Stereology with Artificial Intelligence for Examining Cells and Circuits in Neuroscience Research

体视学是分析脑细胞的数量、形状和大小以分析神经回路的黄金标准方法。它是任何神经科学实验室的重要工具，也是关于大脑和神经回路的突破性科学发现的模式。纽芬兰纪念大学没有任何体视学设备。有了体视学系统，我们的研究人员和学生将能够放大他们现有的研究问题，以更好地了解大脑的一系列自然过程，包括特定的神经回路如何工作，是什么导致它们在整个生命中发生故障，大脑中的性别差异如何表现以及压力反应如何导致神经变化。所要求的具有人工智能（AI）的体视学系统自动量化三维（3D）结构的数量、形状和大小。SRC Stereologer的这种新的自动化深度学习AI软件具有检测两种细胞类型的能力（即，NeuN -神经元染色和Iba-1 -小胶质细胞染色），具有进一步学习的可能性。这种自动化方法在两步过程中使用深度学习AI：首先，网络通过标记为显示感兴趣细胞的图像处理地面实况来“学习”所需的感兴趣细胞。然后，该技术使用该信息，使用光学分馏器和体视学方法计算感兴趣的细胞的总数。对于神经科学和相关领域的MUN研究人员来说，使用人工智能获取体视学将使我们能够以时间和成本效益的方式收集国际知名规模的高质量数据。随着人工智能模块（美国国家卫生研究院倡议的产品）的最新发展，与目前我们唯一的选择劳动密集型和容易出错的手动方法相比，细胞计数的速度快30-60倍，准确度也高得多。由于模拟联合国是纽芬兰岛唯一的大学，模拟联合国研究人员没有实际的替代方案来访问体视学设备。所要求的设备将允许在MUN的数十个NSERC资助的研究项目的增长和每年约200名HQP的培训。这个体视学单位将加快生产力和发现，同时使我们的研究人员和学生在我们追求推进神经系统知识的过程中保持国际竞争力。

Stereology is the gold-standard method for analyzing the number, shape and size of brain cells for analyzing neural circuits. It is an essential tool for any neuroscience laboratory, and is the mode through which ground-breaking scientific discoveries about the brain and neural circuits are made. Memorial University of Newfoundland (MUN) does not have any stereology equipment. With a stereology system, our researchers and students would be able to amplify their existing research questions to better understand a range of natural processes of the brain, including how specific neural circuits work and what causes them to malfunction throughout life, how sex differences in the brain manifest and how stress responses lead to neural changes. The requested stereology system with artificial intelligence (AI) automatically quantifies the number, shape and size of three-dimensional (3D) structures. This new automated deep-learning AI software from SRC Stereologer comes with the capability of detecting two cell types (i.e., NeuN - neuron stain, and Iba-1 - microglia stain), with further possibility of learning. This automatization approach uses deep learning AI in a 2-step process: first, the network "learns" the desired cells of interest by processing ground truth via images marked to show the cells of interest. Then, this technology uses this information to calculate the total number of cells of interest using the optical fractionator and stereological approach. For MUN researchers in neuroscience and related fields, access to stereology with AI will enable us to collect high-quality data on an internationally reputable scale in a time- and cost-efficient manner. With recent developments in the AI module (product of National Institute of Health initiative), cell counting is 30-60 times faster and far more accurate compared to the labor-intensive and error-prone manual method that is currently our only option. Since MUN is the only university of the island of Newfoundland, there is no practical alternative for MUN researchers to access stereology equipment. The requested equipment will allow for the growth of dozens of NSERC-funded research programs at MUN and the training of ~200 HQP each year. This stereology unit will accelerate productivity and discovery, while allowing our researchers and students to stay internationally competitive in our pursuit of advancing knowledge of the nervous system.