Sandoval Ortega Raquel Adaia, Li Emmy, Joseph Oliver, Dufour Pascal A, Corder Gregory
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
eNeuro. 2025 Jun 3;12(6). doi: 10.1523/ENEURO.0233-24.2025. Print 2025 Jun.
The rodent brain contains 70,000,000+ neurons interconnected via complex axonal circuits with varying architectures. Neural pathologies are often associated with anatomical changes in these axonal projections and synaptic connections. Notably, axonal density variations of local and long-range projections increase or decrease as a function of the strengthening or weakening, respectively, of the information flow between brain regions. Traditionally, histological quantification of axonal inputs relied on assessing the fluorescence intensity in the brain region of interest. Despite yielding valuable insights, this conventional method is notably susceptible to background fluorescence, postacquisition adjustments, and inter-researcher variability. Additionally, it fails to account for nonuniform innervation across brain regions, thus overlooking critical data such as innervation percentages and axonal distribution patterns. In response to these challenges, we introduce AxoDen, an open-source semiautomated platform designed to increase the speed and rigor of axon quantifications for basic neuroscience discovery. AxoDen processes user-defined brain regions of interests incorporating dynamic thresholding of grayscale-transformed images to facilitate binarized pixel measurements. Here, in mice, we show that AxoDen segregates the image content into signal and nonsignal categories, effectively eliminating background interference and enabling the exclusive measurement of fluorescence from axonal projections. AxoDen provides detailed and accurate representations of axonal density and spatial distribution. AxoDen's advanced yet user-friendly platform enhances the reliability and efficiency of axonal density analysis and facilitates access to unbiased high-quality data analysis with no technical background or coding experience required. AxoDen is available to everyone as a valuable neuroscience tool for dissecting axonal innervation patterns in precisely defined brain regions.
啮齿动物的大脑包含7000万个以上的神经元，这些神经元通过具有不同结构的复杂轴突回路相互连接。神经病理学通常与这些轴突投射和突触连接的解剖学变化有关。值得注意的是，局部和远程投射的轴突密度变化分别随着脑区之间信息流的增强或减弱而增加或减少。传统上，轴突输入的组织学定量依赖于评估感兴趣脑区的荧光强度。尽管这种传统方法提供了有价值的见解，但它特别容易受到背景荧光、采集后调整和研究人员之间差异的影响。此外，它没有考虑到脑区之间神经支配的不均匀性，从而忽略了诸如神经支配百分比和轴突分布模式等关键数据。为应对这些挑战，我们引入了AxoDen，这是一个开源的半自动化平台，旨在提高轴突定量的速度和严谨性，以用于基础神经科学发现。AxoDen处理用户定义的感兴趣脑区，结合灰度转换图像的动态阈值处理，以方便二值化像素测量。在这里，在小鼠中，我们表明AxoDen将图像内容分为信号和非信号类别，有效消除背景干扰，并能够专门测量轴突投射的荧光。AxoDen提供了轴突密度和空间分布的详细准确表示。AxoDen先进但用户友好的平台提高了轴突密度分析的可靠性和效率，并便于获得无偏倚的高质量数据分析，无需技术背景或编码经验。AxoDen作为一种有价值的神经科学工具，可供所有人使用，用于剖析精确界定脑区的轴突神经支配模式。
