquire high spatial and temporal resolution recordings of both neuronal and glial activity simultaneously, and to then to use novel analysis techniques to determine the relationship between the two. My research goals are: Aim 1) To enhance the neuronal/silicon device developed in my first DG with activity detection features which will allow complex activity patterns in both neurons and glial cells to be recorded. This will involve incorporation of a high resolution CCD chip with a 200 fps frame rate, coupled to a built in light source, detecting light emitted by fluorescent sensors when they are triggered by neuronal or glial events. This will allow the extended acquisition of neuronal and glial activity data of sufficient spatial and temporal resolution to perform multi-layer analysis of network structure. Aim 2) To perform dynamical systems analysis to determine how glial activity patterns change the flow of information through the neuronal network. To date, no technique has existed to estimate how these populations communicate at a large scale. To address the relationship between the neuronal and glial networks we will identify causal interactions between the two by extending techniques from Information Theory, in particular Transfer Entropy. Ultimately the goal will be to apply Causal Deep Learning, a method that combines Information Theory and Deep Learning, to infer neuronal and glial connectivity. Aim 3) Incorporate surface plasmon resonance (SPR) nanoparticle (NP) amplification of photonic signals in our detection methodology. The use of SPR in the design of biosensors has been under intense development for the past decade. My lab has developed a lipid encapsulation technique for delivering silver NPs to living cultured neurons, and preliminary results suggest they can be used for detection of changes in membrane potential. This project also provides a potential strategy to detect biophotonic emission from neural tissue, a long pursued hypothesis in the realm of quantum neuroscience. Development of these technologies will advance our understanding of complex neuronal systems, and ultimately, the brain.

大脑功能是通过相互连接的神经元网络传播信息的结果。神经胶质细胞为神经元提供生理支持，但也直接调节神经元活动，从而有助于网络结构。此外，神经胶质细胞在它们自己的通信网络中连接在一起，该通信网络与神经元网络平行运行，但与神经元网络不同。虽然神经元网络已经被深入研究，但神经胶质网络在调节通过神经元的信息流中的作用还没有。体外神经元系统使我们能够研究神经回路的潜在机制，并由此产生了对相互连接的神经元集合的放电模式中涌现的复杂行为的研究。我的研究计划旨在进一步发展该技术，以同时获得神经元和神经胶质活动的高空间和时间分辨率记录，然后使用新的分析技术来确定两者之间的关系。我的研究目标是：目的1）增强在我的第一个DG中开发的具有活动检测功能的神经元/硅器件，这将允许记录神经元和胶质细胞中的复杂活动模式。这将涉及结合具有200 fps帧速率的高分辨率CCD芯片，该芯片耦合到内置光源，当荧光传感器被神经元或神经胶质事件触发时检测荧光传感器发出的光。这将允许扩展获取足够的空间和时间分辨率的神经元和神经胶质活动数据，以执行网络结构的多层分析。目的2）进行动力系统分析，以确定胶质细胞活动模式如何改变通过神经元网络的信息流。到目前为止，还没有技术来估计这些人群如何大规模地交流。为了解决神经元和神经胶质网络之间的关系，我们将通过扩展信息论的技术，特别是转移熵来确定两者之间的因果关系。最终的目标将是应用因果深度学习，一种结合信息理论和深度学习的方法，来推断神经元和神经胶质的连接。目的3）将表面等离子体共振（SPR）纳米粒子（NP）的光子信号放大技术引入到我们的检测方法中。SPR在生物传感器设计中的应用在过去的十年中一直处于激烈的发展之中。我的实验室已经开发出一种脂质包封技术，用于将银纳米颗粒递送到活的培养神经元中，初步结果表明它们可用于检测膜电位的变化。该项目还提供了一种潜在的策略来检测神经组织的生物光子发射，这是量子神经科学领域长期追求的假设。这些技术的发展将促进我们对复杂神经系统的理解，并最终促进对大脑的理解。