Abstract：
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, we developed a cytoarchitectonic landmark identification pipeline. The fluorescence micro-optical sectioning tomography method was employed to image the whole mouse brain stained by general fluorescent nucleotide dye. A fast 3D convolution network was subsequently utilized to segment neuronal somas in entire neocortex. By approach, the cortical cytoarchitectonic profile and the neuronal morphology were analyzed in 3D, eliminating the influence of section angle. And the distribution maps were generated that visualized the number of neurons across diverse morphological types, revealing the cytoarchitectonic landscape which characterizes the landmarks of cortical regions, especially the typical signal pattern of barrel cortex. Furthermore, the cortical regions of various ages were aligned using the generated cytoarchitectonic landmarks suggesting the structural changes of barrel cortex during the aging process. Moreover, we observed the spatiotemporally gradient distributions of spindly neurons, concentrated in the deep layer of primary visual area, with their proportion decreased over time. These findings could improve structural understanding of neocortex, paving the way for further exploration with this method.
摘要：
新皮质是一个复杂的结构，具有不同的皮质亚层和区域。然而,皮层区域的精确定位可能是具有挑战性的，因为没有特殊的准备工作就没有明显的地标。为了应对这一挑战，我们开发了一个细胞建筑学地标识别管道。采用荧光显微光学切片层析成像方法对普通荧光核苷酸染料染色的整个小鼠脑进行成像。随后使用快速3D卷积网络来分割整个新皮层中的神经元体。通过方法，在3D中分析了皮质细胞结构和神经元形态，消除截面角度的影响。生成了分布图，将不同形态类型的神经元数量可视化，揭示了表征皮质区域地标的细胞建筑学景观，尤其是桶状皮层的典型信号模式。此外，使用产生的细胞结构标志将不同年龄的皮质区域对齐，表明桶状皮质在衰老过程中的结构变化。此外，我们观察到细长神经元的时空梯度分布，集中在初级视觉区域的深层，他们的比例随着时间的推移而下降。这些发现可以提高对大脑皮层的结构理解，为该方法的进一步探索铺平了道路。
