Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan; Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan.
Laboratory for Brain Connectomics Imaging, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
Neuroimage. 2022 Apr 15;250:118965. doi: 10.1016/j.neuroimage.2022.118965. Epub 2022 Feb 2.
Localising accurate brain regions needs careful evaluation in each experimental species due to their individual variability. However, the function and connectivity of brain areas is commonly studied using a single-subject cranial landmark-based stereotactic atlas in animal neuroscience. Here, we address this issue in a small primate, the common marmoset, which is increasingly widely used in systems neuroscience. We developed a non-invasive multi-modal neuroimaging-based targeting pipeline, which accounts for intersubject anatomical variability in cranial and cortical landmarks in marmosets. This methodology allowed creation of multi-modal templates (MarmosetRIKEN20) including head CT and brain MR images, embedded in coordinate systems of anterior and posterior commissures (AC-PC) and CIFTI grayordinates. We found that the horizontal plane of the stereotactic coordinate was significantly rotated in pitch relative to the AC-PC coordinate system (10 degrees, frontal downwards), and had a significant bias and uncertainty due to positioning procedures. We also found that many common cranial and brain landmarks (e.g., bregma, intraparietal sulcus) vary in location across subjects and are substantial relative to average marmoset cortical area dimensions. Combining the neuroimaging-based targeting pipeline with robot-guided surgery enabled proof-of-concept targeting of deep brain structures with an accuracy of 0.2 mm. Altogether, our findings demonstrate substantial intersubject variability in marmoset brain and cranial landmarks, implying that subject-specific neuroimaging-based localization is needed for precision targeting in marmosets. The population-based templates and atlases in grayordinates, created for the first time in marmoset monkeys, should help bridging between macroscale and microscale analyses.
由于每个实验物种的个体差异,准确定位大脑区域需要在每个实验物种中进行仔细评估。然而,在动物神经科学中,通常使用基于单个个体颅部地标点的立体定向图谱来研究大脑区域的功能和连接。在这里,我们在一种小型灵长类动物——普通狨猴中解决了这个问题,普通狨猴在系统神经科学中越来越广泛地被应用。我们开发了一种非侵入性的多模态基于神经影像学的靶向定位方法,该方法考虑了狨猴颅骨和皮质地标点的个体间解剖学变异性。这种方法允许创建多模态模板(MarmosetRIKEN20),包括头部 CT 和脑磁共振图像,嵌入在前连合和后连合(AC-PC)以及 CIFTI 灰度坐标的坐标系中。我们发现,立体定向坐标的水平面相对于 AC-PC 坐标系在俯仰方向上有明显的旋转(向下 10 度),并且由于定位程序,存在明显的偏差和不确定性。我们还发现,许多常见的颅部和大脑地标点(例如,额骨、顶内沟)在个体之间的位置不同,并且相对于平均狨猴皮质面积尺寸有很大的差异。将基于神经影像学的靶向定位方法与机器人引导手术相结合,实现了对深部脑结构的精准靶向,精度达到 0.2 毫米。总之,我们的研究结果表明,狨猴大脑和颅骨地标点存在明显的个体间变异性,这意味着需要针对特定个体的基于神经影像学的定位来实现狨猴的精准靶向。首次在狨猴中创建的基于群体的灰度坐标模板和图谱应该有助于弥合宏观和微观分析之间的差距。