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

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，从而参与网络结构。此外，神经胶质细胞通过它们自己的通讯网络连接在一起，这种通讯网络与神经元网络并行运行，但又不同于神经元网络。虽然神经网络已被深入研究，但神经胶质网络在调节通过神经元的信息流中的作用尚未得到深入研究。体外神经元系统使我们能够研究神经回路的潜在机制，并由此开始研究相互连接的神经元集合的放电模式中出现的复杂行为。我的研究计划旨在进一步发展该技术，同时获取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：目标1)增强在我的第一个DG中开发的神经元/硅器件的活动检测功能，这将允许记录神经元和神经胶质细胞的复杂活动模式。这将包括一个帧率为200帧/秒的高分辨率CCD芯片，以及一个内置光源，当神经元或神经胶质事件触发荧光传感器发出的光时，它就会被检测出来。这将允许扩展获取足够的空间和时间分辨率的神经元和胶质活动数据，以执行网络结构的多层分析。目的2)进行动态系统分析，以确定神经胶质活动模式如何改变通过神经元网络的信息流。到目前为止，还没有技术可以估计这些种群是如何大规模交流的。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理论的技术，特别是传递熵，来确定两者之间的因果相互作用。最终的目标将是应用因果深度学习，一种结合信息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)在我们的检测方法中加入表面等离子体共振（SPR）纳米粒子（NP）放大光子信号。在过去十年中，SPR在生物传感器设计中的应用得到了大力发展。我的实验室已经开发了一种脂质封装技术，用于将银NPs输送到培养的活神经元中，初步结果表明它们可以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元系统的理解，并最终促进对大脑的理解。

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.